1 / 16

Lab # 1

The Completely Randomized Design (CRD). Lab # 1. Definition. Achieved when the samples of experimental units for each treatment are random and independent of each other Design is used to compare the treatment means:. The hypotheses are tested by comparing the differences

dex
Download Presentation

Lab # 1

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. The Completely Randomized Design (CRD) Lab # 1

  2. Definition • Achieved when the samples of experimental units for each treatment are random and independent of each other • Design is used to compare the treatment means:

  3. The hypotheses are tested by comparing the differences between the treatment means. • Test statistic is calculated using measures of variability within treatment groups and measures of variability between treatment groups

  4. Steps for Conducting an Analysis of Variance (ANOVA) for a Completely Randomized Design: • 1- Assure randomness of design, and independence, randomness of samples • 2- Check normality, equal variance assumptions • 3- Create ANOVA summary table • 4- Conduct multiple comparisons for pairs of means as necessary/desired

  5. assumptions 1- Normality: You can check on normality using 1- plot 2- Kolmogorve test 2- Constant variance: You can check on homogeneity of variances using 1- Plot 2- leven’s test.

  6. ONE WAY ANOVA

  7. multiple comparisons of means • A significant F-test in an ANOVA tells you that the treatment means as a group are statistically different. • Does not tell you which pairs of means differ statistically from each other • With k treatment means, there are c different pairs of means that can be compared, with c calculated as

  8. multiple comparisons of means

  9. Example 1 • A manufacturer of television sets is interested in the effect on tube conductivity of four different types of coating for color picture tubes. The • following conductivity data are obtained.

  10. Solution • Enter data in spss as follows:

  11. Analysis

  12. One way Anova

  13. Thanks for all

More Related