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    • Hypothesis Testing

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    122 results for "hypothesis testing"

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      Johns Hopkins University

      Hypothesis Testing in Public Health

      Skills you'll gain: General Statistics, Probability & Statistics, Biostatistics, Business Analysis, Data Analysis, Statistical Analysis, Statistical Tests, Basic Descriptive Statistics, Correlation And Dependence, Estimation, Mobile Development, Probability Distribution, iOS Development

      4.8

      (561 reviews)

      Beginner · Course · 1-3 Months

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      University of Colorado Boulder

      Statistical Inference and Hypothesis Testing in Data Science Applications

      Skills you'll gain: General Statistics, Probability & Statistics, Statistical Tests

      4.7

      (23 reviews)

      Intermediate · Course · 1-3 Months

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      SAS

      Introduction to Statistical Analysis: Hypothesis Testing

      Skills you'll gain: Business Analysis, Data Analysis, General Statistics, Probability & Statistics, SAS (Software), Statistical Analysis, Statistical Programming, Statistical Tests, Regression, Correlation And Dependence, Advertising, Algebra, Communication, Journalism, Marketing

      4.6

      (80 reviews)

      Intermediate · Course · 1-4 Weeks

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      Rice University

      Business Applications of Hypothesis Testing and Confidence Interval Estimation

      Skills you'll gain: Business Analysis, Data Analysis, General Statistics, Probability & Statistics, Statistical Analysis, Spreadsheet Software, Statistical Tests, Experiment, Probability Distribution, Microsoft Excel

      4.8

      (1.3k reviews)

      Mixed · Course · 1-4 Weeks

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      Coursera Project Network

      RStudio for Six Sigma - Hypothesis Testing

      Skills you'll gain: General Statistics, Probability & Statistics, Data Science, R Programming

      4.5

      (8 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Hypothesis Testing in R

      Skills you'll gain: Data Analysis, General Statistics, Probability & Statistics, R Programming, Statistical Programming

      4.6

      (21 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

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      Queen Mary University of London

      Hypotheses Testing in Econometrics

      Skills you'll gain: Econometrics, Probability & Statistics

      Intermediate · Course · 1-4 Weeks

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      IBM

      AI Workflow: Data Analysis and Hypothesis Testing

      Skills you'll gain: Business Analysis, Data Analysis, General Statistics, Probability & Statistics, Data Visualization, Exploratory Data Analysis, Statistical Analysis, Data Engineering, Data Science, Machine Learning, Python Programming

      4.2

      (97 reviews)

      Advanced · Course · 1-4 Weeks

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      Tufts University

      Hypothesis Testing with Python and Excel

      Skills you'll gain: Data Analysis, Data Analysis Software, Experiment, Microsoft Excel, Python Programming

      4.1

      (21 reviews)

      Intermediate · Course · 1-4 Weeks

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      Johns Hopkins University

      Advanced Statistics for Data Science

      Skills you'll gain: Probability & Statistics, General Statistics, Mathematics, Probability Distribution, Regression, Linear Algebra, Bayesian Statistics, Experiment, Econometrics, Machine Learning, Basic Descriptive Statistics, Biostatistics, Calculus, Statistical Tests, Algebra, Artificial Neural Networks, Dimensionality Reduction, Machine Learning Algorithms, Statistical Machine Learning, Communication, Correlation And Dependence, Data Analysis, Estimation, Exploratory Data Analysis, Statistical Analysis

      4.4

      (688 reviews)

      Advanced · Specialization · 3-6 Months

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      University of Pennsylvania

      Entrepreneurship 1: Developing the Opportunity

      Skills you'll gain: Entrepreneurship, Innovation, Decision Making, Research and Design, Business Analysis, Business Research, Communication, Customer Analysis, Market Research, Planning, Survey Creation, Visual Design, Design and Product, Leadership and Management, Marketing, Product Development, Sales, Strategy, Strategy and Operations, Supply Chain and Logistics

      4.8

      (4k reviews)

      Mixed · Course · 1-3 Months

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      IBM Skills Network

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Data Analysis, Machine Learning, Business Analysis, Exploratory Data Analysis, Feature Engineering, Bayesian Statistics, NoSQL, Probability Distribution, Basic Descriptive Statistics, Computer Programming, Correlation And Dependence, Data Visualization, Deep Learning, Estimation, Python Programming, Regression, SQL, Statistical Programming, Statistical Tests

      4.6

      (1.1k reviews)

      Intermediate · Course · 1-3 Months

    Searches related to hypothesis testing

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    hypothesis testing in r
    statistical inference and hypothesis testing in data science applications
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    1234…11

    In summary, here are 10 of our most popular hypothesis testing courses

    • Hypothesis Testing in Public Health: Johns Hopkins University
    • Statistical Inference and Hypothesis Testing in Data Science Applications: University of Colorado Boulder
    • Introduction to Statistical Analysis: Hypothesis Testing: SAS
    • Business Applications of Hypothesis Testing and Confidence Interval Estimation: Rice University
    • RStudio for Six Sigma - Hypothesis Testing: Coursera Project Network
    • Hypothesis Testing in R: Coursera Project Network
    • Hypotheses Testing in Econometrics: Queen Mary University of London
    • AI Workflow: Data Analysis and Hypothesis Testing: IBM
    • Hypothesis Testing with Python and Excel: Tufts University
    • Advanced Statistics for Data Science: Johns Hopkins University

    Frequently Asked Questions about Hypothesis Testing

    • While hypothesis might make you think of science, hypothesis testing is a mathematical process that involves testing data using statistics to see if there is enough evidence to support a hypothesis. A hypothesis is a belief or a proposed explanation for something that has not yet been backed up by evidence. Hypothesis testing takes the data gathered in an experiment, survey, or other collection of information and interprets it. The five steps of hypothesis testing are specifying the null hypothesis (the statement of no relationship between the factors involved), specifying the alternative hypothesis (the statement that there is a relationship between the factors involved), setting the significance level (the percentage of chance the alternative hypothesis will be accepted), calculating the test statistic and corresponding P-value (probability of obtaining the sample statistic), and drawing a conclusion.‎

    • Learning hypothesis testing is important because it's what allows you to decide if something is true based on real data. If you're in marketing, for example, you can use hypothesis testing in consumer research to see how well your product is accepted by customers. If you're in the medical field, you can use it to see if a treatment has positive effects. An educational institution may be interested in determining if getting eight hours of sleep correlates with higher grades for its students. Hypothesis testing helps remove the likelihood of chance affecting a conclusion and instead backs it up with statistically significant data.‎

    • Online courses on Coursera can help you learn how hypothesis testing applies to a variety of fields, including health care, business, artificial intelligence, psychology, social sciences, and machine learning. You can learn how to use specific statistical tools to conduct hypothesis testing, too, such as R, RStudio for Six Sigma, and Python. With online courses on Coursera, you also have the opportunity to learn the essential building blocks of hypothesis testing, which include choosing the right hypothesis testing tool and performing hypothesis tests using chi-square tests, correlation, t-tests, simple regression, logistic regression, and analysis of variance (ANOVA).‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
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