What is 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.

Why is hypothesis testing important to learn?

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.

How can taking online courses on Coursera help me learn hypothesis testing?

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).

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Hypothesis Testing

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''hypothesis testing'的 52 个结果

SAS
Introduction to Statistical Analysis: Hypothesis Testing
您将获得的技能： SAS (Software), Regression, Statistical Tests, Communication, Probability & Statistics, Marketing, Business Analysis, Algebra, Analysis, Data Analysis, Modeling, Journalism, General Statistics, Correlation And Dependence, Statistical Programming, Advertising, Statistical Analysis
4.6
（72 条评论）
Intermediate · Course · 1-4 Weeks
Johns Hopkins University
Hypothesis Testing in Public Health
您将获得的技能： Interpretation, Hypothesis, Statistical Tests, Biostatistics, Business Analysis, Hypothesis Testing, iOS Development, Statistical Hypothesis Testing, Mobile Development, Data Analysis, Chi-Squared Distribution, Probability & Statistics, General Statistics, Statistical Analysis, Confidence
4.8
（538 条评论）
Beginner · Course · 1-3 Months
Rice University
Business Applications of Hypothesis Testing and Confidence Interval Estimation
您将获得的技能： Analysis, Statistical Tests, Spreadsheet Software, Probability & Statistics, Business Analysis, Data Analysis, Hypothesis, Experiment, Probability Distribution, Relative Change And Difference, Hypothesis Testing, Confidence, General Statistics, Statistical Hypothesis Testing, Statistical Analysis, Microsoft Excel
4.8
（1.2k 条评论）
Mixed · Course · 1-4 Weeks
免费
Stanford University
Introduction to Statistics
您将获得的技能： Econometrics, Basic Descriptive Statistics, Statistical Tests, Experiment, Bayesian Statistics, Probability Distribution, Plot (Graphics), Regression, Probability & Statistics, Data Analysis, Probability, Machine Learning, Data Visualization, Statistical Analysis, General Statistics, Correlation And Dependence, Statistical Hypothesis Testing, Statistical Inference, Markov Model, Inference, Hypothesis Testing
4.5
（1.3k 条评论）
Beginner · Course · 1-3 Months
免费
University of Cape Town
Understanding Clinical Research: Behind the Statistics
您将获得的技能： Analysis, Probability & Statistics, Data Analysis, Experiment, Business Analysis, Basic Descriptive Statistics, Probability Distribution, Research and Design, General Statistics, Statistical Analysis, Statistical Tests, Statistical Hypothesis Testing
4.8
（2.9k 条评论）
Mixed · Course · 1-3 Months
IBM Skills Network
Exploratory Data Analysis for Machine Learning
您将获得的技能： Analysis, Business Analysis, Hypothesis, Feature Engineering, Probability & Statistics, Bayesian Statistics, Experiment, Python Programming, Machine Learning, NoSQL, Data Analysis, Computer Programming, Exploratory Data Analysis, Deep Learning, Databases, General Statistics, Statistical Hypothesis Testing, Hypothesis Testing, Statistical Programming, Data Visualization
4.6
（813 条评论）
Intermediate · Course · 1-3 Months

与 hypothesis testing 相关的搜索

hypothesis testing in public health

hypothesis testing with python and excel

hypothesis testing in r

business applications of hypothesis testing and confidence interval estimation

statistical inference and hypothesis testing in data science applications

introduction to statistical analysis: hypothesis testing

rstudio for six sigma - hypothesis testing

ai workflow: data analysis and hypothesis testing

总之，这是我们最受欢迎的 hypothesis testing 门课程中的 10 门

Introduction to Statistical Analysis: Hypothesis Testing: SAS
Statistical Inference and Hypothesis Testing in Data Science Applications: University of Colorado Boulder
Hypothesis Testing in Public Health: Johns Hopkins University
Hypothesis Testing in R: Coursera Project Network
Business Applications of Hypothesis Testing and Confidence Interval Estimation: Rice University
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
RStudio for Six Sigma - Hypothesis Testing: Coursera Project Network
Introduction to Statistics: Stanford University

关于 Hypothesis Testing 的常见问题

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).‎