Weather-Related Deaths For the most recent year as of this writing, the numbers of weather-related U.S. deaths for each month were 61, 14, 22, 26, 29, 42, 93, 49, 47, 35, 96, 16, listed in order beginning with January (based on data from the National Weather Service). Use a 0.01 significance level to test the claim that weather-related deaths occur in the different months with the same frequency. Provide an explanation for the result.
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 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: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 29m
- 10. Hypothesis Testing for Two Samples4h 50m
- 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
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
13. Chi-Square Tests & Goodness of Fit
Goodness of Fit Test
Struggling with Statistics?
Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
A gym owner wants to know if the gym has similar numbers of members across different age groups. The table shows the distribution of ages for members from a random survey. Does this data set fit the criteria for a G.O.F. test?

A
Yes
B
No
C
More information is required.
Verified step by step guidance1
Step 1: Understand the problem. The gym owner wants to determine if the distribution of members across different age groups is similar. This requires a statistical test to compare observed frequencies (from the table) to expected frequencies.
Step 2: Recognize the type of test needed. A Goodness-of-Fit (G.O.F.) test is appropriate when you want to compare observed data to a theoretical distribution or expected frequencies. To decide if the data fits the criteria for a G.O.F. test, you need to check if expected frequencies are provided or can be calculated.
Step 3: Analyze the table. The table provides observed frequencies for five age groups: 18–25 (54 members), 26–35 (46 members), 36–45 (53 members), 46–55 (49 members), and 56+ (48 members). However, the table does not provide expected frequencies or a theoretical distribution to compare against.
Step 4: Determine if more information is required. To perform a G.O.F. test, you need expected frequencies or a theoretical distribution (e.g., uniform distribution, proportional distribution based on population demographics). Without this information, you cannot proceed with the test.
Step 5: Conclude. Based on the given data, the criteria for a G.O.F. test are not fully met because expected frequencies or a theoretical distribution are not provided. Therefore, the correct answer is 'More information is required.'
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