Age at First Marriage A marriage counselor claims that the median age of women at the time of their first marriage is less than or equal to 27 years old. In a random sample of 65 women, 24 were less than 27 years old, 35 were more than 27 years old, and 6 were 27 years old at the time of their first marriage. At α = 0.05, can you reject the counselor’s claim? (Adapted from U.S. Census Bureau)
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
9. Hypothesis Testing for One Sample
Steps in Hypothesis Testing
Problem 11.5.13
Textbook Question
Finding Critical Values In Exercises 11–14, use the sequence and Table 12 in Appendix B to determine the number of runs that are considered too high and the number of runs that are considered too low for the data to be in random order.
N S S S N N N N N S N S N S S N N N

1
Step 1: Identify the sequence of data provided in the problem. The sequence is: N S S S N N N N N S N S N S S N N N. Here, 'N' and 'S' represent two different categories or types of data.
Step 2: Define a 'run' in the context of the problem. A run is a sequence of identical elements (e.g., consecutive 'N's or 'S's) that is followed by a different element or ends the sequence. Count the number of runs in the given sequence.
Step 3: Determine the total number of elements in each category. Count the occurrences of 'N' and 'S' in the sequence. This will help in referencing Table 12 in Appendix B.
Step 4: Use Table 12 in Appendix B to find the critical values for the number of runs. The table provides thresholds for the number of runs that are considered too high or too low for the data to be in random order, based on the counts of 'N' and 'S'.
Step 5: Compare the actual number of runs in the sequence to the critical values obtained from the table. If the number of runs is outside the range defined by the critical values, the data is not in random order. Otherwise, it is considered random.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Runs in Statistics
A 'run' in statistics refers to a sequence of consecutive identical elements in a dataset. For example, in the sequence 'N S S N', there are three runs: one run of 'N', one run of 'S S', and another run of 'N'. Analyzing runs helps assess the randomness of a dataset, as a random sequence should have a certain number of runs that can be statistically expected.
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Critical Values
Critical values are specific points in a statistical distribution that determine the threshold for making decisions about hypotheses. In the context of runs, critical values help identify whether the observed number of runs in a dataset is significantly higher or lower than what would be expected under the assumption of randomness. These values are often derived from statistical tables or calculated based on the sample size.
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Randomness Testing
Randomness testing involves statistical methods to determine if a sequence of data points is random or exhibits a pattern. This is crucial in various fields, including quality control and cryptography. In the context of the given question, testing for randomness involves comparing the number of observed runs to the critical values to conclude whether the data sequence is random or not.
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