15- **Understanding the Standard Error in Independent-Measures t Statistics**In the context of an independent-measures t statistic, the standard error (SE) provides important information regarding the comparison of two sample means. Specifically, the SE indicates the average discrepancy between two population means as predicted under the null hypothesis.Here are the options to understand better what the SE indicates:- **Option 1**: The SE tells you the average discrepancy between two observed sample means that would be expected to occur under the null hypothesis, only if the population means are different.- **Option 2**: The SE tells you the average discrepancy between two population means that would be expected to occur under the null hypothesis, only if these means are different.- **Option 3 (Correct)**: The SE tells you the average discrepancy between two population means that would be expected to occur under the null hypothesis, even if these means are not different.- **Option 4**: The SE tells you the average discrepancy between two observed sample means that would be expected to occur under the null hypothesis, even if the two population means are not different.Understanding the correct role of the SE as described in Option 3 is crucial for interpreting results in hypothesis testing.

Name: 15- **Understanding the Standard Error in Independent-Measures t Stati
Uploaded: 2024-03-20T07:06:41.000Z
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Description: 15- **Understanding the Standard Error in Independent-Measures t Statistics**In the context of an independent-measures t statistic, the standard error (SE) provides important information regarding the comparison of two sample means. Specifically, the