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 26m
- 11. Correlation1h 6m
- 12. Regression1h 35m
- 13. Chi-Square Tests & Goodness of Fit1h 57m
- 14. ANOVA1h 0m
13. Chi-Square Tests & Goodness of Fit
Independence Test Using TI-84
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A student performs an independence test using technology to see if pet ownership is independent of relationship status. They get the following results: & . What can they conclude about pet ownership and relationship status?
A
Reject H0 since there is enough evidence to suggest that pet ownership and relationship status are dependent.
B
Fail to reject since there is not enough evidence to suggest that pet ownership and relationship status are dependent.
C
Reject H0 since there is not enough evidence to suggest that pet ownership and relationship status are dependent.
D
Fail to reject H0 since there is enough evidence to suggest that pet ownership and relationship status are dependent.

1
Identify the null hypothesis \( H_0 \) and the alternative hypothesis \( H_a \). For a test of independence, \( H_0 \) states that pet ownership and relationship status are independent, while \( H_a \) states that they are dependent.
Look at the given test statistic \( \chi^2 = 0.545 \) and the p-value \( p = 0.7614 \). The p-value represents the probability of observing a test statistic as extreme as, or more extreme than, the one calculated, assuming \( H_0 \) is true.
Compare the p-value to the significance level \( \alpha \) (commonly 0.05). If \( p \leq \alpha \), reject \( H_0 \); if \( p > \alpha \), fail to reject \( H_0 \).
Since the p-value \( 0.7614 \) is greater than the typical significance level \( 0.05 \), there is not enough evidence to reject the null hypothesis.
Conclude that we fail to reject \( H_0 \), meaning there is not enough evidence to suggest that pet ownership and relationship status are dependent; they appear to be independent based on this test.
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