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Cognitive Security Market Size & Share, Future Growth, Trends Evaluation, Demands, Regional Analysis and Forecast to 2027, by report ocean Market…
Cognitive Security market report contains detailed information on factors influencing demand, growth, opportunities, challenges, and restraints. It provides detailed information about the structure and prospects for global and regional industries. In addition, the report includes data on research & development, new product launches, product responses from the global and local markets by leading players. The structured analysis offers a graphical representation and a diagrammatic breakdown of the Cognitive Security market by region.
Cognitive security market in IT & telecommunication is expected to reach $3.68 billion by 2023 growing at a CAGR of 30.36% during the forecast period.
Cognitive Security Market In IT & Telecommunication: Global Drivers Restraints Opportunities Trends and Forecasts up to 2023
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Overview:The Cognitive Security Market in It & Telecommunication is defined as security that uses data mining machine learning natural language processing (NLP) and human-computer interface for securing data from cyber-attacks and virus. In addition the cognitive system even helps in analyzing the security developments and discrete the structured and unstructured information data into relevant information. It also provides security to businesses and helps in improving the productivity of the business. The increasing shift toward the use of cognitive security services for data storage of confidential and private data of an organization and the rise in employee mobility contribute to the need for cognitive security in IT & telecommunication.
With the increasing adoption of the cloud-based services in various business platforms such as enterprize business has led to the need to secure the information of organizations. The implementation of cloud-based cognitive security by small and medium enterprises is increasing rapidly and fuels the growth of the market.
Market Analysis:According to Reportocean Research the cognitive security market in IT & telecommunication is expected to reach $3.68 billion by 2023 growing at a CAGR of 30.36% during the forecast period. Cognitive security is widely being adopted across diverse set of industries for the protection of crucial information that includes public safety and utility companies. An increase in the adoption of the cloud-based services and the Internet across the IT & telecommunication sector the need to protect the data has irapidly increased.Furthermore the Americas is experiencing significant growth due to the developed infrastructure in the region boosting the cognitive security market followed by APAC and EMEA during the forecast period.
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Market Segmentation Analysis:The report provides a wide-range evaluation of the market. It provides an in-depth qualitative insights historical data and supportable projections and assumptions about the market size. The projections featured in the report have been derived using proven research methodologies and assumptions based on the vendors portfolio blogs whitepapers and vendors presentations. Thus the research report serves every side of the market and is segmented based on regional markets deployment organization size and end-users.
Countries and Vertical Analysis:The report contains an in-depth analysis of the vendor profiles which includes financial health business units key business priorities SWOT strategy and views; and competitive landscape. The key and the prominent vendors covered in the report include Intel Security XTN Symantec Corporation IBM Corporation Cisco Systems CA Technologies Inc. CSC Fortinet Inc. Cato Networks and Check Point Software Technologies. Most of the major players are in the Americas. The vendors have been identified based on the portfolio geographical presence marketing & distribution channels revenue generation and significant investments in R&D.
The counties covered in report are Canada the US China India Japan and Germany. Among these Japan the US and China are expected to grow at a high rate during the forecast period (2017-2023) owing to an increase in the penetration rate of e-commere connected devices and increasing number of data centers.
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Competitive AnalysisThe report covers and analyzes the cognitive security market. Various strategies such as joint ventures partnerships collaborations and contracts have also been included accordingly. In addition as customers are in search for better solutions a rising number of partnerships is expected. There is likely to be an increase in the number of mergers acquistions and strategic partnership during the forecast period.
The report includes a complete insight of the industry and aims to provide an opportunity for the emerging and established players to understand the market trend current scenario initiative taken by government and the latest technology related to the market. In addition it also helps the venture capitalists in understanding the companies better and take informed decisions.
Regional AnalysisThe Americas is the dominating region which holds the largest share for of the cognitive security market owing to the high adoption of cloud security by small and medium size enterprises as the benefits and cost factors are advantageous. In addition they have the largest base for technological innovations and adoption and are primarily one of the global producers of automation equipment and is home to several domestic industries.
Asia Pacific is among the fastest growing markets for cognitive security. The region boasts of major developing economies with focus on the increasing data centers and the growing penetration rate of connected devices across this region. In addition the government is focused on ICT infrastructure development owing to the increasing demand for safety and security of information. EMEA is the third largest contributor to the cognitive security market due to the increasing demand from the IT industries. The companies are utilizing IoT analytics cloud and various tools to differentiate their services.
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Cloud-based solution is the major driving factor in the region. The proliferation of connected devices such as smartphones tablets laptops and drones is driving the market in the region. The major telecommunication industries are also partnering with cognitive security vendors to secure their products and services. Thus the Cognitive Security Market in IT & Telecommunication is expected to witness significant growth in this region.
Benefits
The report provides an in-depth analysis of the cognitive security market aiming to secure the data and services reduce operational cost improve business efficiency and operational performance. With the help of cognitive security various organizations can increase the productivity and efficiency and can ensure the protection of the data. They can easily be integrated with other applications. They can be installed either on-premises or even through the network of the vendors. In addition the solutions are proven to be reliable and improves scalibility. The report discusses about the organization size deployment mode end-users and regions. Further the report provides details about the major challenges impacting the market growth.
Region/Country Cover in the Report
Regions-Canada the US China India Japan and Germany. Among these Japan the US and China
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Key Players Covered in the Report
Regions- Intel Security XTN Symantec Corporation IBM Corporation Cisco Systems CA Technologies Inc. CSC Fortinet Inc. Cato Networks and Check Point Software Technologies
This report covers aspects of the regional analysis market.The report includes data about North America, Europe, Asia Pacific, Latin America, the Middle East, and Africa.This report analyzes current and future market trends by region, providing information on product usage and consumption.Reports on the market include the growth rate of every region, based on their countries over the forecast period.
What factors are taken into consideration when assessing the key market players?
The report analyzes companies across the globe in detail.The report provides an overview of major vendors in the market, including key players.Reports include information about each manufacturer, such as profiles, revenue, product pricing, and other pertinent information about the manufactured products.This report includes a comparison of market competitors and a discussion of the standpoints of the major players.Market reports provide information regarding recent developments, mergers, and acquisitions involving key players.
