Question 1

Which of the following helps in evaluation of autocorrelation?

Accepted Answer

A) Breusch-Pagan test 
B) Durbin-Watson statistic 
C) Hosmer-Lemeshow test 
D) Cochran-Mantel-Haenszel statistics 
A) Breusch-Pagan test 
B) Durbin-Watson statistic 
C) Hosmer-Lemeshow test 
D) Cochran-Mantel-Haenszel statistics B

Question 2

Use the data given below to answer the following question(s).
Following is an extract from a firm's database detailing the number of hours spent on the job by employees and their corresponding pay.(Note: Assume a level of significance of 0.05 wherever necessary.)
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Hours spent } \
\text { on the job }
\end{array} & \text { Salary (\$) } \
\hline 4 & 340 \
\hline 12 & 850 \
\hline 7 & 570 \
\hline 5 & 470 \
\hline 11 & 820 \
\hline 8 & 610 \
\hline 9 & 630 \
\hline 13 & 900 \
\hline 10 & 800 \
\hline 6 & 480 \
\hline
\end{array}$$
-The standard error may be assumed to be large if the data are clustered close to the regression line.

Accepted Answer

A) True 
 B)False  False

Question 3

Use the data given below to answer the following question(s).
Following is an extract from a firm's database detailing the number of hours spent on the job by employees and their corresponding pay.(Note: Assume a level of significance of 0.05 wherever necessary.)
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Hours spent } \
\text { on the job }
\end{array} & \text { Salary (\$) } \
\hline 4 & 340 \
\hline 12 & 850 \
\hline 7 & 570 \
\hline 5 & 470 \
\hline 11 & 820 \
\hline 8 & 610 \
\hline 9 & 630 \
\hline 13 & 900 \
\hline 10 & 800 \
\hline 6 & 480 \
\hline
\end{array}$$
-Is the hours spent on the job a statistically significant variable in explaining the variation in pay of employees? (Hint: Use Regression tool).

Accepted Answer

Hypothesis test for significance of regression:
H₀ : β1 = 0
H₁ : β1 ≠ 0
where, β1 is the slope of the intercept.
Significance F, that is, the p-value associated with the hypothesis test is essentially zero (2.525 × 10⁻⁷).Therefore, assuming a level of significance of 0.05, the null hypothesis must be rejected and conclude that the slope-the coefficient for number of hours spent on the job-is not zero.This means that work hours is a statistically significant variable in explaining the variation in employee pay.

Question 4

In multiple regression, R Square is referred to as the:

Accepted Answer

A) multiple correlation coefficient. 
B) coefficient of autocorrelation. 
C) coefficient of multiple determination. 
D) multiple significance coefficient. 
A) multiple correlation coefficient. 
B) coefficient of autocorrelation. 
C) coefficient of multiple determination. 
D) multiple significance coefficient.

Question 5

Use the data given below to answer the following question(s).
Following is an extract from the database of a construction company.The table shows the height of walls in feet and the cost of raising them.The estimated simple linear regression equation is given as Ŷ = b0 + b1X.(Hint: Use Excel functions).
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Height } \
\text { (ft) }
\end{array} & \text { Cost (\$) } \
\hline 4 & 670 \
\hline 3 & 430 \
\hline 7 & 810 \
\hline 9 & 1100 \
\hline 6 & 790 \
\hline 8 & 880 \
\hline 5 & 760 \
\hline 11 & 1200 \
\hline
\end{array}$$
-Which of the following generates a scatter chart in Excel with the values predicted by the regression model included?

Accepted Answer

A) Trendline 
B) Residual Plots 
C) R Square 
D) Line Fit Plots 
A) Trendline 
B) Residual Plots 
C) R Square 
D) Line Fit Plots

Question 6

________ means that the variation about the regression line is constant for all values of the independent variable.

Accepted Answer

A) Autocorrelation 
B) Normality of errors 
C) Homoscedasticity 
D) Linearity 
A) Autocorrelation 
B) Normality of errors 
C) Homoscedasticity 
D) Linearity

Question 7

When a scatter chart of data shows a nonlinear relationship, the nonlinear model can be expressed as:

Accepted Answer

A) Y = β₀ + β₁X + β₂X² + ε 
B) Y = β₀+ β₁X + (β₂X)² + ε 
C) Y = β₀ + β₁X + β₂X 
D) Y = β₀ + β₁X² + β₂X² + ε 
A) Y = β₀ + β₁X + β₂X² + ε 
B) Y = β₀+ β₁X + (β₂X)² + ε 
C) Y = β₀ + β₁X + β₂X 
D) Y = β₀ + β₁X² + β₂X² + ε

Question 8

Regression models of ________ data focus on predicting the future.

