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.
Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 53m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample2h 19m
- 10. Hypothesis Testing for Two Samples3h 22m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
14. ANOVA
Introduction to ANOVA
Problem 10.RE.15
Textbook Question
In Exercises 13–16, find the critical F-value for a two-tailed test using the level of significance α and degrees of freedom d.f.N and d.f.D.
α=0.01,d.f.N=40,d.f.D=60

1
Step 1: Understand the problem. You are tasked with finding the critical F-value for a two-tailed test using the given level of significance (α = 0.01) and degrees of freedom for the numerator (d.f.N = 40) and denominator (d.f.D = 60). The critical F-value is used in hypothesis testing to determine the rejection region for the null hypothesis.
Step 2: Recognize that the F-distribution is not symmetric, and the critical values depend on the degrees of freedom for the numerator and denominator. For a two-tailed test, you will need to find the critical F-value for both tails (upper and lower).
Step 3: Use an F-distribution table or statistical software to locate the critical F-value. In the table, find the row corresponding to d.f.N = 40 and the column corresponding to d.f.D = 60. Since α = 0.01 for a two-tailed test, divide α by 2 to allocate 0.005 to each tail.
Step 4: For the upper tail, locate the critical F-value corresponding to α = 0.005, d.f.N = 40, and d.f.D = 60. For the lower tail, calculate the reciprocal of the upper tail critical F-value because the F-distribution is asymmetric.
Step 5: Summarize the results. The critical F-values for the two-tailed test are the values found in Step 4 for the upper and lower tails. These values define the rejection region for the null hypothesis in the F-test.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Critical F-value
The critical F-value is a threshold used in hypothesis testing to determine whether to reject the null hypothesis. It is derived from the F-distribution, which is used when comparing variances between two groups. The critical value is based on the chosen significance level (α) and the degrees of freedom for the numerator (d.f.N) and denominator (d.f.D). If the calculated F-statistic exceeds this critical value, the null hypothesis is rejected.
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Degrees of Freedom
Degrees of freedom (d.f.) refer to the number of independent values or quantities that can vary in an analysis without violating any constraints. In the context of an F-test, d.f.N represents the degrees of freedom associated with the numerator (the group with more variability), while d.f.D represents the degrees of freedom for the denominator (the group with less variability). These values are crucial for determining the shape of the F-distribution and finding the critical F-value.
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Level of Significance (α)
The level of significance (α) is the probability of rejecting the null hypothesis when it is actually true, also known as a Type I error. It is a threshold set by the researcher, commonly at 0.05 or 0.01, which indicates the risk level they are willing to accept for making a false positive conclusion. In this question, α is set at 0.01, meaning there is a 1% risk of incorrectly rejecting the null hypothesis.
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