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Independent Samples T Test Assumptions. To conduct a valid test. Whether males and females differ significantly in terms of their self-esteem levels. Assumptions that should be satisfied 1. The observations within each sample must be independent 2.
In the case of the independent t-test it is often assumed that this test is robust against violation of the normality assumption at least when the sample. Another of the first steps in using the independent-samples t test is to test the assumption of normality where the Null Hypothesis is that there is no significant departure from normality as such. CHAPTER 104 Assumptions Underlying the Independent-Measures t Formula 39. This often holds if each case in SPSS represents a. The two populations from which the samples are selected must be normal Or you must have large samples 3. No significant outliers in the two groups.
CHAPTER 104 Assumptions Underlying the Independent-Measures t Formula 39.
The dependent variable should be normally distributed in both groups The variance of the dependent variable should be the same in both groups. Conclusions from an independent samples t-test can be trusted if the following assumptions are met. Assumptions mean that your data must satisfy certain properties in order for statistical method results to be accurate. The common assumptions made when doing a t-test include those regarding the scale of measurement random sampling normality of data distribution adequacy of sample. Similar Spread Between Groups. Assumptions for an Independent Samples T-Test.