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The process of hypothesis testing on means, which is a statistical method used to compare the means of two or more populations. The null and alternative hypotheses, determining x, s, and n, calculating the z-score, finding the associated percentile and p-value, and drawing a conclusion. This guide is essential for students and researchers in various fields, including statistics, psychology, and engineering.
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Hypothesis testing on means
Step 1. Write the null and alternative hypotheses
Null: Always contains an = sign and CONTAINS THE VALUE FOR “ μ ” The null states what is currently going on in the population. Alternative: Always contains an <,>, or ≠ The alternative states what the researcher believes is true.
Step 2. Determine X , s and n BASED ON THE STUDY
Step 3. Plug X , μ , s and n into the formula:
s n
Step 4. Look up the Z-score on the chart to find the associated percentile (remember this is already a percent…do not slide the decimal point!!!!!!)
Step 5. Find the P-value
If the alternative hypothesis in step 1 is a “less than” statement, the percentile is the p- value.
If the alternative hypothesis in step 1 is a “greater than” statement, you must subtract the percentile from 100 to get the p-value
Step 6. Draw the conclusion
If the p-value is less than 5% (or .05), then reject the null in favor of the alternative. Acknowledge you may have made a type I error.
If the p-value is greater than 5% (or .05), then fail to reject the null. Acknowledge you may have made a type II error.