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What are the key findings of the report?This report provides comprehensive information on factors expected to influence the market growth and market share in the future.The report offers the current state of the market and future prospects for various geographical regions.This report provides both qualitative and quantitative information about the competitive landscape of the market.Combined with Porters Five Forces analysis, it serves as SWOT analysis and competitive landscape analysis.It provides an in-depth analysis of the market, highlighting its growth rates and opportunities for growth.
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Mobile Ticketing Market 2021 by Top region Data: Global Industry Trends, Share, Size, Demand, Growth Opportunities, Industry Revenue, Future and…
Mobile Ticketing Market to reach USD 4349.8 million by 2027. Mobile Ticketing Market valued approximately USD 705.4 million in 2016 is anticipated to grow with a healthy growth rate of more than 22.4% over the forecast period 2021-2027.
Mobile Ticketing Market report contains detailed information on factors influencing demand, growth, opportunities, challenges, and restraints. It provides detailed information about the structure and prospects for global and regional industries. In addition, the report includes data on research & development, new product launches, product responses from the global and local markets by leading players. The structured analysis offers a graphical representation and a diagrammatic breakdown of the Mobile Ticketing Market by region.
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This report analyzes the global primary production, consumption, and fastest-growing countries in the Information and Communications Technology(ICT) market. Also included in the report are prominent and prominent players in the global Information and Communications Technology Market (ICT).
According to Statista, as of 2021 data, the United States held over ~36% of the global market share for information and communication technology (ICT). With a market share of 16%, the EU ranked second, followed by 12%, China ranked third. In addition, according to forecasts, the ICT market will reach more than US$ 6 trillion in 2021 and almost US$ 7 trillion by 2023. In todays society, continuous growth is another reminder of how ubiquitous and crucial technology has become. Over the next few years, traditional tech spending will be driven mainly by big data and analytics, mobile, social, and cloud computing.
An increasing number of customers have shifted from feature phones to smartphones. Which as a result, showed customers are well acquainted with the functioning of a smartphone. On the other hand, mobile ticketing applications can be easily installed and operated in smartphones. Due to which, wide adoption of smartphones increased rapidly affecting the growth of the global mobile ticketing market, and this trend is estimated to continue over the forecast period.
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The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players.
The detailed segments and sub-segment of the market are explained below:
> By Type> Mobile Ticketing Application> SMS Mobile Ticketing> By Application> Travel Ticketso Airline Ticketso Railway Ticketso Bus TicketsBy Regions:> North America> U.S.> Canada> Europe> UK> Germany> Asia Pacific> China> India> Japan> Rest of the World
Furthermore, years considered for the study are as follows:Historical year 2015Base year 2016Forecast period 2017 to 2025
Some of the key manufacturers involved in the market are Bytemark, Corethree, Eventbrite, Gemalto, Masabi, ShowClix, Bizzabo, eos. uptrade, Margento, Open Mobile Ticketing Alliance, StubHub, Tick Pick Acquisitions and effective mergers are some of the strategies adopted by the key manufacturers. New product launches and continuous technological innovations are the key strategies adopted by the major players.
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Target Audience of the Global Mobile Ticketing in Market Study:> Key Consulting Companies & Advisors> Large, medium-sized, and small enterprises> Venture capitalists> Value-Added Resellers (VARs)> Third-party knowledge providers> Investment bankers
TABLE OF CONTENTSChapter 1. Global Mobile Ticketing Market Definition and Scope1.1. Research Objective1.2. Market Definition1.3. Scope of The Study1.4. Years Considered for The Study1.5. Currency Conversion Rates1.6. Report LimitationChapter 2. Research Methodology2.1. Research Process2.1.1. Data Mining2.1.2. Analysis2.1.3. Market Estimation2.1.4. Validation2.1.5. Publishing2.2. Research AssumptionChapter 3. Executive Summary3.1. Global & Segmental Market Estimates & Forecasts, 2015-2025 (USD Billion)3.2. Key TrendsChapter 4. Global Mobile Ticketing Market Dynamics4.1. Growth Prospects4.1.1. Drivers4.1.2. Restraints4.1.3. Opportunities4.2. Industry Analysis4.2.1. Porters 5 Force Model4.2.2. PEST Analysis4.2.3. Value Chain Analysis4.3. Analyst Recommendation & Conclusion
Chapter 5. Global Mobile Ticketing Market, By Type5.1. Market Snapshot5.2. Market Performance Potential Model5.3. Global Mobile Ticketing Market, Sub Segment Analysis5.3.1. Mobile Ticketing Application5.3.1.1. Market estimates & forecasts, 2015-2025 (USD Billion)5.3.1.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)5.3.2. SMS Mobile Ticketing5.3.2.1. Market estimates & forecasts, 2015-2025 (USD Billion)5.3.2.2. Regional breakdown estimates & forecasts, 2015-2025 (USD Billion)Chapter 6. Global Mobile Ticketing Market, By Application7.1. Market Snapshot7.2. Market Performance Potential Model7.3. Global Mobile Ticketing Market, Sub Segment Analysis
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Final Report will add the analysis of the impact of COVID-19 on this industry.
a large number of indigenous manufacturers of syringes and needles have managed to come up. However, it does not mean that imports are low for this market. Imports, as in the case with other medical devices, are quite high but the domestic manufacturers have been able to tap foreign markets through increasing exports. The target base of consumers is growing steadily which is expected to significantly boost sales in the market.
It begins with the introduction section which mentions the features and uses of syringes and needles along with a brief description of the various phases in their development. The market overview section provides an insight into the market and highlights the market size. Import and export figures for syringes and needles, both in terms of volume and value have been provided in the next section. It also includes the regional break-up of the imports and exports.
