1. Statistical Inference With StatTools

2. Test for Difference Between Means means The average satisfaction of males is higher than that of females. Is this statistically significant or just a fluke? data

3. Difference Between Means Test

5. Means Test: Interpreting Results There is only a 4% chance that the population means are the same and that the difference in these two samples was a fluke occurrence. We reject the null hypothesis that the means are equal. P-value below.05 suggests variances are unequal.

6. ANOVA: 1-Way Analysis of Variance (ANOVA) simultaneously compares the mean values of three or more groups and indicates which differences are statistically significant.

7. ANOVA: 1-Way Example 5 Brands of golf balls were driven 15 times each by a machine and the distances were recorded. The brands had different average distances, but are these statistically significant? data Overall Average: 268.3

8. ANOVA: 1-Way Menu Selection

9. ANOVA: 1-Way Options

10. ANOVA: 1-Way Interpreting Results There is at least one statistically significant difference. Confidence intervals that do not include zero indicate that the difference is statistically significant. StatTools marks them in bold.

11. ANOVA: 2-Way Perhaps the temperature outside when each ball was driven also has a statistically significant effect on distance. Using 2-Way ANOVA, we can consider both factors: golf ball brand and outdoor temperature. Average distance

12. ANOVA: 2-Way Menu

13. ANOVA: 2-Way Options

14. ANOVA: 2-Way Interpreting Results Both main effects are highly statistically significant. This means that there is at least one significant difference between the brands and at least one between the temperatures. The interaction term is also significant, indicating that the combined effect of temperature and brand has an amplified effect. In other words, temperature has a larger effect on at least one of the models than the others.

15. ANOVA: 2-Way Interpreting Results Model E appears to vary most among temperatures.