A production company is studying the relationship between the average cost/unit and number of units produced in a batch. A sample of 10 batches is selected and the data is given below. \[\begin{array} { | c | c | } \hline \text { No. of units produced } & \text { Cost/unit } \\ \hline 20 & 37.7158 \\ \hline 35 & 35.0158 \\ \hline 50 & 30.8158 \\ \hline 65 & 25.8158 \\ \hline 80 & 20.0364 \\ \hline 95 & 16.9064 \\ \hline 110 & 16.3766 \\ \hline 120 & 13.8564 \\ \hline 135 & 13.9696 \\ \hline 150 & 13.847 \\ \hline \end{array}\] a. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between average cost/unit and number of units produced? b. Regardless of your answer to part (a), develop an estimated simple linear regression equation for the data. How much variation in the sample values of cost/unit is explained by this regression model?

a. The scatter chart with number of unit

A research team in at the Gonzaga University is interested in predicting a student's overall university GPA if his/her high school GPA is known. Assume that a random sample of 20 students is selected from the data listed below. \[\begin{array} { | c | c | } \hline \text { High School GPA } & \text { University GPA } \\ \hline 3.65 & 3.72 \\ \hline 3.08 & 3.21 \\ \hline 3.12 & 3 \\ \hline 2.87 & 2.67 \\ \hline 3.34 & 3.57 \\ \hline 2.7 & 2.97 \\ \hline 3.25 & 2.83 \\ \hline 3.01 & 2.89 \\ \hline 3.2 & 3.8 \\ \hline 2.62 & 2.43 \\ \hline 3.71 & 3.82 \\ \hline 2.26 & 2.66 \\ \hline 3.02 & 3.62 \\ \hline 3.58 & 3.83 \\ \hline 3.67 & 3.74 \\ \hline 2.92 & 2.64 \\ \hline 3.71 & 3.53 \\ \hline 3.22 & 2.99 \\ \hline 2.27 & 2.37 \\ \hline 2.8 & 2.69 \\ \hline \end{array}\] a. Develop a scatter chart for these data with High School GPA as the independent variable.What does the scatter chart indicate about the relationship between high school GPAs and overall university GPA? b. Develop an estimated regression equation showing how high school GPA is related to overall university GPA.What is the estimated regression model? c. What is the predicted overall university GPA of Sophia, a student who has been admitted to Gonzaga University, with 3.40 high school GPA?

a. The scatter chart with high school GP

In a simple linear regression model, y = ß0 + ß1x + ε B1 represents the

A) intercept. B) slope of the true regression line. C) mean value of x. D) error term. A) intercept. B) slope of the true regression line. C) mean value of x. D) error term.

Listed below is data on profit and market capitalization for a sample of 15 different firms in U.S. \[\begin{array} { | c | c | } \hline \begin{array} { c } \text { Profits (\$ } \\ \text { millions) } \boldsymbol { y } \end{array} & \begin{array} { c } \text { Market Capitalization } \\ \text { (\$ millions) } \boldsymbol { x } \end{array} \\ \hline 296.2 & 1,936.9 \\ \hline - 25 & 1,171.8 \\ \hline 4,085 & 55,135.8 \\ \hline 6,558 & 97,417.2 \\ \hline 12,525 & 95,198.9 \\ \hline 3,394 & 53,579.7 \\ \hline 442.8 & 12,466.3 \\ \hline 633.1 & 8,894.3 \\ \hline 3,528 & 65,872.4 \\ \hline 2,698 & 25,661.3 \\ \hline 1,200.65 & 19,854.7 \\ \hline 11.987 & 195,643.8 \\ \hline 641.8 & 10,447.8 \\ \hline 5,043 & 66,695.5 \\ \hline 5,206 & 53,558.4 \\ \hline \end{array}\] a. Develop a scatter chart for the above data. What does this chart indicate about the relationship between market capitalization and profit? b. Use the data to develop an estimated regression equation that could be used to estimate a firm's profit based on its market capitalization. What is the estimated regression model? c. What is the predicted profit for the market capitalization of 70,721.3 (million)?

a. The scatter chart with Market Capital

Exam 7: Linear Regression

A production company is studying the relationship between the average cost/unit and number of units produced in a batch. A sample of 10 batches is selected and the data is given below. No. of units produced Cost/unit 20 37.7158 35 35.0158 50 30.8158 65 25.8158 80 20.0364 95 16.9064 110 16.3766 120 13.8564 135 13.9696 150 13.847 a. Develop a scatter chart for these data. What does the scatter chart indicate about the relationship between average cost/unit and number of units produced? b. Regardless of your answer to part (a), develop an estimated simple linear regression equation for the data. How much variation in the sample values of cost/unit is explained by this regression model?