An analysis of the drivers explains the factors leading to the growth of the market which include increasing need of insulin doses, increasing demand for vaccines, improving health infrastructure, growing incidence of diseases, changing demographics and health check-up packages. Some of the major challenges to the market are illegal recycling of syringes and needles and problems associated with usage. Government legislation in the market has been discussed in the next section.The competition section highlights the features of the major players operating in the market. A brief profile of the major domestic and foreign players in the market along with their financials has been included in this section.
A section providing strategic recommendations has been given at the end of the report which gives effective solutions to existing and potential players for improving market share and increasing profitability. The Market report answers the following questions:
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What is the aim of the report?
Based on various indicators, the Year-on-Year growth (%) and compound annual growth rate (CAGR) for the given forecast period is offered.An overview of the Market based on geographical scope, market segmentation and financial performance of key players is presented in the report.The report presents current trends in the industry and future scope of the Market in North America, Asia Pacific, Europe, Latin America and Middle East and Africa.The various parameters accelerating the growth of Market are incorporated in the research report.The report analyses growth rate, market size and valuation of the Market during the forecast period.
What aspects regarding the regional analysis Market are included in this report?
Geographical regions covered in the report include North America, Europe, Asia Pacific, Latin America and Middle East and Africa region.The report consists of detailed region-wise analysis of current and future market trends, providing information on product usage and consumption.The growth rate of the market in every region, including their countries over the forecast period is included in the market report.Based on what factors are the key market players assessed in this report?The report offers detailed analysis of leading companies in the market across the globe.It provides details of the major vendors involved in the Market including Key PlayersA comprehensive overview of each company including the company profile, generated revenue, pricing of goods andthe manufactured products is incorporated in the report.The facts and figures about market competitors along with standpoints of leading market players are presented in the report.The recent developments, mergers and acquisitions related to mentioned key players are provided in the market report.
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What is the key information extracted from the report?
Extensive information on factors estimated to affect the Market growth and market share during the forecast period is presented in the report.The report offers the present scenario and future growth prospects Market in various geographical regions.The competitive landscape analysis on the market as well as the qualitative and quantitative information is delivered.The SWOT analysis is conducted along with Porters Five Force analysis.The in-depth analysis provides an insight into the Market, underlining the growth rate and opportunities offered in the business.
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The Cult of Statistical Significanceand the Neglect of Oomph – Walter Bradley Center for Natural and Artificial Intelligence
A central part of John Maynard Keynes explanation of the Great Depression was his assertion that household income affects household spending. When people lose their jobs and income, they cut back on their spending, which causes other people to lose their jobs and their income propelling the economy downhill.
Keynes theory was based on logic and common sense. It was later tested empirically with household survey data and with national income data compiled by the National Bureau of Economic Research.Figure 1shows U.S. after-tax personal income and consumer spending for the years 1929 through 1940. Since income and spending both tend to grow over time along with the population, the data were converted to annual percentage changes.
The observed statistical relationship is highly statistically significant. If there were no relationship between income and spending, the chances of a correlation as high as that shown in Figure 1 would be0.000000002.
It is not all about statistical significance, however. Keynes argument hinges on changes in income having a substantial effect on spending. The slope of the line in Figure 1 is 0.83, which supports Keynes argument about the importance of the linkage between income and spending. Specifically, a 1 percent increase (or decrease) in income is predicted to increase (or decrease) spending by 0.83 percent.
Suppose, however, that the data were those shown in Figure 2. The relationship is statistically significant, but the slope is only 0.01. When income goes up or down by 1 percent, spending is predicted to increase or decrease by a negligible one-hundredth of a percent, which would undercut Keynesargument completely.
Empirical studies should report both statistical persuasiveness and whether the estimated coefficients are substantial and plausible. It is not plausible that anincrease in income would reduce spending or that it would increase spending by more than the increase in income. Thus, a statistically significant relationship between income and spending with a slope of 1.2 or +3.4 would be a reason for distress, not celebration. Instead of rushing off to publish counter-intuitive findings, we should investigate the reasons for the implausible results.
Figure 3 is another example a fourth order polynomial that gives a good fit with every coefficient statistically significant. Yet, the model has clearly gone off the tracks predicting that spending increases when there is a 12 percent drop in income and that spending falls when there is a 6 percent increase in income. When the data can be plotted in a simple scatter diagram, like Figure 3, it is obvious that, despite the statistically significant coefficients, the results are useless. However, these flaws are more difficult to detect in models with multiple explanatory variables. What is certain is that the success of a model cannot be assessed solely by looking at the statistical significance of the coefficients.
Economists have been criticizedsharply and repeatedly by Deirdre McCloskey forconfusing statistical significance with practical importance (what she calls oomph).A widespread focus on statistical significance rather than practical importance has also been found in dozens of papers published in the fields of psychology, education, and epidemiology.
Ananya Sen, Claire Van Note, and I analyzed 306 empirical papers that werepublished duringthe years 2010-2019inMIS Quarterly,generally considered to be one of the top information systems journals, to see whether these papers were fixated on statistical significance at the expense of practical importance. They were.
We found that78 percent of the papers used statistical significance alone to judge the success of their models. Many focused on counting the number ofstatisticallysignificantresults, with little concern for practical importance; for example, these authors reported statistical significance for nine of their ten hypotheses:
Table 5 summarizes the converged results of the model. As we can see, the fixed effects of apps, off-hour accesses, conf, off-site accesses, and log(DeptSize) all significantly support H1, H2, H3, H4, and H5(a). The cross-level interaction terms are significant, except Apps*Log(DeptSize), therefore supporting H6(c), H6(d) H6(e), and H6(f), but not H6(b).
Wheres an assessment of the oomph? Nowhere to be seen.
Another study investigated the factors affecting German household decisions to adopt smart metering technology (SMT) for monitoring electricity consumption. One factor they considered was household income:Consumers with higher income are able to spend on environmental friendly devices such as SMT and are more likely to adopt it, but the researchers do not say how much more likely they do not consider the practical importance of their findings. Nor did their paper give enough information for readers to judge for themselves.
