1 / 17

Oneway ANOVA comparing 3 or more means

Oneway ANOVA comparing 3 or more means. Overall Purpose. A Oneway ANOVA is used to compare three or more average scores. Used when there is one IV with 3 or more levels and one DV. Sample data are used to answer a question about population means. Examples.

ilowe
Download Presentation

Oneway ANOVA comparing 3 or more means

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. Oneway ANOVA comparing 3 or more means

  2. Overall Purpose • A Oneway ANOVA is used to compare three or more average scores. • Used when there is one IV with 3 or more levels and one DV. • Sample data are used to answer a question about population means.

  3. Examples • Does a new instructional method lead to more favorable student outcomes when compared to two types of traditional instruction comparison groups?

  4. Examples • Do low-income preschool children who live in the following situations differ in school readiness? • father present in the home • see father regularly • no contact with their father

  5. The F statistic • The F statistic is a ratio. • The denominator is within group variance. •  The numerator is between group + within group variance. • t2=F for the two group case.

  6. The F statistic • If the IV has no relationship to the population means, the F statistic will equal 1. • If F=1, there is no between group variance. 

  7. The F statistic • The F statistic examines whether sample means are varying more than they would be expected to vary due to sampling error alone.

  8. Assumptions • Normality • Homogeneity of Variance • Independence of Observations • Random Sampling

  9. Statistical Significance • How do you know when there is a statistically significant difference between the average scores you are comparing?

  10. Statistical Significance • When the F statistic is greater than 1 by enough to be beyond sampling error. • We know this because the p value is less than alpha, usually set at .05.

  11. Statistical Significance • A small p value tells us that there is a low probability that the variability in the means is due to sampling error alone. • We conclude there is more variability between the group means than would be expected by sampling error alone.

  12. Hypotheses • Hypotheses for the Oneway ANOVA: Null Hypothesis: • m1 = m2 = m3 ... mk Alternative Hypothesis: • mi =/= mj for at least one pair. • At least two of the population means are different. Where: • k = the number of population means

  13. Additional Considerations • There is a unique critical F value for each degrees of freedom condition. • A statistically significant F statistic does not tell us where the difference lies. • Confidence intervals and effect sizes can be very helpful in interpreting the results.

  14. Example • Our research design:

  15. The Research Question • Are classroom structural characteristic (class size, number of ELL children, etc.) different across the three stress groups?

  16. Writing About Results • Use APA format for reporting test statistics and p values: • t(29) = 7.345, p=.005 • F(1,123) = 2.446, p = .122 • Recognize the distinction between a statistically significant finding and an important finding.

  17. Writing About Results • Remember to review the writing guidelines in the handout on the website.

More Related