Elementary Statistics (Text Only)
2nd Edition
ISBN: 9780077836351
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Publisher: McGraw Hill
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Chapter 4.2, Problem 33E
a.
To determine
The equation of the least-squares regression line.
b.
To determine
The predicted salary for a graduate with
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C4 Q6 V1: Randomly collected student data in the dataset STATISTICSSTUDENTSSURVEYFORR contains the columns FEDBEST (preferred Federal party (Conservative, Green, Liberals, or NDP) ) , UNDERGORGRAD (degree being sought (GraduateProfessional, Undergraduate) ) and GENDERIDENTITY (Female or Male or Other). Make a crosstab (contingency) table of the counts for each of the (UNDERGORGRAD, FEDBEST) pairs for ONLY the females. If we randomly select a female student who is pursuing a graduateprofessional degree, what is the probability that she prefers the Federal Liberals. Choose the most correct (closest) answer below.
Question 6 Answer
a.
0.128
b.
0.263
c.
0.744
d.
0.333
Install RStudio: Begin by installing RStudio on your computer. If you haven't done so, please refer to the official RStudio website for download and installation instructions.
Watch the Tutorial Video: Watch the provided video tutorial that explains how to run RStudio. Pay close attention to the steps for opening and managing data files. https://www.youtube.com/watch?v=RhJp6vSZ7z0
Open RStudio: Once RStudio is installed, open the application.
Load the Dataset: In RStudio, open a data file named "mtcars". To do this, type the command mtcars in the script editor and run the command.
Attach the Data: Next, attach the dataset using the command attach(mtcars).
Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following…
A marketing professor has surveyed the students at her university to better understand attitudes towards PPT usage for higher education. To be able to make inferences to the entire student body, the sample drawn needs to represent the university’s student population on all key characteristics. The table below shows the five key student demographic variables. The professor found the breakdown of the overall student body in the university’s fact book posted online.
A non-parametric chi-square test was used to test the sample demographics against the population percentages shown in the table above. Review the output for the five chi-square tests on the following pages and answer the five questions:
Based on the chi-square test, which sample variables adequately represent the university’s student population and which ones do not? Support your answer by providing the p-value of the chi-square test and explaining what it means.
Using the results from Question 1, make recommendation for…
Chapter 4 Solutions
Elementary Statistics (Text Only)
Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - Prob. 13ECh. 4.1 - Prob. 14ECh. 4.1 - In Exercises 13-16, determine whether the...Ch. 4.1 - In Exercises 13-16, determine whether the...Ch. 4.1 - In Exercises 17-20, compute the correlation...Ch. 4.1 - In Exercises 17-20, compute the correlation...
Ch. 4.1 - In Exercises 17-20, compute the correlation...Ch. 4.1 - In Exercises 17-20, compute the correlation...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - Price of eggs and milk: The following table...Ch. 4.1 - Government funding: The following table presents...Ch. 4.1 - Pass the ball: The NFL Scouting Combine is an...Ch. 4.1 - Carbon footprint: Carbon dioxide (co2) is produced...Ch. 4.1 - Prob. 35ECh. 4.1 - Prob. 36ECh. 4.1 - Blood pressure: A blood pressure measurement...Ch. 4.1 - Prob. 38ECh. 4.1 - Police and crime: In a survey of cities in the...Ch. 4.1 - Age and education: A survey of U.S. adults showed...Ch. 4.1 - Whats the correlation? In a sample of adults, the...Ch. 4.1 - Prob. 42ECh. 4.1 - Changing means and standard deviations: A small...Ch. 4.2 - In Exercises 5-7, fill in each blank with the...Ch. 4.2 - In Exercises 5-7, fill in each blank with the...Ch. 4.2 - In Exercises 5-7, fill in each blank with the...Ch. 4.2 - Prob. 8ECh. 4.2 - Prob. 9ECh. 4.2 - Prob. 10ECh. 4.2 - Prob. 11ECh. 4.2 - Prob. 12ECh. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - Compute the least-squares regression he for...Ch. 4.2 - Compute the least-squares regression he for...Ch. 4.2 - In a hypothetical study of the relationship...Ch. 4.2 - Assume in a study of educational level in years...Ch. 4.2 - Prices of egg and milk: The following table...Ch. 4.2 - Prob. 22ECh. 4.2 - Pass the ball: The NFL Scouting Combine is an...Ch. 4.2 - Carbon footprint: Carbon dioxide (CO2) is produced...Ch. 4.2 - Foot temperatures: Foot ulcers are a common...Ch. 4.2 - Mortgage payments: The following table presents...Ch. 4.2 - Blood pressure: A blood pressure measurement...Ch. 4.2 - Butterfly wings: Do larger butterflies live...Ch. 4.2 - Interpreting technology: The following display...Ch. 4.2 - Interpreting technology: The following display...Ch. 4.2 - Interpreting technology: The following MINITAB...Ch. 4.2 - Interpreting technology: The following MINITAB...Ch. 4.2 - Prob. 33ECh. 4.2 - Prob. 34ECh. 4.2 - Least-squares regression line for z-scores: The...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - Prob. 10ECh. 4.3 - Prob. 11ECh. 4.3 - In Exercises 11-14, determine whether the...Ch. 4.3 - Prob. 13ECh. 4.3 - In Exercises 11-14, determine whether the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - Prob. 19ECh. 4.3 - Prob. 20ECh. 4.3 - Prob. 21ECh. 4.3 - Prob. 22ECh. 4.3 - Prob. 23ECh. 4.3 - Prob. 24ECh. 4.3 - Mutant genes: In a study to determine whether the...Ch. 4.3 - Imports and exports: The following table presents...Ch. 4.3 - Energy consumption: The following table presents...Ch. 4.3 - Cost of health care: The following table presents...Ch. 4.3 - Prob. 29ECh. 4.3 - Broadway: The following table presents the average...Ch. 4.3 - Prob. 31ECh. 4.3 - Transforming a variable: The following table...Ch. 4.3 - Prob. 33ECh. 4.3 - Prob. 34ECh. 4 - Compute the correlation coefficient for the...Ch. 4 - The number of theaters showing the movie Monsters...Ch. 4 - Use the data in Exercise 2 to compute the...Ch. 4 - A scatterplot has a correlation of r=1. Describe...Ch. 4 - Prob. 5CQCh. 4 - The following table presents the average delay in...Ch. 4 - Use the least-squares regression line computed in...Ch. 4 - Use the least-squares regression line computed in...Ch. 4 - Prob. 9CQCh. 4 - A scatterplot has a least-squares regression line...Ch. 4 - Prob. 11CQCh. 4 - Prob. 12CQCh. 4 - A sample of students was studied to determine the...Ch. 4 - In a scatter-plot; the point (-2, 7) is...Ch. 4 - The correlation coefficient for a data set is...Ch. 4 - Prob. 1RECh. 4 - Prob. 2RECh. 4 - Hows your mileage? Weight (in tons) and fuel...Ch. 4 - Prob. 4RECh. 4 - Energy efficiency: A sample of 10 households was...Ch. 4 - Energy efficiency: Using the data in Exercise 5:...Ch. 4 - Prob. 7RECh. 4 - Prob. 8RECh. 4 - Prob. 9RECh. 4 - Prob. 10RECh. 4 - Baby weights: The average gestational age (time...Ch. 4 - Commute times: Every morning, Tania leaves for...Ch. 4 - Prob. 13RECh. 4 - Prob. 14RECh. 4 - Prob. 15RECh. 4 - Describe an example which two variables are...Ch. 4 - Two variables x and y have a positive association...Ch. 4 - Prob. 3WAICh. 4 - Prob. 4WAICh. 4 - Prob. 5WAICh. 4 - Prob. 6WAICh. 4 - Prob. 7WAICh. 4 - Prob. 8WAICh. 4 - Prob. 9WAICh. 4 - The following table, Reproduce from chapter...Ch. 4 - The following table, Reproduce from chapter...Ch. 4 - The following table. Reproduce from chapter...Ch. 4 - Prob. 4CSCh. 4 - Prob. 5CSCh. 4 - The relationship between inflation and...Ch. 4 - The relationship between inflation and...Ch. 4 - Relationship between inflation and unemployment is...Ch. 4 - Relationship between inflation and unemployment is...Ch. 4 - If we are going to use data from this year to...Ch. 4 - If we are going to use data from this year to...Ch. 4 - Prob. 12CSCh. 4 - Prob. 13CSCh. 4 - Prob. 14CSCh. 4 - Prob. 15CS
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- A marketing professor has surveyed the students at her university to better understand attitudes towards PPT usage for higher education. To be able to make inferences to the entire student body, the sample drawn needs to represent the university’s student population on all key characteristics. The table below shows the five key student demographic variables. The professor found the breakdown of the overall student body in the university’s fact book posted online. A non-parametric chi-square test was used to test the sample demographics against the population percentages shown in the table above. Review the output for the five chi-square tests on the following pages and answer the five questions: Based on the chi-square test, which sample variables adequately represent the university’s student population and which ones do not? Support your answer by providing the p-value of the chi-square test and explaining what it means. Using the results from Question 1, make recommendation for…arrow_forwardA retail chain is interested in determining whether a digital video point-of-purchase (POP) display would