Overview of ED506 Statistical Tests
T-tests
You will have two groups that you are comparing and looking for a difference in the means of
the data collected for the two groups.
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Independent Sample T-tests – the two groups being compared are not related. For
example, one group received one type of treatment, and the second group received a
second type of treatment (or possibly no treatment), and then you compare their scores
on some assessment.
Dependent Samples T-tests - the two groups being compared are related. For example,
a group of students takes a pretest before instruction and then a posttest after
instruction, and the scores are compared. The two sets of test scores are from the same
group of students, and thus, the “groups” being compared are related because they are
the same students.
One-Way ANOVA
You will have more than two groups and you are comparing and looking for a difference in the
means of the data collected for each of the groups. You might have three or 100 groups, but if
you have more than two groups, you cannot use a t-test. You must use a one-way ANOVA.
Correlations
You will be looking for a relationship between groups or sets of data. For example, test scores
are compared to study time to determine if there is a relationship between the two. Does
studying more translate to higher test scores?
Chi-Square Tests
You will have categorical data such as male/female, proficient/not proficient, or yes/no. There
will be no hard and fast numbers such as test scores.
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Chi-Square Test of Independence – you are looking to see if membership in one
category is related to membership in another category. For example, is a person’s
gender (membership in the “girl” or “boy” club) related to their annual income
(membership in the “under 50K” or “over 50K” club)?
One Sample Chi-Square – you are looking to see if there is a difference in the groups
being compared. For example, is the distribution of ethnic groups in a particular school
different from the distribution of ethnic groups in the entire school district?
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