Accepted Answer

A) missing 
B) time-series 
C) panel 
D) cross-sectional 
A) missing 
B) time-series 
C) panel 
D) cross-sectional

Question 9

Use the data given below to answer the following question(s).
Following is an extract from the database of a construction company.The table shows the height of walls in feet and the cost of raising them.The estimated simple linear regression equation is given as Ŷ = b0 + b1X.(Hint: Use Excel functions).
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Height } \
\text { (ft) }
\end{array} & \text { Cost (\$) } \
\hline 4 & 670 \
\hline 3 & 430 \
\hline 7 & 810 \
\hline 9 & 1100 \
\hline 6 & 790 \
\hline 8 & 880 \
\hline 5 & 760 \
\hline 11 & 1200 \
\hline
\end{array}$$
-While testing hypotheses for regression coefficients, the t-test for the slope is expressed as:

Accepted Answer

A) t = $\frac { b 1 - 0 } { \text { standard error } }$ 
B) t = $\frac{b_{1}-0}{b_{0}+b_{1}}$ 
C) t = $\frac{b_{1}}{b_{0}-b_{1}}$ 
D) t = $\frac { \text { (standard error) } ^ { 2 } } { b _ { 0 } - b _ { 1 } }$ 
A) t = $\frac { b 1 - 0 } { \text { standard error } }$ 
B) t = $\frac{b_{1}-0}{b_{0}+b_{1}}$ 
C) t = $\frac{b_{1}}{b_{0}-b_{1}}$ 
D) t = $\frac { \text { (standard error) } ^ { 2 } } { b _ { 0 } - b _ { 1 } }$

Question 10

Use the data given below to answer the following question(s).
Following is an extract from a firm's database detailing the number of hours spent on the job by employees and their corresponding pay.(Note: Assume a level of significance of 0.05 wherever necessary.)
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Hours spent } \
\text { on the job }
\end{array} & \text { Salary (\$) } \
\hline 4 & 340 \
\hline 12 & 850 \
\hline 7 & 570 \
\hline 5 & 470 \
\hline 11 & 820 \
\hline 8 & 610 \
\hline 9 & 630 \
\hline 13 & 900 \
\hline 10 & 800 \
\hline 6 & 480 \
\hline
\end{array}$$
-Interpret residual output.

Accepted Answer

From the data, the first observation has

Question 11

Use the data given below to answer the following question(s).
Following is an extract from a firm's database detailing the number of hours spent on the job by employees and their corresponding pay.(Note: Assume a level of significance of 0.05 wherever necessary.)
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Hours spent } \
\text { on the job }
\end{array} & \text { Salary (\$) } \
\hline 4 & 340 \
\hline 12 & 850 \
\hline 7 & 570 \
\hline 5 & 470 \
\hline 11 & 820 \
\hline 8 & 610 \
\hline 9 & 630 \
\hline 13 & 900 \
\hline 10 & 800 \
\hline 6 & 480 \
\hline
\end{array}$$
-Briefly explain the assumptions on which the statistical hypothesis tests associated with regression analysis are predicated.

Accepted Answer

The statistical hypothesis tests associa

Question 12

Use the data given below to answer the following question(s).
Following is an extract from the database of a construction company.The table shows the height of walls in feet and the cost of raising them.The estimated simple linear regression equation is given as Ŷ = b0 + b1X.(Hint: Use Excel functions).
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Height } \
\text { (ft) }
\end{array} & \text { Cost (\$) } \
\hline 4 & 670 \
\hline 3 & 430 \
\hline 7 & 810 \
\hline 9 & 1100 \
\hline 6 & 790 \
\hline 8 & 880 \
\hline 5 & 760 \
\hline 11 & 1200 \
\hline
\end{array}$$
-Which of the following is true about Excel outputs Multiple R?

