Introduction To Statistics And Data Analysis
6th Edition
ISBN: 9781337794503
Author: PECK
Publisher: Cengage
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Chapter 5, Problem 81E
To determine
Obtain the logistic regression equation for the given data.
Predict the
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A study by Wolfinger in 2015 showed that the probability of divorce decreases with marriage age for people who were married between 18 and 32 years old. Would it be appropriate to use this decreasing trend to predict the probability of divorce for a person who was married at 65 years old? why or why not? what poor practice in regression does this illustrate?
While attempting to measure its risk exposure for the upcoming year, an insurance company notices a trend between the age of a customer and the number of claims per year. It appears that the number of claims keep going up as customers age. After performing a regression, they find that the relationship is (claims per year) = 0.385*(age) + 5.218. If a customer is 44.315 years old and they make an average of 11.239 claims per year, the residual is -11.04. Interpret this residual in terms of the problem.
Question 10 options:
1)
The number of claims per year is 11.04 claims less than what we would expect.
2)
The age is 11.04 years larger than what we would expect.
3)
The age is 11.04 years less than what we would expect.
4)
The number of claims per year is 11.239 claims less than what we would expect.
5)
The number of claims per year is 11.04 claims…
State the Interpretation of Regression Coefficients?
Chapter 5 Solutions
Introduction To Statistics And Data Analysis
Ch. 5.1 - For each of the scatterplots shown, answer the...Ch. 5.1 - For each of the following pairs of variables,...Ch. 5.1 - For each of the following pairs of variables,...Ch. 5.1 - For each of the following pairs of variables,...Ch. 5.1 - Is the following statement correct? Explain why or...Ch. 5.1 - Draw a scatterplot for which r = 1.Ch. 5.1 - Draw a scatterplot for which r = 1.Ch. 5.1 - Each year J.D. Power and Associates surveys new...Ch. 5.1 - The accompanying data are x = Cost (cents per...Ch. 5.1 - The authors of the paper Flat-footedness Is Not a...
Ch. 5.1 - The paper The Relationship Between Cell Phone Use,...Ch. 5.1 - Data from the U.S. Federal Reserve Board (federal...Ch. 5.1 - The article 115K! The 13 Best Paying U.S....Ch. 5.1 - It may seem odd, but one of the ways biologists...Ch. 5.1 - An auction house released a list of 25 recently...Ch. 5.1 - A sample of automobiles traversing a certain...Ch. 5.2 - Two scatterplots are shown below. Explain why it...Ch. 5.2 - The authors of the paper Statistical Methods for...Ch. 5.2 - The accompanying data are a subset of data from...Ch. 5.2 - The authors of the paper Evaluating Existing...Ch. 5.2 - The authors of the paper referenced in the...Ch. 5.2 - A sample of 548 ethnically diverse students from...Ch. 5.2 - The relationship between hospital patient-to-nurse...Ch. 5.2 - The report Airline Quality Rating 2016...Ch. 5.2 - Acrylamide is a chemical that is sometimes found...Ch. 5.2 - Use the acrylamide data given in the previous...Ch. 5.2 - Studies have shown that people who suffer sudden...Ch. 5.2 - The data given in the previous exercise on x =...Ch. 5.2 - An article on the cost of housing in Califomia...Ch. 5.2 - The following data on sale price, size, and...Ch. 5.2 - Explain why it can be dangerous to use the...Ch. 5.2 - The sales manager of a large company selected a...Ch. 5.2 - Explain why the slope b of the least-squares line...Ch. 5.2 - Prob. 34ECh. 5.3 - Does it pay to stay in school? The report Trends...Ch. 5.3 - The data in the accompanying table is from the...Ch. 5.3 - The paper referenced in the previous exercise also...Ch. 5.3 - Consider the residual plot from the previous...Ch. 5.3 - The report Airline Quality Rating 2016...Ch. 5.3 - Acrylamide is a chemical that is sometimes found...Ch. 5.3 - Consider the scatterplot of acrylamide...Ch. 5.3 - Some types of algae have the potential to cause...Ch. 5.3 - The relationship between x = Total number of...Ch. 5.3 - The residuals from the least-squares line for the...Ch. 5.3 - The first Batman movie was made over 50 years ago...Ch. 5.3 - The article 115K! The 13 Best Paying U.S....Ch. 5.3 - The article Examined Life: What Stanley H. Kaplan...Ch. 5.3 - The accompanying data are a subset of data from...Ch. 5.3 - The article California State Parks Closure List...Ch. 5.3 - The article referenced in the previous exercise...Ch. 5.3 - A study was carried out to investigate the...Ch. 5.3 - Both r2 and se are used to assess the fit of a...Ch. 5.3 - Prob. 53ECh. 5.4 - The following data on x = Frying time (in seconds)...Ch. 5.4 - Use the information provided in the previous...Ch. 5.4 - The paper Aspects of Food Finding by Wintering...Ch. 5.4 - Food intake of grazing animals is limited by the...Ch. 5.4 - A study, described in the paper Prediction of...Ch. 5.4 - Prob. 59ECh. 5.4 - The following table gives the number of heart...Ch. 5.4 - Refer to the heart transplant data given in the...Ch. 5.4 - The paper Population Pressure and Agricultural...Ch. 5.4 - Determining the age of an animal can sometimes be...Ch. 5.5 - The paper How Lead Exposure Relates to Temporal...Ch. 5.5 - The following quote is from the paper Evaluation...Ch. 5 - The accompanying data represent x = Amount of...Ch. 5 - The paper A Cross-National Relationship Between...Ch. 5 - The following data on x = Score on a measure of...Ch. 5 - The paper Effects of Canine Parvovirus (CPV) on...Ch. 5 - The paper Depression, Body Mass Index, and Chronic...Ch. 5 - The paper Aspects of Food Finding by Wintering...Ch. 5 - Data on salmon availability (x) and the percentage...Ch. 5 - No tortilla chip lover likes soggy chips, so it is...Ch. 5 - The article Reduction is Soluble Protein and...Ch. 5 - The following quote is from the paper The Weight...Ch. 5 - An accurate assessment of oxygen consumption...Ch. 5 - Consider the four (x, y) pairs (0, 0), (1, 1), 1,...Ch. 5 - Prob. 1CRECh. 5 - Data from a survey of 1046 adults age 50 and older...Ch. 5 - Prob. 3CRECh. 5 - Prob. 4CRECh. 5 - Prob. 5CRECh. 5 - The amount of money spent each year on science,...Ch. 5 - Below are the data used to construct the time...Ch. 5 - In August 2009, Harris Interactive released the...Ch. 5 - Prob. 9CRECh. 5 - Prob. 10CRECh. 5 - Prob. 11CRECh. 5 - Prob. 12CRECh. 5 - Cost-to-charge ratios (the percentage of the...Ch. 5 - In the article Reproductive Biology of the Aquatic...Ch. 5 - Prob. 15CRECh. 5 - Anabolic steroid abuse has been increasing despite...Ch. 5 - Prob. 81ECh. 5 - Prob. 82ECh. 5 - Prob. 83ECh. 5 - Prob. 84ECh. 5 - Suppose the hypothetical data below are from a...Ch. 5 - Prob. 86E
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- Find the mean hourly cost when the cell phone described above is used for 240 minutes.arrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forwardA university has found a correlation between Math SAT scores and first year GPAs, and r = 0.4. Suppose a student scores at the 10th percentile of Math SAT scores. What would regression predict for their GPA? Choose the answer that is closest. Group of answer choices It's at the 20th percentile it's at the 28th percentile it's at the 33rd percentile it's at the 30th percentilearrow_forward
- A researcher uses a regression equation to predict home heating bills (dollar cost), based on home size (square feet). The correlation between predicted bills and home size is 0.70. What is the correct interpretation of this finding? (A) 70% of the variability in home heating bills can be explained by home size. (B) 49% of the variability in home heating bills can be explained by home size. (C) For each added square foot of home size, heating bills increased by 70 cents. (D) For each added square foot of home size, heating bills increased by 49 cents. (E) None of the above.arrow_forwardWould the regression in Equation be useful for predicting test scoresin a school district in Massachusetts? Why or why not?arrow_forwardExplain the process to Compute predicted scores from a regression equation?arrow_forward
