Four different high schools in local towns took random samples of 100 students in three grades, 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 , , , and . Which F-Statistic is most likely to indicate the average study times across grades are not all the same?
Table of contents
- 1. Introduction to Statistics53m
- 2. Describing Data with Tables and Graphs2h 2m
- 3. Describing Data Numerically2h 8m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables3h 28m
- 6. Normal Distribution & Continuous Random Variables2h 21m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 37m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - ExcelBonus23m
- Introduction to Confidence Intervals22m
- Confidence Intervals for Population Mean1h 26m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - ExcelBonus28m
- Confidence Intervals for Population Means - ExcelBonus25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 20m
- 9. Hypothesis Testing for One Sample5h 15m
- Steps in Hypothesis Testing1h 13m
- Performing Hypothesis Tests: Means1h 1m
- Hypothesis Testing: Means - ExcelBonus42m
- Performing Hypothesis Tests: Proportions39m
- Hypothesis Testing: Proportions - ExcelBonus27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions29m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 35m
- Two Proportions1h 12m
- Two Proportions Hypothesis Test - ExcelBonus28m
- Two Means - Unknown, Unequal Variance1h 2m
- Two Means - Unknown Variances Hypothesis Test - ExcelBonus12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - ExcelBonus9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - ExcelBonus21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - ExcelBonus12m
- Two Variances and F Distribution29m
- Two Variances - Graphing CalculatorBonus15m
- 11. Correlation1h 24m
- 12. Regression3h 42m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - ExcelBonus8m
- Finding Residuals and Creating Residual Plots - ExcelBonus11m
- Inferences for Slope32m
- Enabling Data Analysis ToolpakBonus1m
- Regression Readout of the Data Analysis Toolpak - ExcelBonus21m
- Prediction Intervals13m
- Prediction Intervals - ExcelBonus19m
- Multiple Regression - ExcelBonus29m
- Quadratic Regression23m
- Quadratic Regression - ExcelBonus10m
- 13. Chi-Square Tests & Goodness of Fit2h 31m
- 14. ANOVA2h 32m
14. ANOVA
Introduction to ANOVA
Multiple Choice
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?

A
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.
B
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.
C
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.
D
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.
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Verified step by step guidance1
Step 1: Understand the problem. The marketing manager wants to determine if there is a statistically significant difference in mean weekly sales among three advertising platforms (TV, Social Media, and Print Media). An ANOVA test is used to compare the means of more than two groups.
Step 2: Review the data provided. The table shows weekly sales (in \$1,000s) for 5 stores assigned to each platform during the campaign period. For TV: {22, 25, 27, 24, 26}, Social Media: {28, 30, 27, 29, 31}, and Print Media: {20, 21, 19, 23, 22}.
Step 3: Recall the null hypothesis (H₀) and alternative hypothesis (H₁) for ANOVA. H₀: The mean weekly sales are the same across all platforms. H₁: At least one platform has a different mean weekly sales.
Step 4: Interpret the P-value (0.03) obtained from the ANOVA test. If the P-value is less than the significance level (typically 0.05), we reject the null hypothesis. This indicates that at least one advertising platform leads to a significant difference in average sales.
Step 5: Conclude based on the P-value. Since the P-value (0.03) is less than 0.05, the null hypothesis is rejected. This means there is evidence to suggest that at least one advertising platform leads to a significant difference in mean weekly sales.
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