(Essay)

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Question 21

A research team in at the Gonzaga University is interested in predicting a student's overall university GPA if his/her high school GPA is known. Assume that a random sample of 20 students is selected from the data listed below. High School GPA University GPA 3.65 3.72 3.08 3.21 3.12 3 2.87 2.67 3.34 3.57 2.7 2.97 3.25 2.83 3.01 2.89 3.2 3.8 2.62 2.43 3.71 3.82 2.26 2.66 3.02 3.62 3.58 3.83 3.67 3.74 2.92 2.64 3.71 3.53 3.22 2.99 2.27 2.37 2.8 2.69 a. Develop a scatter chart for these data with High School GPA as the independent variable.What does the scatter chart indicate about the relationship between high school GPAs and overall university GPA? b. Develop an estimated regression equation showing how high school GPA is related to overall university GPA.What is the estimated regression model? c. What is the predicted overall university GPA of Sophia, a student who has been admitted to Gonzaga University, with 3.40 high school GPA?

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Question 22

______________ refers to the degree of correlation among independent variables in a regression model.

(Multiple Choice)

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Question 23

The _______________ is the range of values of the independent variables in the data used to estimate the regression model.

(Multiple Choice)

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Question 24

In a simple linear regression model, y = ß₀ + ß₁x + ε B₁ represents the

(Multiple Choice)

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Question 25

The ___________ is a measure of the goodness of fit of the estimated regression equation. It can be interpreted as the proportion of the variability in the dependent variable y that is explained by the estimated regression equation.

(Multiple Choice)

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Question 26

Fitting a model too closely to sample data, resulting in a model that does not accurately reflect the population is termed as

(Multiple Choice)

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Question 27

Prediction of the value of the dependent variable outside the experimental region is called

(Multiple Choice)

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Question 28

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the

(Multiple Choice)

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Question 29

In the graph of the simple linear regression equation, the parameter $B _ { 1 }$ is the ___________ of the regression line.

(Multiple Choice)

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Question 30

The multiple regression model represents pricing for residential housing in a certain market. Predicted Price ̂ = 19,856.56 + 6,985.25 bedrooms + 87.53 square foot. A house in the local market has 5 bedrooms and 3,500 square feet of living area. Use the multiple regression model to determine the predicted price and the residual if the house sells for $360,200.

(Short Answer)

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Question 31

The process of making estimates and drawing conclusions about one or more characteristics of a population through analysis of sample data drawn from the population is known as

(Multiple Choice)

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Question 32

A multiple regression model has the form $\hat { y }$ = 10 + 2 x₁ + 12 x₂. As x1 increases by 1 unit (holding x₂ constant), $\hat { y }$ is expected to increase by how many units?

(Short Answer)

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Question 33

In a linear regression model, the variable (or variables) used for predicting or explaining values of the response variable are known as the ________________. It(they) is(are) denoted by x.

(Multiple Choice)

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Question 34

The multiple regression model represents pricing for residential housing in a certain market. Predicted Price ̂ = 19,856.56 + 6,985.25 bedrooms + 87.53 square foot. A house in the local market has 5 bedrooms and 3,200 square feet of living area. Use the multiple regression model to determine the price and the residual if the house sells for $352,200.

(Short Answer)

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Question 35

Listed below is data on profit and market capitalization for a sample of 15 different firms in U.S. Profits (\ millions) Market Capitalization (\ millions) 296.2 1,936.9 -25 1,171.8 4,085 55,135.8 6,558 97,417.2 12,525 95,198.9 3,394 53,579.7 442.8 12,466.3 633.1 8,894.3 3,528 65,872.4 2,698 25,661.3 1,200.65 19,854.7 11.987 195,643.8 641.8 10,447.8 5,043 66,695.5 5,206 53,558.4 a. Develop a scatter chart for the above data. What does this chart indicate about the relationship between market capitalization and profit? b. Use the data to develop an estimated regression equation that could be used to estimate a firm's profit based on its market capitalization. What is the estimated regression model? c. What is the predicted profit for the market capitalization of 70,721.3 (million)?