- The regression equation is intended to be the “best fitting” straight line for a set of data. What is the criterion for “best fitting”?arrow_forwardwhat is the best-predicted weight for a bear with 43 inches, and What is the regression equation?arrow_forwardUniversal bank launched a campaign to promote personal loans to its customers. In order to better understand customers' decision, the bank built a logistic regression model to predict the probability of a customer accepting personal loan offered by the bank. Define p= P(Personal. Loan = 1) odds = The model with estimated coefficients is: log(odds) = -12.6806 – 0.0369 x Age + 0.0491 x Experience + 0.0613 x Income + 0.5435 x Family + 0.2166 x CCAvg + 4.2681 x EducationGraduate + 4.4408 x EducationProfessional + 0.0015 x Mortgage – 1.1457 x Securities. Account + 4.5856 x CD. Account – 0.8588 x Online – 1.2514 x CreditCard Descriptions of the variables in the model: Personal.Loan: Coded as 1 if customer responded to the last personal loan campaign Age: Customer's age in completed years Experience: Number of years professional experience Income: Annual incomes of the customer (in $000s) Family: Family size of the customer CCAvg: Average spending on credit cards per month (in $000s)…arrow_forward
- To monitor and improve its productivity, a company made an investigation and found out that the factor that affects the productivity the most is the absenteeism. The company data analytics department have collected data about the two variables (Productivity and Absenteeism) for the 12 past years as shown in the table below. Now the purpose of the company is to determine, through regression analysis, whether the productivity is statistically affected by the absenteeism level or not. Year Absenteeism Productivity (in number of absent worker) (in Million AED) 1 204 342 2 352 336 3 154 406 4 206 410 5 422 278 6 530 214 7 750 138 8 482 268 9 374 262 10 120 356 11 188 396 12 634 152 Questions: Construct a scatter diagram for the data about productivity and absenteeism then interpret the possible relationship that can be found. Construct a simple regression model to predict the…arrow_forwardWe wish to determine if there is a correlation between the birth weight (in grams) of nine newborn infants and the length of their mothers’ stay (in days) in the hospital. The results of a correlation and regression analysis are indicated in the Excel output below. The mean birth weight of the newborn infants (the independent variable) was 3162.5 grams, and the mean length of their mothers’ stay in the hospital (the dependent variable) was 7 days. SUMMARY OUTPUT Regression Statistics Multiple R 0.862675 R Square 0.744208 Adjusted R Square 0.707666 Standard Error 6.02142 Observations 9 ANOVA df SS MS F Significance F Regression 1 738.4198 738.4198 20.36599 0.002756 Residual 7 253.8025 36.25749 Total 8 992.2222…arrow_forwardA popular television show recently released a video preview for the upcoming season on its website. As fans of the show discover the video, the number of views of the preview video has grown each day during the last 2 weeks. The number of days since the release of the video and the natural log of the number of video views is shown in the scatterplot. Based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and number of views? An exponential model is appropriate because the residual plot does not show a clear pattern. A linear model is appropriate because the scatterplot shows a strong, positive linear relationship. A power model is appropriate because the scatterplot of days and natural log of views is strong and linear. An exponential model is appropriate because the relationship between days and the natural log of views is linear, and the residual plot does not show a clear pattern.arrow_forward
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