Student Solutions Manual for Basic Business Statistics
13th Edition
ISBN: 9780321926708
Author: David M. Levine; Mark L. Berenson; Timothy C. Krehbiel; Kathryn A. Szabat; David F. Stephan
Publisher: Pearson Education
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Chapter 12, Problem 12PS
Use the following
a. Compute the expected frequency for each cell.
b. Compute
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3. Bayesian Inference – Updating Beliefs
A medical test for a rare disease has the following characteristics:
Sensitivity (true positive rate): 99%
Specificity (true negative rate): 98%
The disease occurs in 0.5% of the population.
A patient receives a positive test result.
Questions:
a) Define the relevant events and use Bayes’ Theorem to compute the probability that the patient actually has the disease.b) Explain why the result might seem counterintuitive, despite the high sensitivity and specificity.c) Discuss how prior probabilities influence posterior beliefs in Bayesian inference.d) Suppose a second, independent test with the same accuracy is conducted and is also positive. Update the probability that the patient has the disease.
4. Linear Regression - Model Assumptions and Interpretation
A real estate analyst is studying how house prices (Y) are related to house size in square feet (X). A simple
linear regression model is proposed:
The analyst fits the model and obtains:
•
Ŷ50,000+150X
YBoB₁X + €
•
R² = 0.76
• Residuals show a fan-shaped pattern when plotted against fitted values.
Questions:
a) Interpret the slope coefficient in context.
b) Explain what the R² value tells us about the model's performance.
c) Based on the residual pattern, what regression assumption is likely violated? What might be the
consequence?
d) Suggest at least two remedies to improve the model, based on the residual analysis.
5. Probability Distributions – Continuous Random Variables
A factory machine produces metal rods whose lengths (in cm) follow a continuous uniform distribution on the interval [98, 102].
Questions:
a) Define the probability density function (PDF) of the rod length.b) Calculate the probability that a randomly selected rod is shorter than 99 cm.c) Determine the expected value and variance of rod lengths.d) If a sample of 25 rods is selected, what is the probability that their average length is between 99.5 cm and 100.5 cm? Justify your answer using the appropriate distribution.
Chapter 12 Solutions
Student Solutions Manual for Basic Business Statistics
Ch. 12 - Determine the critical value of 2 with 1 degree of...Ch. 12 - Determine the critical value of 2 with 1 degree of...Ch. 12 - Use the following contingency table: a. Compute...Ch. 12 - Use the following contingency table: a. Compare...Ch. 12 - Prob. 5PSCh. 12 - Prob. 6PSCh. 12 - Do males or females feel more tense or stressed...Ch. 12 - Prob. 8PSCh. 12 - Prob. 9PSCh. 12 - Prob. 10PS
Ch. 12 - Consider a contingency table, with two rows and...Ch. 12 - Use the following contingency table: a. Compute...Ch. 12 - Use the following contingency table: a. Compute...Ch. 12 - Prob. 14PSCh. 12 - Prob. 15PSCh. 12 - Social media users use a variety of devices to...Ch. 12 - Repeat (a) and (b) of Problem 12.16, assuming that...Ch. 12 - Prob. 18PSCh. 12 - Prob. 19PSCh. 12 - Prob. 20PSCh. 12 - Prob. 21PSCh. 12 - Prob. 22PSCh. 12 - Prob. 23PSCh. 12 - Prob. 24PSCh. 12 - Prob. 25PSCh. 12 - Prob. 26PSCh. 12 - Using Table E.6, determine the lower-and...Ch. 12 - Using Table E.6, determine the lower-tail critical...Ch. 12 - Prob. 29PSCh. 12 - Prob. 30PSCh. 12 - Prob. 31PSCh. 12 - The following information is available for two...Ch. 12 - From Problem 12.32 , at the 0.05 level of...Ch. 12 - In Problems 12.32 and 12.33, what is your...Ch. 12 - A vice president for marketing recruits 20 college...Ch. 12 - Prob. 36PSCh. 12 - Prob. 37PSCh. 12 - The management of a hotel has the business...Ch. 12 - The lengths of life (in hours) of a sample of 40...Ch. 12 - Brand valuations are critical to CEOs, financial...Ch. 12 - A bank with a branch located in a commercial...Ch. 12 - Prob. 42PSCh. 12 - Prob. 43PSCh. 12 - Prob. 44PSCh. 12 - A pet food company has the business objective of...Ch. 12 - A hospital conducted a study of the waiting time...Ch. 12 - Prob. 47PSCh. 12 - An advertising agency has been hired by a...Ch. 12 - Prob. 49PSCh. 12 - The more costly and time consuming it is to export...Ch. 12 - Prob. 51PSCh. 12 - Prob. 52PSCh. 12 - Prob. 53PSCh. 12 - Prob. 54PSCh. 12 - Prob. 55PSCh. 12 - Prob. 56PSCh. 12 - Prob. 57PSCh. 12 - Prob. 58PSCh. 12 - Prob. 59PS
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- 2. Hypothesis Testing - Two Sample Means A nutritionist is investigating the effect of two different diet programs, A and B, on weight loss. Two independent samples of adults were randomly assigned to each diet for 12 weeks. The weight losses (in kg) are normally distributed. Sample A: n = 35, 4.8, s = 1.2 Sample B: n=40, 4.3, 8 = 1.0 Questions: a) State the null and alternative hypotheses to test whether there is a significant difference in mean weight loss between the two diet programs. b) Perform a hypothesis test at the 5% significance level and interpret the result. c) Compute a 95% confidence interval for the difference in means and interpret it. d) Discuss assumptions of this test and explain how violations of these assumptions could impact the results.arrow_forward1. Sampling Distribution and the Central Limit Theorem A company produces batteries with a mean lifetime of 300 hours and a standard deviation of 50 hours. The lifetimes are not normally distributed—they are right-skewed due to some batteries lasting unusually long. Suppose a quality control analyst selects a random sample of 64 batteries from a large production batch. Questions: a) Explain whether the distribution of sample means will be approximately normal. Justify your answer using the Central Limit Theorem. b) Compute the mean and standard deviation of the sampling distribution of the sample mean. c) What is the probability that the sample mean lifetime of the 64 batteries exceeds 310 hours? d) Discuss how the sample size affects the shape and variability of the sampling distribution.arrow_forwardA biologist is investigating the effect of potential plant hormones by treating 20 stem segments. At the end of the observation period he computes the following length averages: Compound X = 1.18 Compound Y = 1.17 Based on these mean values he concludes that there are no treatment differences. 1) Are you satisfied with his conclusion? Why or why not? 2) If he asked you for help in analyzing these data, what statistical method would you suggest that he use to come to a meaningful conclusion about his data and why? 3) Are there any other questions you would ask him regarding his experiment, data collection, and analysis methods?arrow_forward
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