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Question 36

A ___________ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables.

(Multiple Choice)

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Question 37

In a simple linear regression analysis the quantity that gives the amount by which the dependent variable changes for a unit change in the independent variable is called the

(Multiple Choice)

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Question 38

A regression analysis involving one independent variable and one dependent variable is referred to as a

(Multiple Choice)

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Question 39

A variable used to model the effect of categorical independent variables in a regression model is known as a

(Multiple Choice)

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Question 40

Showing 21 - 40 of 71

______________ refers to the degree of correlation among independent variables in a regression model.

The _______________ is the range of values of the independent variables in the data used to estimate the regression model.

In a simple linear regression model, y = ß₀ + ß₁x + ε B₁ represents the

The ___________ is a measure of the goodness of fit of the estimated regression equation. It can be interpreted as the proportion of the variability in the dependent variable y that is explained by the estimated regression equation.

Fitting a model too closely to sample data, resulting in a model that does not accurately reflect the population is termed as

Prediction of the value of the dependent variable outside the experimental region is called

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the

In the graph of the simple linear regression equation, the parameter $B _ { 1 }$ is the ___________ of the regression line.

The process of making estimates and drawing conclusions about one or more characteristics of a population through analysis of sample data drawn from the population is known as

A multiple regression model has the form $\hat { y }$ = 10 + 2 x₁ + 12 x₂. As x1 increases by 1 unit (holding x₂ constant), $\hat { y }$ is expected to increase by how many units?

In a linear regression model, the variable (or variables) used for predicting or explaining values of the response variable are known as the ________________. It(they) is(are) denoted by x.

A ___________ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables.

In a simple linear regression analysis the quantity that gives the amount by which the dependent variable changes for a unit change in the independent variable is called the

A regression analysis involving one independent variable and one dependent variable is referred to as a

A variable used to model the effect of categorical independent variables in a regression model is known as a

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Monte Carlo Simulation

Decision Analysis

Filters

Exam 7: Linear Regression

______________ refers to the degree of correlation among independent variables in a regression model.

The _______________ is the range of values of the independent variables in the data used to estimate the regression model.

In a simple linear regression model, y = ß0 + ß1x + ε B1 represents the

The ___________ is a measure of the goodness of fit of the estimated regression equation. It can be interpreted as the proportion of the variability in the dependent variable y that is explained by the estimated regression equation.

Fitting a model too closely to sample data, resulting in a model that does not accurately reflect the population is termed as

Prediction of the value of the dependent variable outside the experimental region is called

The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the

In the graph of the simple linear regression equation, the parameter B1B _ { 1 }B1​ is the ___________ of the regression line.

The process of making estimates and drawing conclusions about one or more characteristics of a population through analysis of sample data drawn from the population is known as

A multiple regression model has the form y^\hat { y }y^​ = 10 + 2 x1 + 12 x2. As x1 increases by 1 unit (holding x2 constant), y^\hat { y }y^​ is expected to increase by how many units?

In a linear regression model, the variable (or variables) used for predicting or explaining values of the response variable are known as the ________________. It(they) is(are) denoted by x.

A ___________ is used to visualize sample data graphically and to draw preliminary conclusions about the possible relationship between the variables.

In a simple linear regression analysis the quantity that gives the amount by which the dependent variable changes for a unit change in the independent variable is called the

A regression analysis involving one independent variable and one dependent variable is referred to as a

A variable used to model the effect of categorical independent variables in a regression model is known as a

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Monte Carlo Simulation

Decision Analysis

Filters

In a simple linear regression model, y = ß₀ + ß₁x + ε B₁ represents the

In the graph of the simple linear regression equation, the parameter $B _ { 1 }$ is the ___________ of the regression line.

A multiple regression model has the form $\hat { y }$ = 10 + 2 x₁ + 12 x₂. As x1 increases by 1 unit (holding x₂ constant), $\hat { y }$ is expected to increase by how many units?