T-test - What is a t-test?
t-tests are used to determine whether two samples are different. For example, two fifth grade classes (random samples) took the same reading pre and post-tests. The T-Test will help us analyze whether the two means are different. This means we are comparing the mean of fifth-grade class #1 to fifth grade class #2 to see how they vary. This will help to figure out if students are increasing performance overall or not. Also, if there is significant difference, the t-test will help us figure out if we need to investigate further to see why there is significant differences in performance (intervention, supplemental materials, delivery method of instruction, etc).
contributed by Tania Nicole Sutherland
== A t-test is an inferential test that is used to test the difference in the mean scores of two groups. It assists teachers in determining whether an instructional plan, intervention, or policy change has quantifiable outcomes. Otherwise put, it separates the differences that occurred by chance and the differences that may have occurred due to actual treatment effects. In educational research, two types of t-tests exist. Independent Samples t-test - applied in situations when two different groups of people (e.g., students in two classrooms) are compared. Paired Samples t-test - used when the researcher wants to compare the same group of scores before an intervention and after (an example is pre-test vs. post-test). The test produces a t-value and a p-value. When p is below 05, the researchers will make a conclusion that the difference between the group means is statistically significant, which means that it is likely to be a real effect. An illustration of this is that the difference in the score of a digital-learning group versus a textbook group ( t (48) = 2.62, p =.012) would not have been due to chance. In SPSS, perform this test using Analyze - Compare Means - Independent-Samples t-test or Paired-Samples t-test. Check the Levene Test to assume that variances are equal and normality holds. Also, it is best practice to report the effect size (Cohen's d) to describe the magnitude of the difference, and not the statistical significance. T-tests provide an easy but efficient method of evaluating the teaching strategies, the use of technology, or the outcomes of the program as a teacher. They endorse an evidence-based reflection culture, which allows teachers to promote evidence-based change in instruction.
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contributed by Casimir007
==Identifying the independent and dependent variables within an experimental design.
Independent variable- A factor that is controlled or changes. There can be several levels to the independent variable.
The dependent variable is the variable that changes in response to the independent variable.==
contributed by howarth006
Assumptions of the t-test
A t-test is based on several assumptions. The data should be approximately normally distributed, and the observations should be independent. For independent samples, the two groups should also have similar variances.
If these assumptions are not met, the results of the t-test may be misleading, and another statistical method may be more appropriate.
contribution by Celino Grigorio