The authors write that,Intention is the subjective probability that a person will perform a certain behavior; however, I contacted the authors and learned that their intention variable is not a probability but, instead, the average value of each households response to three questions on a Likert scale of 17. Similarly, the income explanatory variable is defined asthe average income of the consumers, but we are not told whether it is weekly, monthly, or annual income and whether the data are recorded in euros, thousands of euros, or some other unit. It turns out that the data are monthly income measured in thousands of euros. All this detective work yields our oomph answer: a 1000-euro increase in monthly household income is predicted to increase a households intention to adopt SMT on a 17 Likert scale by a trifling 0.062.
There are two related problems with a myopic focus on statistical significance. First, it encourages data mining and data torturing in a quest for statistically significant results. Second, models that are judgedby statistical significance rather than the plausibility of the coefficients are apt to fare poorly with fresh data.
This misplaced focus on statistical significance is aninherent weakness of deep neural networks and other black box models, since computer algorithms do not understand the world in any relevant sense and consequently cannot assess oomph or plausibility. Black box algorithms would happily choose the useless fourth-order polynomial in Figure 3.
Sound reliable empirical analyses are enhanced by de-emphasizing statistical significance and focusing, instead, on expert assessments of a models credibility and oomph.
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SensOre releases technology and exploration update ahead of the new year – Proactive Investors UK
Currently, the minerals targeting company is looking to attract direct investment for its portfolio of lithium and nickel targets.
SensOre Ltd has provided a technology and exploration update ahead of the new year.
Currently, the minerals targeting company, which intends to list on the ASX next quarter, is looking to attract direct investment for its portfolio of lithium and nickel targets.
In other news, the company is on the hunt for new gold targets in WA with a series of exploration partners.
Looking at the big picture, SensOre has also passed the 20,000-metre drilling milestone on its wholly-owned and joint venture projects.
SensOres data mining for lithium prospectivity in WA has opened up new pegmatite opportunities.
To date, promising results from SensOres first lithium prospectivity runs have attracted international interest in funding expanded regional search opportunities.
SensOre chief operating officer Robbie Rowe said: These first predicted lithium targets are now possible due to SensOres continued investment in a massive geochemical data cleaning program combined with geology transformation and WA state-wide geophysical compilation programs.
SensOres Discriminant Predictive Targeting (DPT) technology for nickel has generated previously unidentified nickel potential on open ground.
Fast on the heels of delivering the Yilgarn nickel targets to BHP, the company has honed in on new opportunities in the Albany-Fraser and other parts of WA.
Combined with the Auralia Project in which SensOre holdsina 70% joint venture with a Chalice Mining Ltd (ASX:CHN, OTCQB:CGMLF) subsidiary these new, top-ranking nickel target applications on open tenure extend the known nickel search space in WA.
The company is now analysing high-ranking nickel targets on third-party tenure that could form acquisition targets in early 2022. Initial applications are now in place, with more to follow.
SensOre has also commenced partnering discussions to fund exploration on its 100%-owned targets.
In the meantime, SensOre and DGO Gold Ltd (ASX:DGO) have expanded their gold exploration activities.
This includes adding new targets to the Yilgarn Exploration Ventures joint venture and jointly approaching third parties to acquire new acreage in the WA Goldfields.
The next stage of the joint venture builds on the exploration activities conducted in the last two years over multiple projects.
SensOres collaboration with Great Boulder Resources Ltd (ASX:GBR) has opened up potential on eastern portions of the Tea Well Project, trending south from Mulga Bill.
SensOres subsidiary, Yilgarn Exploration Ventures, completed an extension of a gravity geophysical survey over the Tea Well project in collaboration with GBR.
The survey has extended coverage of the eastern flank of the Polelle syncline sequence east of the Meekatharra mining camp and south of the Mulga Bill prospect.
Promisingly, results have identified a series of previously untested gravity low features on the Tea Well Project tenure under shallow transported cover, indicating lower density lithologies within the basement mafic volcanic north-south trending sequence.
SensOre is also advancing discussions with several top-tier Australian technology companies about developing a proprietary Data Cube platform to service current and future mining sector clients.
Finally, SensOre has exercised its option in relation to the Moonera prospect.
Following infill geophysical programs in mid-2021, drilling is now planned in early 2022 to test a large, 7-kilometre geophysical feature, which is interpreted as a carbonatite-intrusive centre prospective for rare earth elements and copper.
Phase one drilling at Moonera is eligible for co-funding under the WA Government EIS program after a successful application was awarded in 2021.
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SensOre releases technology and exploration update ahead of the new year - Proactive Investors UK
The relationship between objective app engagement and medication adherence in asthma and COPD: a retrospective analysis | Scientific Reports -…
Recruitment and eligibility
Data used in this retrospective analysis was collected from participants who enrolled in a digital self-management platform (Propeller Health, WI, USA) between January 2018 and March 2019. Participants who enrolled in the platform were recruited via social media campaigns (e.g., Facebook advertisements), and needed to own a smartphone and have a self-reported history of asthma and/or COPD to be eligible. All participants agreed to the platforms Terms of Service.
Data was examined retrospectively using an aggregated dataset. To be included in the analysis, participants needed to be18years of age, reside in the United States, and have a controller inhaler compatible with an electronic medication monitor (EMM). Participants also needed to have at least 97days of controller medication use data (the first seven days of participation was considered an onboarding period). The retrospective analysis plan was determined to be exempt and consent was waived by the Copernicus Independent Review Board (PRH1-18-132). A subset of data used in this retrospective analysis included data previously collected from an electronic survey to which patients provided consent (Protocol 20191728). All methods were carried out in accordance with relevant guidelines and regulations.
Propeller Health is an FDA-cleared digital platform that includes an EMM, and a paired smartphone app targeted to the users self-reported condition (asthma or COPD) (Fig.1).
A small FDA-cleared electronic medication monitor (EMM) is attached to the users controller medication inhaler to capture the date and time of use. Data from the EMM is then transferred wirelessly via Bluetooth to a paired smartphone app providing feedback, insights and medication reminders.
