Job Search A Gallup poll of 195,600 employees showed that 51% of them were actively searching for new jobs. Use a 0.01 significance level to test the claim that the majority of employees are searching for new jobs
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 9.2.6b
Textbook Question
In Exercises 5–20, assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. (Note: Answers in Appendix D include technology answers based on Formula 9-1 along with “Table” answers based on Table A-3 with df equal to the smaller of n1-1 and n2-1)
Readability of Font On a Computer Screen The statistics shown below were obtained from a standard test of readability of fonts on a computer screen (based on data from “Reading on the Computer Screen: Does Font Type Have Effects on Web Text Readability?” by Ali et al., International Education Studies, Vol. 6, No. 3). Reading speed and accuracy were combined into a readability performance score (x), where a higher score represents better font readability.
b. Construct the confidence interval suitable for testing the claim in part (a).


1
Step 1: Identify the given data for both samples. For the Roman font: sample size (n₁) = 24, sample mean (x̄₁) = 66.25, and sample standard deviation (s₁) = 12.96. For the Arial font: sample size (n₂) = 24, sample mean (x̄₂) = 65.62, and sample standard deviation (s₂) = 9.93.
Step 2: Use the formula for the confidence interval for the difference between two means when the population standard deviations are not assumed to be equal. The formula is: CI = (x̄₁ - x̄₂) ± t * √((s₁²/n₁) + (s₂²/n₂)), where t is the critical value from the t-distribution with degrees of freedom calculated using the Welch-Satterthwaite equation.
Step 3: Calculate the degrees of freedom (df) using the Welch-Satterthwaite equation: df = ((s₁²/n₁ + s₂²/n₂)²) / (((s₁²/n₁)² / (n₁ - 1)) + ((s₂²/n₂)² / (n₂ - 1))). Substitute the given values into this formula to find the approximate df.
Step 4: Determine the critical t-value (t) for the desired confidence level (e.g., 95%) using the calculated degrees of freedom and a t-distribution table or technology. Ensure you use a two-tailed test since the confidence interval is symmetric.
Step 5: Substitute the values of x̄₁, x̄₂, s₁, s₂, n₁, n₂, and t into the confidence interval formula to compute the lower and upper bounds of the confidence interval. This will give you the range of values for the difference in readability performance scores between the two fonts.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Confidence Interval
A confidence interval is a range of values, derived from sample statistics, that is likely to contain the true population parameter. It is calculated using the sample mean, standard deviation, and a critical value from the t-distribution, especially when the sample size is small. The width of the interval reflects the level of uncertainty about the estimate, with wider intervals indicating more uncertainty.
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Independent Samples
Independent samples refer to two or more groups that are not related or paired in any way. In statistical analysis, this means that the selection of one sample does not influence the selection of another. This concept is crucial when comparing means from different groups, as it allows for the application of specific statistical tests, such as the independent t-test.
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Standard Deviation
Standard deviation is a measure of the amount of variation or dispersion in a set of values. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation indicates that the values are spread out over a wider range. In the context of the question, it helps assess the reliability of the readability performance scores for the different font types.
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