Hypothesis testing is a statistical method used to make inferences about population parameters based on sample data. It involves formulating a null hypothesis (H0) representing no effect or difference, and an alternative hypothesis (H1) indicating the presence of an effect or difference. The process includes selecting a significance level (alpha), conducting a test statistic, and comparing it to a critical value or p-value. If the test statistic falls in the rejection region or the p-value is less than alpha, the null hypothesis is rejected. This method is crucial in validating research findings and making data-driven decisions.
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Hypothesis testing is a statistical method used to make inferences about population parameters based on sample data. It involves formulating a null hypothesis (H0) representing no effect or difference, and an alternative hypothesis (H1) indicating the presence of an effect or difference. The process includes selecting a significance level (alpha), conducting a test statistic, and comparing it to a critical value or p-value. If the test statistic falls in the rejection region or the p-value is less than alpha, the null hypothesis is rejected. This method is crucial in validating research findings and making data-driven decisions.
For more information contact:

Home

& https://www.statswork.com/contact-us/
Contact our Experts:
Our Email id: info@statswork.com
Contact No: +91 8754467066