Question 1

If there is perfect negative correlation between two sets of numbers,then ___.

Accepted Answer

A) r = 0 
B) r = -1 
C) r = +1 
D) SSE=1 
E) MSE = 1 
A) r = 0 
B) r = -1 
C) r = +1 
D) SSE=1 
E) MSE = 1

Question 2

Calculate the Pearson product-moment correlation coefficient to determine if there is a correlation between two variables.

Accepted Answer

Correlation is a measure that can be use

Question 3

In the simple regression model,y = 21 − 5x,if the coefficient of determination is 0.81,we can say that the coefficient of correlation between y and x is 0.90.

Accepted Answer

A) True 
 B)False

Question 4

Louis Katz,a cost accountant at Papalote Plastics,Inc.(PPI),is analyzing the manufacturing costs of a moulded plastic telephone handset produced by PPI.Louis's independent variable is production lot size (in 1,000's of units),and his dependent variable is the total cost of the lot (in $100's).Regression analysis of the data yielded the following tables:     Louis's regression model is ___.

Accepted Answer

A) y = -0.358 + 3.996x 
B) y = 0.358 + 3.996x 
C) y = -3.996 + 0.358x 
D) y = 3.996 - 0.358x 
E) y = 3.996 + 0.358x 
A) y = -0.358 + 3.996x 
B) y = 0.358 + 3.996x 
C) y = -3.996 + 0.358x 
D) y = 3.996 - 0.358x 
E) y = 3.996 + 0.358x

Question 5

Louis Katz,a cost accountant at Papalote Plastics,Inc.(PPI),is analyzing the manufacturing costs of a moulded plastic telephone handset produced by PPI.Louis's independent variable is production lot size (in 1,000's of units),and his dependent variable is the total cost of the lot (in $100's).Regression analysis of the data yielded the following tables:     Using F1F1F1S1F1F1F10 = 0.05,Louis should ___.

Accepted Answer

A) increase the sample size 
B) suspend judgment 
C) not reject H0: F1F1F1S1F1F1F101 = 0 
D) reject H0: F1F1F1S1F1F1F101 = 0 
E) do not reject H0: F1F1F1S1F1F1F100 = 0 
A) increase the sample size 
B) suspend judgment 
C) not reject H0: F1F1F1S1F1F1F101 = 0 
D) reject H0: F1F1F1S1F1F1F101 = 0 
E) do not reject H0: F1F1F1S1F1F1F100 = 0

Question 6

For the regression line,y = 21 − 5x,21 is the y intercept of the line.

Accepted Answer

A) True 
 B)False

Question 7

Louis Katz,a cost accountant at Papalote Plastics,Inc.(PPI),is analyzing the manufacturing costs of a moulded plastic telephone handset produced by PPI.Louis's independent variable is production lot size (in 1,000's of units),and his dependent variable is the total cost of the lot (in $100's).Regression analysis of the data yielded the following tables:     Louis's sample size (n)is ___.

Accepted Answer

A) 13 
B) 14 
C) 12 
D) 24 
E) 1 
A) 13 
B) 14 
C) 12 
D) 24 
E) 1

Question 8

From the following scatter plot,we can say that between y and x there is ___.

Accepted Answer

A) perfect positive correlation 
B) virtually no correlation 
C) positive correlation 
D) negative correlation 
E) perfect negative correlation 
A) perfect positive correlation 
B) virtually no correlation 
C) positive correlation 
D) negative correlation 
E) perfect negative correlation

Question 9

In the regression equation,y = 75.65 + 0.50x,the slope is ___.

Accepted Answer

A) 0.50 
B) 75.65 
C) 1.00 
D) 0.00 
E) -0.50 
A) 0.50 
B) 75.65 
C) 1.00 
D) 0.00 
E) -0.50

Question 10

One of the assumptions of simple regression analysis is that the error terms are exponentially distributed.

Accepted Answer

A) True 
 B)False

Question 11

Explain what regression analysis is and the concepts of independent and dependent variable.

Accepted Answer

Simple regression is a mathematical mode

Question 12

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch).The intercept of this model is the ___.

Accepted Answer

A) batch size 
B) unit variable cost 
C) fixed cost 
D) total cost 
E) total variable cost 
A) batch size 
B) unit variable cost 
C) fixed cost 
D) total cost 
E) total variable cost

Question 13

A manager wants to predict the cost (y)of travel for salespeople based on the number of days (x)spent on each sales trip.The following model has been developed: y = $400 + 120x.If a trip took 4 days,the predicted cost of the trip is ___.

Accepted Answer

A) 480 
B) 880 
C) 524 
D) 2080 
E) 1080 
A) 480 
B) 880 
C) 524 
D) 2080 
E) 1080

Question 14

The following residuals plot indicates ___.