Electronic medication monitors (EMMs) attach to a compatible inhaler medication to passively capture the date and time of use. Usage data is then wirelessly transferred via Bluetooth to a paired smartphone app. The EMM has a battery life of 1218months and does not require charging11. Compatible medications include inhaled corticosteroids (ICS), long-acting beta-agonists (LABA), long-acting muscarinic antagonists (LAMA), and combination therapies (ICS+LABA, LABA/LAMAs and triple therapy).
The paired smartphone app serves not only to collect data from the EMM, but also to engage the user through evidence-based asthma and/or COPD content, including relevant guideline content20,21, feedback on medication use and trends, and schedule-based medication reminders through the EMM and smartphone application. Patients with continued poor medication adherence may be presented with additional gamified features and challenges aimed at improving daily medication adherence. The app also prompts users to complete an in-app Asthma Control Test (ACT) or COPD Assessment Test (CAT) at baseline and monthly thereafter to better assess disease control and burden, respectively (Supplementary Fig.1a,b).
We examined app engagement, defined by daily app opens and app active session duration, as the independent variable. Daily app engagement was defined differently for each model estimate to explore the varying associations of duration on controller medication adherence: Model 1 (no app open vs. any app open regardless of session duration) and Model 2 (no app open vs. at least one app open with<1, 1<5, 510 and 10+minutes of total daily app session duration).
Controller inhaler use was determined using data collected from the EMM, which recorded the date and time of each inhaler actuation. Adherence was calculated by dividing the number of EMM-recorded actuations by the prescribed number of actuations (reported by the participant during enrollment)100 per day.
For the primary analyses, the outcome of controller medication use was dichotomously defined as having taken at least 1 actuation vs. no actuation per day.Controller adherencewas dichotomized because daily adherence was either 0% or 100% on the majority of participant-days (74%). For secondary analyses, controller medication use was defined as being 100% adherent vs.<100% per day. Being 100% adherent was defined as having EMM-recorded controller actuations that were greater than or equal to the total number of prescribed actuations for that day.
Symptom control was assessed with the Asthma Control Test (ACT), a self-administered, validated questionnaire for patients with asthma. The 5-item assessment asks respondents to rate their symptoms on a scale of 15. A score>19 indicates good symptom control, 1519 indicates not well-controlled symptoms, and<15 indicates very poorly controlled symptoms22.
Disease burden for participants with COPD was assessed with the COPD Assessment Test (CAT). The 8-item self-administered questionnaire asks respondents to rate their symptoms on a scale of 15. Summative scores<20 indicate lower disease burden, and scores20 indicate higher disease burden23.
Longitudinal, mixed-effects logistic regressions were used to estimate the association between daily app engagement and daily controller medication adherence during days 897 of EMM use for asthma and COPD, adjusting for age, gender, smartphone type (iOS vs. Android), baseline disease status (defined as initial ACT or CAT score), rescue medication use, day on platform and US Census-derived neighborhood-level income and education. Analyses were also stratified by age and disease severity. Stratification by age was completed for participants 40years and older to allow for comparisons between asthma and COPD. Odds ratios and 95% confidence intervals (CI) were presented, with alpha=0.05 as the significance threshold.
Representatives from the study sponsors (Propeller Health, Council of State and Territorial Epidemiologists) were involved in the study design, collection, analysis and interpretation of data, writing of the report, and in the decision to submit the paper for publication. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.
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Top 10 online courses on Coursera and how they help you upskill – Telegraph India
Summary
Online upskilling platforms like Coursera are bridging the massive skills gap between professionals and industries
Most in-demand courses on Coursera are on Data Science, Machine Learning, Web Development, Finance, Mental Wellbeing
Emerging technologies and dynamic changes have rendered a large number of Indian professionals unsuitable for the evolving job market. You can avoid this massive upskilling gap by being part of the recent digital revolution in the education sector where online platforms aim to get students and professionals job-ready.
A major player in the online education space, Coursera brings courses offered by top global universities and leading technology companies under one umbrella and offers them to young professionals.
Here are the most in-demand courses on Coursera:
This popular course will give you a general overview of Machine Learning, Data Mining and Statistical Pattern Recognition in just 11 weeks. Drawing from numerous case studies and applications, itll teach you how to apply algorithms to the development of smart robots, text understanding, computer vision, medical informatics, and audio and database mining. Here youll also learn theory as well as practical know-how, enabling you to apply Machine Learning techniques to resolve new problems.
Click here to learn more.
The target of this course is to teach everyone the fundamentals of Computer Programming using Python. You'll go over the fundamentals of building a programme from a set of simple instructions. There are no prerequisites for this course, which avoids all but the most basic mathematics. Anyone with a basic understanding of computers should be able to understand the material in this course. Once you complete this curse, youll be ready to deal with more advanced courses.
Click here to learn more.
This course will teach you the skills required to apply for entry-level data analyst jobs. Here youll get introduced to the world of Data Analytics through a hands-on curriculum created by Google. Other than learning key topics in this field, youll get an overview of whats to come in the Google Data Analytics Certificate. Youll be aided by Google data analysts and the best tools and resources.,
Click here to learn more.
Designed for non-native English speakers, this course is for anyone who wants to advance their careers in the global marketplace. Here youll learn job search, application and interviews. Other than offering the opportunity to explore your career options, youll also be able to expand your vocabulary and improve your language skills in order to achieve your professional goals.
Click here to learn more.
Here youll get an overview of current practices and analysis of the financial markets. Emphasising finance-based leadership roles, this course will also teach you future prospects of risk management and behavioural finance principles. It is designed to help students and young professionals understand how the securities, insurance and banking industries work in the real world.
Click here to learn more.
In this four-week-long course, you will learn the fundamental tools that every web page coder should be familiar with. It starts from the ground up, teaching how to use HTML and CSS to create modern web pages. Then you will learn the more complex industry-level aspects of web designing.
Click here to learn more.
This four-week long course will give you easy access to the invaluable learning techniques used by experts in a wide range of fields like art, music, literature, maths, science and sports. You'll also get to know about illusions, memory techniques, dealing with procrastination and best practices. Here youll get introduced to recent research and learn how to master difficult subjects.
Click here to learn more.