Accepted Answer

A) It is often referred to as the coefficient of determination. 
B) A value of 0 indicates positive correlation. 
C) A negative slope of the regression line denotes a positive Multiple R. 
D) It is another name for the sample correlation coefficient, r. 
A) It is often referred to as the coefficient of determination. 
B) A value of 0 indicates positive correlation. 
C) A negative slope of the regression line denotes a positive Multiple R. 
D) It is another name for the sample correlation coefficient, r.

Question 13

The following table exhibits the age of antique furniture and the corresponding prices.Use the table to answer the following question(s).(Hint: Use scatter diagram and the Excel Trendline tool where necessary).
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Number } \
\text { of years }
\end{array} & \begin{array} { l } 
\text { Value } \
( \$ )
\end{array} \
\hline 78 & 930 \
\hline 91 & 1010 \
\hline 83 & 970 \
\hline 159 & 1950 \
\hline 134 & 1610 \
\hline 210 & 2880 \
\hline 88 & 980 \
\hline 178 & 2010 \
\hline 124 & 1370 \
\hline 72 & 900 \
\hline
\end{array}$$
-What is the expected value for a 90 year-old piece of furniture?

Accepted Answer

A) $1002.45 
B) $997.98 
C) $934.56 
D) $1033.21 
A) $1002.45 
B) $997.98 
C) $934.56 
D) $1033.21

Question 14

Categorical variables that have been coded are called ________.

Accepted Answer

A) limited dependent variables 
B) dummy variables 
C) instrumental variables 
D) observable variables 
A) limited dependent variables 
B) dummy variables 
C) instrumental variables 
D) observable variables

Question 15

Use the data given below to answer the following question(s).
Following is an extract from a firm's database detailing the number of hours spent on the job by employees and their corresponding pay.(Note: Assume a level of significance of 0.05 wherever necessary.)
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Hours spent } \
\text { on the job }
\end{array} & \text { Salary (\$) } \
\hline 4 & 340 \
\hline 12 & 850 \
\hline 7 & 570 \
\hline 5 & 470 \
\hline 11 & 820 \
\hline 8 & 610 \
\hline 9 & 630 \
\hline 13 & 900 \
\hline 10 & 800 \
\hline 6 & 480 \
\hline
\end{array}$$
-Construct a scatter diagram and use the Excel Trendline tool to find the best-fitting simple linear regression model.

Accepted Answer

The answer of Use the data given below to answer...

Question 16

Use the data given below to answer the following question(s).
Following is an extract from the database of a construction company.The table shows the height of walls in feet and the cost of raising them.The estimated simple linear regression equation is given as Ŷ = b0 + b1X.(Hint: Use Excel functions).
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Height } \
\text { (ft) }
\end{array} & \text { Cost (\$) } \
\hline 4 & 670 \
\hline 3 & 430 \
\hline 7 & 810 \
\hline 9 & 1100 \
\hline 6 & 790 \
\hline 8 & 880 \
\hline 5 & 760 \
\hline 11 & 1200 \
\hline
\end{array}$$
-Which of the following Excel functions is applied to test for significance of regression?

Accepted Answer

A) COVAR 
B) ANOVA 
C) SINH 
D) TREND 
A) COVAR 
B) ANOVA 
C) SINH 
D) TREND

Question 17

________ provide information about the unknown values of the true regression coefficients, accounting for sampling error.

Accepted Answer

A) Standard errors 
B) Confidence intervals 
C) Adjusted R Squares 
D) P-values 
A) Standard errors 
B) Confidence intervals 
C) Adjusted R Squares 
D) P-values

Question 18

The following table exhibits the age of antique furniture and the corresponding prices.Use the table to answer the following question(s).(Hint: Use scatter diagram and the Excel Trendline tool where necessary).
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Number } \
\text { of years }
\end{array} & \begin{array} { l } 
\text { Value } \
( \$ )
\end{array} \
\hline 78 & 930 \
\hline 91 & 1010 \
\hline 83 & 970 \
\hline 159 & 1950 \
\hline 134 & 1610 \
\hline 210 & 2880 \
\hline 88 & 980 \
\hline 178 & 2010 \
\hline 124 & 1370 \
\hline 72 & 900 \
\hline
\end{array}$$
-For an independent variable Y, the error associated with the iᵗʰ observation is:

