10_t_Test_Independent

10_t_Test_Independent - t Test for Two Independent Samples...

This preview shows pages 1–6. Sign up to view the full content.

1 t Test for Two Independent Samples t Test for Two Independent Samples • Null and Alternative Hypotheses t ratio – Pooled variance – Estimated standard error – Degrees of freedom • Assumptions • Cohen’s d • Proportion of Variance Accounted for t Test for Two Independent Samples • Previous t test for one sample compared a single sample mean to a hypothesized population mean • What if we want to compare the means of two samples to determine if the samples are significantly different (not different just by chance)? Comparing Samples Independent-measures design: • Common research design

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2 Comparing Samples Independent-measures design: • Common research design • Different randomly-selected samples experience different versions of a treatment or manipulation – e.g., one group receives Treatment A, the other B General Population Before Treatment General Population Random Sample Before Treatment General Population Random Sample Random Sample Before Treatment
3 General Population Get Treatment A Get Treatment B Before Treatment Comparing Samples Independent-measures design: • Common research design • Different randomly-selected samples experience different versions of a treatment or manipulation – e.g., one group receives Treatment A, the other B Comparing Samples Independent-measures design: • Common research design • Different randomly-selected samples experience different versions of a treatment or manipulation – e.g., one group receives Treatment A, the other B • A dependent variable that is relevant to the manipulation is then measured Comparing Samples Independent-measures design: • Common research design • Different randomly-selected samples experience different versions of a treatment or manipulation – e.g., one group receives Treatment A, the other B • A dependent variable that is relevant to the manipulation is then measured • The scores are then compared

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
4 Comparing Samples Independent-measures design: • Common research design • Different randomly-selected samples experience different versions of a treatment or manipulation – e.g., one group receives Treatment A, the other B • A dependent variable that is relevant to the manipulation is then measured • The scores are then compared • Also called a between-subjects design Comparing Samples Independent-measures design: • because the samples consist of different people, they are considered to be independent of one another • likewise, the groups of scores obtained from the samples are considered independent of one another Comparing Samples Independent-measures design: • The groups are considered samples that represent populations • Through the samples, the populations are compared after treatment Comparing Samples H 1 ( ) claims that the populations are different – i.e., the treatments have different effects on scores
5 Comparing Samples H 1 ( ) claims that the populations are different – i.e., the treatments have different effects on scores

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 08/22/2011 for the course PSY 207 taught by Professor Pfordesher during the Fall '07 term at SUNY Buffalo.

Page1 / 28

10_t_Test_Independent - t Test for Two Independent Samples...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online