Statistical Methods in Sports Engineering

What is the null hypothesis (H₀) for the running time improvements paired t-test analysis?

• There is no significant difference in running times before and after training.

• There is a significant difference in running times after training.

• The training program has no effect on running times.

• Running times will improve regardless of training.

What is the alternative hypothesis (H₁) for the running time improvements paired t-test analysis?

• There is no significant difference in running times before and after training.

• There is a significant difference in running times after training.

• The training program has no effect on running times.

• Running times will improve regardless of training.

What does the p-value indicate in the context of the running time improvements paired t-test analysis?

• The p-value is extremely small, indicating a significant improvement.

• The p-value is greater than 0.05, indicating no significant difference.

• The p-value is exactly 0.05, indicating borderline significance.

• The p-value is irrelevant to the analysis.

What are the key assumptions of the paired T-Test?

• Normality of differences and dependence between paired observations.

• Independence of observations and equal variances among groups.

• Normality of distribution and independence of observations.

• All observations are independent and normally distributed.

What is the definition of One-Way ANOVA?

• One-way ANOVA evaluates means from three or more groups.

• One-way ANOVA compares two groups only.

• One-way ANOVA is used for categorical data only.

• One-way ANOVA is a type of T-Test.

What are the key assumptions of One-Way ANOVA?

• Independence of observations, normality of distribution, and equal variances.

• Normality of differences and dependence between observations.

• All observations must be normally distributed.

• Observations can be dependent.

What is the main difference between T-Test and ANOVA?

• T-Test compares two groups, while ANOVA accommodates three or more.

• T-Test is used for categorical data, while ANOVA is for continuous data.

• T-Test is more complex than ANOVA.

• ANOVA is only for paired samples.