Accepted Answer

A) eᵢ = Yᵢ - Ŷᵢ 
B) Yᵢ = (eᵢ)² - Ŷᵢ 
C)  (Ŷᵢ)² eᵢ = Yᵢ 
D) eᵢ = (Yᵢ + Ŷᵢ)² 
A) eᵢ = Yᵢ - Ŷᵢ 
B) Yᵢ = (eᵢ)² - Ŷᵢ 
C)  (Ŷᵢ)² eᵢ = Yᵢ 
D) eᵢ = (Yᵢ + Ŷᵢ)²

Question 19

Use the data given below to answer the following question(s).
Following is an extract from a firm's database detailing the number of hours spent on the job by employees and their corresponding pay.(Note: Assume a level of significance of 0.05 wherever necessary.)
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Hours spent } \
\text { on the job }
\end{array} & \text { Salary (\$) } \
\hline 4 & 340 \
\hline 12 & 850 \
\hline 7 & 570 \
\hline 5 & 470 \
\hline 11 & 820 \
\hline 8 & 610 \
\hline 9 & 630 \
\hline 13 & 900 \
\hline 10 & 800 \
\hline 6 & 480 \
\hline
\end{array}$$
-While conducting regression analysis, how is constructing a normal probability plot useful?

Accepted Answer

While conducting regressions analysis us

Question 20

Use the data given below to answer the following question(s).
Following is an extract from a firm's database detailing the number of hours spent on the job by employees and their corresponding pay.(Note: Assume a level of significance of 0.05 wherever necessary.)
 $$\begin{array} { | r | r | } 
\hline \begin{array} { l } 
\text { Hours spent } \
\text { on the job }
\end{array} & \text { Salary (\$) } \
\hline 4 & 340 \
\hline 12 & 850 \
\hline 7 & 570 \
\hline 5 & 470 \
\hline 11 & 820 \
\hline 8 & 610 \
\hline 9 & 630 \
\hline 13 & 900 \
\hline 10 & 800 \
\hline 6 & 480 \
\hline
\end{array}$$
-Creating a scatter chart with an added trendline is visually superior to the scatter chart generated by line fit plots.

Accepted Answer

A) True 
 B)False

Which of the following helps in evaluation of autocorrelation?

In multiple regression, R Square is referred to as the:

________ means that the variation about the regression line is constant for all values of the independent variable.

When a scatter chart of data shows a nonlinear relationship, the nonlinear model can be expressed as:

Regression models of ________ data focus on predicting the future.

Categorical variables that have been coded are called ________.

________ provide information about the unknown values of the true regression coefficients, accounting for sampling error.

Introduction to Business Analytics

Analytics on Spreadsheets

Visualizing and Exploring Data

Descriptive Statistical Measures

Probability Distributions and Data Modeling

Sampling and Estimation

Statistical Inference

Predictive Modeling and Analysis

Forecasting Techniques

Simulation and Risk Analysis

Introduction to Data Mining

Linear Optimization

Applications of Linear Optimization

Integer Optimization

Nonlinear and Non-Smooth Optimization

Optimization Models with Uncertainty

Decision Analysis

Filters

Exam 9: Regression Analysis

Which of the following helps in evaluation of autocorrelation?

In multiple regression, R Square is referred to as the:

________ means that the variation about the regression line is constant for all values of the independent variable.

When a scatter chart of data shows a nonlinear relationship, the nonlinear model can be expressed as:

Regression models of ________ data focus on predicting the future.

Categorical variables that have been coded are called ________.

________ provide information about the unknown values of the true regression coefficients, accounting for sampling error.

Introduction to Business Analytics

Analytics on Spreadsheets

Visualizing and Exploring Data

Descriptive Statistical Measures

Probability Distributions and Data Modeling

Sampling and Estimation

Statistical Inference

Predictive Modeling and Analysis

Forecasting Techniques

Simulation and Risk Analysis

Introduction to Data Mining

Linear Optimization

Applications of Linear Optimization

Integer Optimization

Nonlinear and Non-Smooth Optimization

Optimization Models with Uncertainty

Decision Analysis

Filters