Learn moreLearn moreApplied Statistics Handbook

Table of Contents


Steps to Hypothesis Testing 

Hypothesis testing is used to establish whether the differences exhibited by random samples can be inferred to the populations from which the samples originated.

General Assumptions

      Population is normally distributed

      Random sampling

      Mutually exclusive comparison samples

      Data characteristics match statistical technique

For interval / ratio data use

t-tests, Pearson correlation, ANOVA, OLS regression

For nominal / ordinal data use

Difference of proportions, chi square and related measures of association, logistic regression

State the Hypothesis

Null Hypothesis (Ho): There is no difference between ___ and ___.

Alternative Hypothesis (Ha): There is a difference between __ and __.

Note: The alternative hypothesis will indicate whether a 1-tailed or a 2-tailed test is utilized to reject the null hypothesis.

Ha for 1-tail tested:  The __ of __ is greater (or less) than the __ of __.

Set the Rejection Criteria

This determines how different the parameters and/or statistics must be before the null hypothesis can be rejected. This "region of rejection" is based on alpha () -- the error associated with the confidence level. The point of rejection is known as the critical value.

Compute the Test Statistic

The collected data are converted into standardized scores for comparison with the critical value.

Decide Results of Null Hypothesis

If the test statistic equals or exceeds the region of rejection bracketed by the critical value(s), the null hypothesis is rejected. In other words, the chance that the difference exhibited between the sample statistics is due to sampling error is remote--there is an actual difference in the population.



Copyright 2015, AcaStat Software. All Rights Reserved.