- 1. Introduction to Statistics22m
- 2. Describing Data with Tables and Graphs2h 1m
- 3. Describing Data Numerically1h 48m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables1h 30m
- 6. Normal Distribution & Continuous Random Variables58m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 17m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 11m
- 9. Hypothesis Testing for One Sample1h 8m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 14. ANOVA1h 4m
Introduction to ANOVA: Videos & Practice Problems
Introduction to ANOVA
A company wants to determine whether the average monthly sales differ among three different regions: North, South, and West. The company collects monthly sales data (in thousands of dollars) from four randomly selected stores in each region over the same month. Calculate the F-statistic given the Mean Square due to Treatments: MST = 226.6 (variance between groups) and the Mean Square due to Error: MSE = 7.944 (variance within groups).
Four different high schools in local towns took random samples of 100 students in three grades, 10th−12th and collected data on the weekly time spent studying to see if students in each of these grades study on average for the same amount of time per week. The four schools ran ANOVA tests on their samples, and the F-Statistics were 2.35, 2.57, 2.81, and 3.93. Which F-Statistic is most likely to indicate the average study times across grades are not all the same?
ANOVA Test
A school administrator wants to examine whether students' academic performance differs based on the type of instructional method used in their classes. A random sample of 18 students is selected and divided evenly among the three teaching methods. After a semester, all students take the same standardized final exam. State the null and alternative hypotheses for a one-way ANOVA test.

H0: All means are the same
HA: At least one mean is different, at least one method has a different average test score.
H0: All students perform equally well on the final exam, regardless of the instructional method.
H1: At least one group of students performs differently than the others.
H0: The three instructional methods lead to different mean exam scores.
H1: All three instructional methods lead to the same mean exam scores.
H0: There is a significant difference among the teaching methods.
H1: There is no significant difference among the teaching methods.
A school administrator wants to examine whether students' academic performance differs based on the type of instructional method used in their classes. A random sample of 18 students is selected and divided evenly among the three teaching methods. After a semester, all students take the same standardized final exam. An ANOVA test is performed and results in a P-value of 1.403∙10−7. Interpret these results.

The P-value is very high, so there is insufficient evidence to suggest that the type of instructional method has an effect on academic performance.
At least one method has a different average test score. Reject the null hypothesis.
There is no difference in academic performance, but further testing is required to make a definitive conclusion.
The P-value is close to 1, suggesting that the type of instructional method has no impact on students' academic performance.
A marketing manager wants to evaluate whether three different advertising platforms-TV, social media, and print media-lead to different average sales performance across regional stores. She runs a 4-week advertising campaign, assigning one platform to a group of 5 stores each (15 stores total). After the campaign, she collects the average weekly sales (in $1,000s) for each store during the campaign period. She wants to determine whether there is a statistically significant difference in mean sales among the three advertising platforms. State the null & alternative hypotheses for a one-way ANOVA test.

: All means are the same
: At least one advertising platform leads to a significant difference in average sales.
H0: At least one advertising platform leads to a significant difference in average sales.
Ha: All means are the same.
H0: There is a significant difference in the mean sales among the three advertising platforms.
Ha: There is no significant difference in the mean sales among the three advertising platforms.
H0: The mean sales are equal for TV advertising but differ for social media and print media platforms.
Ha: The mean sales differ for all three advertising platforms.
A marketing manager wants to evaluate whether three different advertising platforms-TV, social media, and print media-lead to different average sales performance across regional stores. She runs a 4-wook advertising campaign, assigning one platform to a group of 5 stores each (15 stores total). After the campaign, she collects the weekly soles (in $1,000s) for each store during the campaign period. She wants to determine whether there is a statistically significant difference in mean sales among the three advertising platforms. In an ANOVA test a P-value of 0.03 is obtained. What can be concluded about mean weekly sales for different advertising platforms?

Since the P-value (0.03) is greater than the significance level (typically 0.05), we fail to reject the null hypothesis and conclude that there is no significant difference in mean sales among the platforms.
Since the P-value (0.03) is greater than 0.05, we reject the null hypothesis and conclude that there is a significant difference in the mean sales across the platforms.
Since the P-value (0.03) is less than 0.05, we fail to reject the null hypothesis and conclude that there is no significant difference in mean sales across the platforms.
Since the P-value (0.03) is less than the significance level (typically 0.05), at least one advertising platforms leads to a significant difference in average sales.
ANOVA Test Using TI-84
A regional sales director wants to determine whether different customer service training programs lead to different levels of employee performance across three branches. Each branch uses one of the following training programs: Program A. Program B, or Program C. After one month, the director measures the performance score (out of 100) for 5 randomly selected employees from each branch. Using α=0.05, perform a one-way ANOVA to determine whether there is a statistically significant difference in mean performance among the three training programs.

Since the performance scores for all three programs (A, B, and C) range from 76 to 85, there is no statistically significant difference between the training programs.
The P-value from the one-way ANOVA is greater than 0.05, so we fail to reject the null hypothesis and conclude that the type of training program does not affect employee performance.
The P-value from the one-way ANOVA is less than 0.05, so we reject the H0 and suggest Ha.
The one-way ANOVA is inappropriate for this study because it compares two groups only, a different statistical test should be used.