In this course, youll complete a series of challenges aimed at increasing your happiness and developing more productive habits. The four-week-long course reveals misconceptions about happiness, annoying features of the mind and research that can help us change as preparation for these tasks. After completion of this course, youll learn to incorporate specific wellness activities in your life.
Click here to learn more.
Mental-health awareness has emerged as one of the most alarming aspects of the 21st century. In this course, youll learn about perception, communication, learning, memory, decision-making, persuasion, emotions and social behaviour. Through this course, youll get to know how these aspects of the mind differ among people, how they are wired up in our brain and how they break down as a result of illness or injury.
Click here to learn more.
Googles foundation course on UX design focuses on how people interact with products such as websites, mobile apps and physical objects. Everyday interactions are made usable, enjoyable, and accessible by UX designers. By the end of this course, youll have a professional UX portfolio including three end-to-end projects.
Click here to learn more.
Last updated on 21 Dec 2021
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Top 10 online courses on Coursera and how they help you upskill - Telegraph India
TrustMining Creating New Benchmark in the Cloud Mining Space By CoinQuora – Investing.com
Cloud mining uses a distant data centre with pooled computing capacity to mine cryptocurrency. Investors do not need to operate the hardware while opting for cloud mining. The mining rigs are housed at a mining company facility. The user needs to register and buy mining contracts to start cloud mining.
TrustMining is a cloud mining and investing firm, lucrative for small investors as it offers minimum requirements to start mining. To swiftly join the crypto market without any upfront costs, it executes all the mining on behalf of the investor. TrustMining currently supports SHA256, Ethash, and Equihash. Investors can choose any algorithm. Moreover, the firm provides a complete guide helping investors choose the right algorithm and choose from a wide range of flexible contracts.
To ensure user privacy, trust cloud mining processes with greater transparency. This open, accessible, and high-quality platform is available to all types of investors worldwide.
Investors prefer Trust cloud mining because of its unique characteristics. Apart from affordable fees for investors to enhance their mining capacity, it empowers investors to choose what suits their needs the best, right from the algorithm to the mining equipments power.
We all are well aware of the meme coins and the way it has been trending in the crypto world. One of the primary faces of meme coins is . The coin has soared and provided investors with record-breaking returns. Not to forget the strongest community backing the coin, the SHIB army.
The cloud mining firm believes in Shiba Inu and its capabilities and will promote it as the crypto of the future. Thus, Shiba Inu will be the community coin and has great potential for investors giving them massive ROI. There will be a 37% bonus for its investors which will even reach up to 60% by 31 December.
TrustMining introduced a giveaway of up to 100 million Shiba Inu coins along with other valuable rewards for lucky investors on the first deposit. The giveaway would be through a mystery box, where investors can win exciting rewards such as unique NFTs, DOGE, and MATIC. This giveaway is available for a limited time only. To sum it up, investors can earn rewards from the pool of 100 million SHIB, Up to 25000 DOGE, Up to 1000 MATIC. And not to forget, the most valuable reward, Crypto Phunks NFT.
Trust cloud minings skilled and constant customer assistance is another reason for its long-term popularity. Their support staff is accessible by live chat, email, phone, etc.
Each component has been carefully structured. The user interface is simple to use. Moreover, this platform can handle both experienced and new miners.
One of the nicest features of Trust cloud mining is that investors may collect their passive profits in any supported cryptocurrencies. In this manner, the investor who supports one coin may earn money in that same crypto. Investors are well aware of how much energy is utilised for mining. The firm is committed to its share of global environmental effects. Thus it uses solar energy for mining.
Unlike other mining service providers, the Trust cloud mining platform pays daily and offers the highest returns compared to other organisations offering similar services. Thus investors dont have to wait for a complete month for their revenue to reach them. TrustMining is a global leader in cloud mining. It is a trusted brand, deploys cutting-edge technology, and offers maximum profit.
Disclaimer: Any information written in this press release does not constitute investment advice. CoinQuora does not, and will not endorse any information on any company or individual on this page. Readers are encouraged to make their own research and make any actions based on their own findings and not from any content written in this press release. CoinQuora is and will not be responsible for any damage or loss caused directly or indirectly by the use of any content, product, or service mentioned in this press release.
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TrustMining Creating New Benchmark in the Cloud Mining Space By CoinQuora - Investing.com
Lundin Mining Corporation’s (TSE:LUN) Stock Has Been Sliding But Fundamentals Look Strong: Is The Market Wrong? – Simply Wall St
Lundin Mining (TSE:LUN) has had a rough week with its share price down 16%. But if you pay close attention, you might gather that its strong financials could mean that the stock could potentially see an increase in value in the long-term, given how markets usually reward companies with good financial health. Particularly, we will be paying attention to Lundin Mining's ROE today.
Return on Equity or ROE is a test of how effectively a company is growing its value and managing investors money. Put another way, it reveals the company's success at turning shareholder investments into profits.
See our latest analysis for Lundin Mining
The formula for return on equity is:
Return on Equity = Net Profit (from continuing operations) Shareholders' Equity
So, based on the above formula, the ROE for Lundin Mining is:
15% = US$734m US$4.8b (Based on the trailing twelve months to September 2021).
The 'return' refers to a company's earnings over the last year. One way to conceptualize this is that for each CA$1 of shareholders' capital it has, the company made CA$0.15 in profit.
So far, we've learned that ROE is a measure of a company's profitability. We now need to evaluate how much profit the company reinvests or "retains" for future growth which then gives us an idea about the growth potential of the company. Assuming all else is equal, companies that have both a higher return on equity and higher profit retention are usually the ones that have a higher growth rate when compared to companies that don't have the same features.
To start with, Lundin Mining's ROE looks acceptable. And on comparing with the industry, we found that the the average industry ROE is similar at 15%. Consequently, this likely laid the ground for the impressive net income growth of 23% seen over the past five years by Lundin Mining. We reckon that there could also be other factors at play here. For example, it is possible that the company's management has made some good strategic decisions, or that the company has a low payout ratio.
As a next step, we compared Lundin Mining's net income growth with the industry and were disappointed to see that the company's growth is lower than the industry average growth of 29% in the same period.