stimulate higher sales for a brand advertised compared to the standard cardboard point-of-purchase display. To test this, a one-shot static group design experiment was conducted over a four-week period in 100 different stores. Fifty stores were randomly assigned to the control treatment (standard display) and the other 50 stores were randomly assigned to the experimental treatment (digital display). Compare the sales of the control group (standard POP) to the experimental group (digital POP). What were the average sales for the standard POP display (control group)? What were the sales for the digital display (experimental group)? What is the (mean) difference in sales between the experimental group and control group? List the null hypothesis being tested. Do you reject or retain the null hypothesis based on the results of the independent t-test? Was the difference between the…arrow_forwardWhat were the average sales for the four weeks prior to the experiment? What were the sales during the four weeks when the stores used the digital display? What is the mean difference in sales between the experimental and regular POP time periods? State the null hypothesis being tested by the paired sample t-test. Do you reject or retain the null hypothesis? At a 95% significance level, was the difference significant? Explain why or why not using the results from the paired sample t-test. Should the manager of the retail chain install new digital displays in each store? Justify your answer.arrow_forward
- A retail chain is interested in determining whether a digital video point-of-purchase (POP) display would stimulate higher sales for a brand advertised compared to the standard cardboard point-of-purchase display. To test this, a one-shot static group design experiment was conducted over a four-week period in 100 different stores. Fifty stores were randomly assigned to the control treatment (standard display) and the other 50 stores were randomly assigned to the experimental treatment (digital display). Compare the sales of the control group (standard POP) to the experimental group (digital POP). What were the average sales for the standard POP display (control group)? What were the sales for the digital display (experimental group)? What is the (mean) difference in sales between the experimental group and control group? List the null hypothesis being tested. Do you reject or retain the null hypothesis based on the results of the independent t-test? Was the difference between the…arrow_forwardQuestion 4 An article in Quality Progress (May 2011, pp. 42-48) describes the use of factorial experiments to improve a silver powder production process. This product is used in conductive pastes to manufacture a wide variety of products ranging from silicon wafers to elastic membrane switches. Powder density (g/cm²) and surface area (cm/g) are the two critical characteristics of this product. The experiments involved three factors: reaction temperature, ammonium percentage, stirring rate. Each of these factors had two levels, and the design was replicated twice. The design is shown in Table 3. A222222222222233 Stir Rate (RPM) Ammonium (%) Table 3: Silver Powder Experiment from Exercise 13.23 Temperature (°C) Density Surface Area 100 8 14.68 0.40 100 8 15.18 0.43 30 100 8 15.12 0.42 30 100 17.48 0.41 150 7.54 0.69 150 8 6.66 0.67 30 150 8 12.46 0.52 30 150 8 12.62 0.36 100 40 10.95 0.58 100 40 17.68 0.43 30 100 40 12.65 0.57 30 100 40 15.96 0.54 150 40 8.03 0.68 150 40 8.84 0.75 30 150…arrow_forward- + ++ Table 2: Crack Experiment for Exercise 2 A B C D Treatment Combination (1) Replicate I II 7.037 6.376 14.707 15.219 |++++ 1 བྱ॰༤༠སྦྱོ སྦྱོཋཏྟཱུ a b ab 11.635 12.089 17.273 17.815 с ас 10.403 10.151 4.368 4.098 bc abc 9.360 9.253 13.440 12.923 d 8.561 8.951 ad 16.867 17.052 bd 13.876 13.658 abd 19.824 19.639 cd 11.846 12.337 acd 6.125 5.904 bcd 11.190 10.935 abcd 15.653 15.053 Question 3 Continuation of Exercise 2. One of the variables in the experiment described in Exercise 2, heat treatment method (C), is a categorical variable. Assume that the remaining factors are continuous. (a) Write two regression models for predicting crack length, one for each level of the heat treatment method variable. What differences, if any, do you notice in these two equations? (b) Generate appropriate response surface contour plots for the two regression models in part (a). (c) What set of conditions would you recommend for the factors A, B, and D if you use heat treatment method C = +? (d) Repeat…arrow_forward
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