A dog food company is interested in how much dog food a dog consumes based off of its weight. The company takes a random sample of dogs and finds that the best regression model to represent the data is as follows: Simple Linear Regression Results: Dependent Variable: Ounces of Food Consumed in a Week Independent Variable: Weight Food Consumed=-32.86 + 5.25xWeight Sample Size: 500 R2:0.8129 Estimate of error standard deviation: 78563121 Suppose that a dog weighs 43.7 pounds, and typically eats 180 ounces of food per week. How many ounces of food would we predict the dog eats in a week, based on the least squares estimate? Provide your answer accurate to 1 digit past the decimal point. Answer: Suppose another dog weighs 20.1 pounds and consumes 70 ounces of food per week. What is the residual associate to this individual using the least squares estimate? Provide your answer accurate to 1 digit past the decimal point. Answer:

A dog food company is interested in how much dog food a dog consumes based off of its weight. The company takes a random sample of dogs and finds that the best regression model to represent the data is as follows: Simple Linear Regression Results: Dependent Variable: Ounces of Food Consumed in a Week Independent Variable: Weight Food Consumed=-32.86 + 5.25xWeight Sample Size: 500 R2:0.8129 Estimate of error standard deviation: 78563121 Suppose that a dog weighs 43.7 pounds, and typically eats 180 ounces of food per week. How many ounces of food would we predict the dog eats in a week, based on the least squares estimate? Provide your answer accurate to 1 digit past the decimal point. Answer: Suppose another dog weighs 20.1 pounds and consumes 70 ounces of food per week. What is the residual associate to this individual using the least squares estimate? Provide your answer accurate to 1 digit past the decimal point. Answer:

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
Does Table 1 represent a linear function? If so, finda linear equation that models the data.
Given a generic data set (x,y) with a linear regression. How do you determine if the y(dependent) will be less/greater than a certain value at a decided value of x?
Given a generic data set (x,y) with a linear regression. How do you determine if the y(dependent) will be less than a certain value?
Which of the multivariate regression parameters listed below would be best interpreted as: the predicted value on the dependent variable when all of the independent variables in the model are equal to zero. a b1 X1 R2
Which of the multivariate regression parameters listed below would be best interpreted as: the proportion of variation in the dependent variable explain by all the independent variables in the model. a b1 X1 R2
Life insurance companies are keenly interested in predicting how long their customers are likely to live, because this will determine their premiums and ultimately their profitability. An Australian life insurance company is interested in the relationship, if any, between the age at death of their male customers and that of the customer’s father. Data are collected on a random sample of 100 of their male customers who have recently died. The customer’s age at death was plotted against that of their father and a linear regression model applied. Relevant output is shown below. Say how you know from the output that there actually is a significant linear relationship between a male customer’s age at death and his father’s age at death. State the value of the coefficient of Father’s Age (Death) and interpret this value in the context of the problem at hand.State the value of the coefficient of determination in the model and interpret this value in the context of the situation.
Life insurance companies are keenly interested in predicting how long their customers are likely to live, because this will determine their premiums and ultimately their profitability. An Australian life insurance company is interested in the relationship, if any, between the age at death of their male customers and that of the customer’s father. Data are collected on a random sample of 100 of their male customers who have recently died. The customer’s age at death was plotted against that of their father and a linear regression model applied. Relevant output is shown below Examine both the scatterplot and the correlation matrix provided above. Comment on the apparent relationship between the customer’s age at death and their father’s age at death in the plot. Explain how the information in the correlation matrix supports your conclusion
A sociologist was hired by a large city hospital to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (miles) between home and work for the employee. A sample of 10 employees was chosen, and the following data were collected. A. Is the estimated regression equation appropriate and adequate
A researcher is interested in examining the relationship between spousal abuse and child abuse. Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices. Calculate the linear regression line for the following data. Note you have already calculated the first step to this analysis