1 / 4

Chapter 19 - Two Sample t Procedures

Chapter 19 - Two Sample t Procedures. Used when comparing two populations or treatments aka: ‘ two sample ’ problems… Samples can be of different sizes. Samples are independent (Matching violates independence). Both populations are normal.

mamaral
Télécharger la présentation

Chapter 19 - Two Sample t Procedures

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Chapter 19 - Two Sample t Procedures • Used when comparing two populations or treatments • aka: ‘two sample’ problems… • Samples can be of different sizes. • Samples are independent (Matching violates independence). • Both populations are normal. ex: Calcium intake vs. blood pressure change.

  2. Diff between means = Not Significant. Example 6.9 - Chapin Social Insight Test Diff between means = Not Significant.

  3. 2 Sample Confidence Intervals Example 6.9 - Chapin Social Insight Test 0 included in interval We cannot reject Ho at the  = .05 level…

  4. (Robustness)2 • For: • equal sample sizes • similar shaped distributions • probabilities from the t table are accurate when the sample sizes are as small as (n1 & n2) = 5. • When the two distributions have different shapes, larger samples are needed. • Rule of thumb: pg 452 guidelines, replace “sample size” with “sum of sample sizes n1+n2” • Results in conservative guidelines: Option1 (software) vs. Option 2 (no software) for degrees of freedom… • Option 2 DF = (n1 - 1) OR (n2 - 1) whichever is smaller…

More Related