Cola Weights Data Set 37 “Cola Weights and Volumes” in Appendix B lists the weights (lb) of the contents of cans of cola from four different samples: (1) regular Coke, (2) Diet Coke, (3) regular Pepsi, and (4) Diet Pepsi. The results from analysis of variance are shown in the Minitab display below. What is the null hypothesis for this analysis of variance test? Based on the displayed results, what should you conclude about H_knot. What do you conclude about equality of the mean weights from the four samples?
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 56m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 8m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - Excel42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - Excel27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 37m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- Two Variances and F Distribution29m
- Two Variances - Graphing Calculator16m
- 11. Correlation1h 24m
- 12. Regression3h 33m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - Excel8m
- Finding Residuals and Creating Residual Plots - Excel11m
- Inferences for Slope31m
- Enabling Data Analysis Toolpak1m
- Regression Readout of the Data Analysis Toolpak - Excel21m
- Prediction Intervals13m
- Prediction Intervals - Excel19m
- Multiple Regression - Excel29m
- Quadratic Regression15m
- Quadratic Regression - Excel10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA2h 28m
14. ANOVA
Introduction to ANOVA
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Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
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 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.

A
: All means are the same
: At least one mean is different, at least one method has a different average test score.
B
: All students perform equally well on the final exam, regardless of the instructional method.
: At least one group of students performs differently than the others.
C
: The three instructional methods lead to different mean exam scores.
: All three instructional methods lead to the same mean exam scores.
D
: There is a significant difference among the teaching methods.
: There is no significant difference among the teaching methods.
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Verified step by step guidance1
Step 1: Understand the problem. The school administrator wants to determine if students' academic performance differs based on the type of instructional method using a one-way ANOVA test. The data provided includes test scores for three instructional methods: Traditional, Flipped, and Online.
Step 2: Define the null and alternative hypotheses for the one-way ANOVA test. The null hypothesis (H₀) states that all group means are equal, meaning the instructional method does not affect academic performance. The alternative hypothesis (H₁) states that at least one group mean is different, indicating that the instructional method affects academic performance.
Step 3: Organize the data. The test scores for each instructional method are provided in the table. Calculate the mean and variance for each group (Traditional, Flipped, Online) to prepare for the ANOVA test.
Step 4: Perform the one-way ANOVA test. Compute the between-group variance (how much the group means differ from the overall mean) and the within-group variance (how much individual scores differ within each group). Use these variances to calculate the F-statistic.
Step 5: Compare the F-statistic to the critical value from the F-distribution table at the chosen significance level (e.g., α = 0.05). If the F-statistic exceeds the critical value, reject the null hypothesis (H₀) and conclude that at least one instructional method leads to different academic performance.
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