The basis for attaching value to a company is, to a great extent, tied to its earnings growth. Its important for an investor to know whether the market has priced in the company's expected earnings growth (or decline). Doing so will help them establish if the stock's future looks promising or ominous. What is LUN worth today? The intrinsic value infographic in our free research report helps visualize whether LUN is currently mispriced by the market.
Lundin Mining has a three-year median payout ratio of 41% (where it is retaining 59% of its income) which is not too low or not too high. This suggests that its dividend is well covered, and given the high growth we discussed above, it looks like Lundin Mining is reinvesting its earnings efficiently.
Moreover, Lundin Mining is determined to keep sharing its profits with shareholders which we infer from its long history of five years of paying a dividend. Looking at the current analyst consensus data, we can see that the company's future payout ratio is expected to rise to 54% over the next three years. Accordingly, the expected increase in the payout ratio explains the expected decline in the company's ROE to 11%, over the same period.
Overall, we are quite pleased with Lundin Mining's performance. Particularly, we like that the company is reinvesting heavily into its business, and at a high rate of return. As a result, the decent growth in its earnings is not surprising. Having said that, on studying current analyst estimates, we were concerned to see that while the company has grown its earnings in the past, analysts expect its earnings to shrink in the future. To know more about the company's future earnings growth forecasts take a look at this free report on analyst forecasts for the company to find out more.
Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team (at) simplywallst.com.
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
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Assessing Nami’s Two Years at The Helm of FIRS – THISDAY Newspapers
Bernard Okri
In the second week of December 2019, when President Muhammadu Buhari announced the nomination of a certain Muhammad Nami to be the forerunner of the Federal Inland Revenue Service, many were taken by surprise.
Known very well to staff of the FIRS, who he met during his many visits seeking tax clearance and other regulatory documents for his client, Nami was not your populist political appointee at that time. His resume was not partisan. But bold on his resume was the fact that he was a tax man. He had risen at the PKF International to the position of senior consultant in charge of tax management and advisory services, he founded Manam Profesional Services a chartered tax practitioners and business advisers firm. He had also served as a member of the Presidential Audit Committee on Recoveries, recovering loot from looters across the country. He is also a fellow of the Chartered Institute of Taxation, the Chartered Institute of Forensice and Investigation Professionals in Nigeria, the Institute of Debt Recovery Practitioners of Nigeria and an Associate Member of the Nigerian Institute of Management (Chartered) and Association of National Accountants of Nigeria.
If we were to judge by Mr. Namis experience and qualifications, he fits into the character to lead the FIRS. His credentials speak to a sound administrator and tax man indeed. Two years on, since he officially resumed as the Chairman of the FIRS, there is so much to assess of his leadership. What has he done differently? What reforms has he brought to the tax administration space? What legacies is he certain to leave? What makes Mr. Nami a worthy appointee?
When Mr. Nami resumed at the FIRS he is reported to have called his management team together to inform his vision and objectives for his tenure. He summarised what he wanted to achieve in a four-point agenda: to rebuild the FIRS institutional framework; to improve collaboration with stakeholders; to make the FIRS a Customer-centric institution and to make the FIRS a Data-centric institution.
How has he faired on this? On the institutional framework of the FIRS: before he came on board the FIRS was mostly a notorious institution. It had become the financing house for rave events and parties across the big cities in Nigeria. There was corruption here and there. Staff morale was low; most of their jobs had been handed over to consultants. Several allowances had not been paid, and there was no boost to do the work. One of the first things the new FIRS Chairman did was to end the contracts of over 2,000 tax consultants previously hired and gave the job of tax administration back to the FIRS staff. As it should have been.
Under him, the management approved a new structure for the FIRS. The new organogram was designed to create improved service delivery to taxpayers. It introduced taxpayer segmentation where Large Taxpayers, Media Taxpayers and Small Taxpayers offices were created. The Audit and Investigation Departments were also reviewed for effectiveness. With the new boss on ground, the FIRS Annual Corporate Retreat was reintroduced to provide staff the opportunity to discuss their work, network, review the workings of the Service and improve on their capacity to deliver.
Mr. Nami further established the Tax Incentive Management Department to monitor companies and enterprises that were benefitting from tax holidays and tax exemptions, and ensuring that they were not making taxable profits and refusing to pay taxes on those income.
One major legacy of the Mr. Muhammad Nami led FIRS would be his deployment of technology to transform tax administration. He has been consistent in his commentary on this. Tax administrators would remain in the brick and mortar age if they do not bring their work to be in line with technological advancement. As the world progresses, and advancements in technologies are recorded, for any sector of human life to engage with the dynamics of the world, it must be technologically advanced too.
Mr. Nami takes the credit for courageously deploying technology in the FIRS for tax administration. With the amendment of the FIRS Establishment Act through the Finance Act 2020, where the Service was given the powers to use technology for tax administration, the FIRS deployed its home-made solution called Tax-Pro Max to register tax payers, receive filings from them, and receive payments too.
The TaxPro Max is the first of its kind in Nigeria. Its deployment in June this year was a bold move by the FIRS against many odds. It has cut off suspect middle-men from the tax filing processes and has made tax administration far easier and in line with global standards.
It was thus not surprising to see that the FIRS collected N664 billion Naira in the month of June 2021 alone. This was the single highest amount ever collected in a month by the Service since the covid-19 pandemic started.
In line with building a data-centric institution, Mr. Nami set up the Intelligence, Strategic Data Mining and Analysis Department (ISDMA) to deploy analytical tools to analyse data mined from the revolutionary TaxPro Max to properly asses taxpayers.
The FIRS has also improved its relationship with various stakeholders within the government finance networks as well as the security departments and agencies. This has allowed for the Service to receive more information on taxpayers, easily track tax defaulting and enforce compliance.
The world saw all these and honoured Mr. Nami with the extra job of leading the Commonwealth Association of Tax Administrators (CATA) as the associations President. On the 12th of November Mr. Nami was elected unanimously as the President of CATA. This election was a testament to the work that he has been doing here in Nigeria. It was a recognition and an affirmation of his success stories, and the call for him to take leadership of global taxation matters.
