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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123 results for "hypothesis testing"

Johns Hopkins University
Advanced Statistics for Data Science
Skills you'll gain: Probability & Statistics, General Statistics, Mathematics, Probability Distribution, Regression, Linear Algebra, Experiment, Bayesian Statistics, Statistical Tests, Econometrics, Machine Learning, Basic Descriptive Statistics, Biostatistics, Calculus, 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
(695 reviews)
Advanced · Specialization · 3-6 Months
Imperial College London
Introduction to Statistics & Data Analysis in Public Health
Skills you'll gain: General Statistics, Probability & Statistics, Data Analysis, Probability Distribution, Statistical Analysis, Business Analysis, Statistical Tests, Basic Descriptive Statistics, Exploratory Data Analysis, R Programming, Statistical Programming, Critical Thinking, Data Analysis Software
4.7
(1.3k reviews)
Beginner · Course · 1-4 Weeks
IBM Skills Network
Statistics for Data Science with Python
Skills you'll gain: General Statistics, Probability & Statistics, Data Analysis, Business Analysis, Statistical Analysis, Probability Distribution, Statistical Tests, Basic Descriptive Statistics, Correlation And Dependence, Data Visualization, Plot (Graphics), Regression, Statistical Visualization
4.5
(293 reviews)
Mixed · Course · 1-3 Months
University System of Georgia
Six Sigma Tools for Improve and Control
Skills you'll gain: Probability & Statistics, Strategy and Operations, Basic Descriptive Statistics, Business Analysis, Business Process Management, Data Analysis, Entrepreneurship, Operations Management, Performance Management, Statistical Analysis, Business Psychology, Correlation And Dependence, Data Visualization, Distributed Computing Architecture, Exploratory Data Analysis, Plot (Graphics), Probability Distribution, Regression, Statistical Tests, Supply Chain and Logistics, Leadership and Management, Mathematics, Organizational Development
4.7
(1k reviews)
Beginner · Course · 1-3 Months
University System of Georgia
Six Sigma Advanced Analyze Phase
Skills you'll gain: Probability & Statistics, Experiment, General Statistics, Business Analysis, Probability Distribution, Statistical Tests, Basic Descriptive Statistics, Correlation And Dependence, Data Analysis, Data Analysis Software, Econometrics, Estimation, Regression, Statistical Analysis
4.7
(855 reviews)
Intermediate · Course · 1-4 Weeks
Free
IBM Skills Network
Data Science with R - Capstone Project
Skills you'll gain: R Programming, Data Analysis, Data Mining, Plot (Graphics), Basic Descriptive Statistics, Data Visualization, General Statistics, Interactive Data Visualization, Regression, Statistical Visualization, Data Visualization Software, Estimation, Exploratory Data Analysis, Geovisualization, Linear Algebra, Machine Learning, Probability & Statistics, SAS (Software), SQL, Spatial Data Analysis, Statistical Analysis, Statistical Tests, Business Analysis, Data Management, Data Science, Extract, Transform, Load, Statistical Programming
4.4
(26 reviews)
Intermediate · Course · 1-3 Months

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

Advanced Statistics for Data Science: Johns Hopkins University
Introduction to Statistics & Data Analysis in Public Health: Imperial College London
Statistics for Data Science with Python: IBM Skills Network
Six Sigma Tools for Improve and Control: University System of Georgia
Six Sigma Advanced Analyze Phase: University System of Georgia
Population Health: Responsible Data Analysis: Universiteit Leiden
Data Science with R - Capstone Project: IBM Skills Network
Stability and Capability in Quality Improvement: University of Colorado Boulder
Topics in Applied Econometrics: Queen Mary University of London
Logistic Regression in R for Public Health: Imperial College London

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.

Filter by

123 results for "hypothesis testing"

Advanced Statistics for Data Science

Introduction to Statistics & Data Analysis in Public Health

Statistics for Data Science with Python

Six Sigma Tools for Improve and Control

Six Sigma Advanced Analyze Phase

Population Health: Responsible Data Analysis

Data Science with R - Capstone Project

Stability and Capability in Quality Improvement

Topics in Applied Econometrics

Logistic Regression in R for Public Health

Performing Confirmatory Data Analysis in R

Using probability distributions for real world problems in R

Searches related to hypothesis testing

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

Frequently Asked Questions about Hypothesis Testing

What is hypothesis testing?‎

Why is hypothesis testing important to learn?‎

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

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123 results for "hypothesis testing"

Searches related to hypothesis testing

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

Frequently Asked Questions about Hypothesis Testing

What is hypothesis testing?‎

Why is hypothesis testing important to learn?‎

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

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Learn Something New

Popular Data Science Topics

Popular Computer Science & IT Topics

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