In December 2020, the FIRS announced that it had collected a total of N4.95 trillion compared to its target of N5.07 trillion. This was an uncommon feat: it happened despite the covid-19 pandemic, and meant the FIRS had met up to 98% of its target. Mr. Nami has indeed proved the naysayers wrong, countless times. His records in the last two years are enviable and rich. He has kept to his four-point objective in rebranding and reforming the FIRS to be one of Nigerias leading government institutions. He is indeed, as a friend describes him, Nigerias Tax Pilot.
Bernard Okri is the President of the Global Economic Policy Initiative (GEPIn)
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Assessing Nami's Two Years at The Helm of FIRS - THISDAY Newspapers
10 Data Science Terms Every Analyst Needs to Know – Built In
Data science is one of the fields that can be overwhelming for newcomers. The term data science itself can be confusing because its an umbrella term that covers many subfields: machine learning, artificial intelligence, natural language processing, data mining the list goes on.
Within each of these subfields we have a plethora of terminology and industry jargon that overwhelm newcomers and discourage them from pursuing a career in data science.
When I first joined the field, I had to juggle learning the techniques, getting up to date with the research and advancements in the field, all while trying to understand the lingo. Here are ten foundation terms every data scientist needs to know to build and develop any data science project.
More Data Science Career Development4 Types of Projects You Need in Your Data Science Portfolio
One of the most important terms in data science youll hear quite often is model: model training, improving model efficiency, model behavior, etc. But what is a model?
Mathematically speaking, a model is a specification of some probabilistic relationship between different variables. In laypersons terms, a model is a way of describing how two variables behave together.
Since the term modeling can be vague, statistical modeling is often used to describe modeling done by data scientists specifically.
Another way to describe models is how well they fit the data to which you apply them.
Overfitting happens when your model considers too much information about that data. So, you end up with an overly complex model thats difficult to apply to various training data.
More on ModelingA Primer on Model Fitting
Underfitting (the opposite of overfitting) happens when the model doesnt have enough information about the data. In either case, you end up with a poorly fitted model.
One of the skills you will need to learn as a data scientist is how to find the middle ground between overfitting and underfitting.
Cross-validation is a way to evaluate a models behavior when you ask it to learn from a data set thats different from the training data you used to build the model. This is a big concern for data scientists because your model will often have good results on the training data but end up with too much noise when applied to real-life data.
There are different ways to apply cross-validation to a model; the three main strategies are:
The holdout method training data is divided into two sections, one to build the model and one to test it.
The k-fold validation an improvement on the holdout method. Instead of dividing the data into two sections, youll divide it into k sections to reach higher accuracy.
The leave-one-out cross-validation the extreme case of the k-fold validation. Here, k will be the same number of data points in the data set youre using.
Want More? We Got You.Model Validation and Testing: A Step-by-Step Guide
Regression is a machine learning term the simplest, most basic supervised machine learning approach. In regression problems, you often have two values, a target value (also called criterion variables) and other values, known as the predictors.
For example, we can look at the job market. How easy or difficult it is to get a job (criterion variable) depends on the demand for the position and the supply for it (predictors).
There are different types of regression to match different applications; the easiest ones are linear and logistic regressions.
Parameter can be confusing because it has slightly different meanings based on the scope in which youre using it. For example, in statistics, a parameter describes a probability distribution's different properties (e.g., its shape, scale). In data science or machine learning, we often use parameters to describe the precision of system components.
In machine learning, there are two types of models: parametric and nonparametric models.
Parametric models have a set number of parameters (features) unaffected by the number of training data. Linear regression is considered a parametric model.
Nonparametric models dont have a set number of features, so the technique's complexity grows with the number of training data. The most well-known example of a nonparametric model is the KNN algorithm.
In data science, we use bias to refer to an error in the data. Bias occurs in the data as a result of sampling and estimation. When we choose some data to analyze, we often sample a large data pool. The sample you select could be biased, as in, it could be an inaccurate representation of the pool.
Since the model were training only knows the data we give it, the model will learn only what it can see. Thats why data scientists need to be careful to create unbiased models.
Want More on Bias? Theres an Article for That.An Introduction to Bias-Variance Tradeoff
In general, we use correlation to refer to the degree of occurrence between two or more events. For example, if depression cases increase in cold weather areas, there might be some correlation between cold weather and depression.
Often, events correlate by different degrees. For example, following a recipe that results in a delicious dish may have a higher correlation than depression and cold weather. We call this the correlation coefficient.
When the correlation coefficient is one, the two events in question are strongly correlated, whereas if it is, lets say, 0.2, then the events are weakly correlated. The coefficient can also be negative. In that case, there is an inverse relationship between two events. For example, if you eat well, your chances of becoming obese will decrease. Theres an inverse relationship between eating a well-balanced diet and obesity.
Finally, you must always remember the axiom of all data scientists: correlation doesnt equal causation.
You Get Some Data Science, and YOU Get Some Data Science!The Poisson Process and Poisson Distribution, Explained
A hypothesis, in general, is an explanation for some event. Often, hypotheses are made based on previous data and observations. A valid hypothesis is one you can test with results, either true or false.
In statistics, a hypothesis must be falsifiable. In other words, we should be able to test any hypothesis to determine whether its valid or not. In machine learning, the term hypothesis refers to candidate models we can use to map the models inputs to the correct and valid output.
Outlier is a term used in data science and statistics to refer to an observation that lies an unusual distance from other values in the data set. The first thing every data scientist should do when given a data set is to decide whats considered usual distancing and whats unusual.
Dig in to Distributions4 Probability Distributions Every Data Scientist Needs
An outlier can represent different things in the data; it could be noise that occurred during the collection of the data or a way to spot rare events and unique patterns. Thats why outliers shouldnt be deleted right away. Instead, make sure you to always investigate your outliers like the good data scientist you are.
This article was originally published on Towards Data Science.
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10 Data Science Terms Every Analyst Needs to Know - Built In