Accepted Answer

A) a nonlinear relation 
B) a nonconstant error variance 
C) the simple regression assumptions are met 
D) the sample is biased 
E) the sample is random 
A) a nonlinear relation 
B) a nonconstant error variance 
C) the simple regression assumptions are met 
D) the sample is biased 
E) the sample is random

Question 15

The F value to test the overall significance of a regression model is computed by dividing the sum of squares regression (SSreg)by the sum of squares error (SSerr).

Accepted Answer

A) True 
 B)False

Question 16

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a function of batch size (the number of boards produced in one lot or batch).The dependent variable is ___.

Accepted Answer

A) batch size 
B) unit variable cost 
C) fixed cost 
D) total cost 
E) total variable cost 
A) batch size 
B) unit variable cost 
C) fixed cost 
D) total cost 
E) total variable cost

Question 17

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a function of batch size (the number of boards produced in one lot or batch).The explanatory variable is ___.

Accepted Answer

A) batch size 
B) unit variable cost 
C) fixed cost 
D) total cost 
E) total variable cost 
A) batch size 
B) unit variable cost 
C) fixed cost 
D) total cost 
E) total variable cost

Question 18

The following data is to be used to construct a regression model:   The value of the slope is ___.

Accepted Answer

A) 2.36 
B) 2.16 
C) 0.68 
D) 0.57 
E) 1.37 
A) 2.36 
B) 2.16 
C) 0.68 
D) 0.57 
E) 1.37

Question 19

Consider the following scatter plot and regression line.At x = 17,the residual (error term)is ___.

Accepted Answer

A) positive 
B) zero 
C) negative 
D) imaginary 
E) unknown 
A) positive 
B) zero 
C) negative 
D) imaginary 
E) unknown

Question 20

To determine whether the overall regression model is significant,the F test is used.

Accepted Answer

A) True 
 B)False

If there is perfect negative correlation between two sets of numbers,then ___.

Calculate the Pearson product-moment correlation coefficient to determine if there is a correlation between two variables.

In the simple regression model,y = 21 − 5x,if the coefficient of determination is 0.81,we can say that the coefficient of correlation between y and x is 0.90.

For the regression line,y = 21 − 5x,21 is the y intercept of the line.

From the following scatter plot,we can say that between y and x there is ___.

In the regression equation,y = 75.65 + 0.50x,the slope is ___.

One of the assumptions of simple regression analysis is that the error terms are exponentially distributed.

Explain what regression analysis is and the concepts of independent and dependent variable.

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch).The intercept of this model is the ___.

A manager wants to predict the cost (y)of travel for salespeople based on the number of days (x)spent on each sales trip.The following model has been developed: y = $400 + 120x.If a trip took 4 days,the predicted cost of the trip is ___.

The following residuals plot indicates ___.

The F value to test the overall significance of a regression model is computed by dividing the sum of squares regression (SS_reg)by the sum of squares error (SS_err).

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a function of batch size (the number of boards produced in one lot or batch).The dependent variable is ___.

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a function of batch size (the number of boards produced in one lot or batch).The explanatory variable is ___.

The following data is to be used to construct a regression model: The value of the slope is ___.

Consider the following scatter plot and regression line.At x = 17,the residual (error term)is ___.

To determine whether the overall regression model is significant,the F test is used.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Multiple Regression Analysis

Building Multiple Regression Models

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

Exam 12: Simple Regression Analysis and Correlation

If there is perfect negative correlation between two sets of numbers,then ___.

Calculate the Pearson product-moment correlation coefficient to determine if there is a correlation between two variables.

In the simple regression model,y = 21 − 5x,if the coefficient of determination is 0.81,we can say that the coefficient of correlation between y and x is 0.90.

For the regression line,y = 21 − 5x,21 is the y intercept of the line.

From the following scatter plot,we can say that between y and x there is ___.

In the regression equation,y = 75.65 + 0.50x,the slope is ___.

One of the assumptions of simple regression analysis is that the error terms are exponentially distributed.

Explain what regression analysis is and the concepts of independent and dependent variable.

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch).The intercept of this model is the ___.

A manager wants to predict the cost (y)of travel for salespeople based on the number of days (x)spent on each sales trip.The following model has been developed: y = $400 + 120x.If a trip took 4 days,the predicted cost of the trip is ___.

The following residuals plot indicates ___.

The F value to test the overall significance of a regression model is computed by dividing the sum of squares regression (SSreg)by the sum of squares error (SSerr).

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a function of batch size (the number of boards produced in one lot or batch).The dependent variable is ___.

A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a function of batch size (the number of boards produced in one lot or batch).The explanatory variable is ___.

The following data is to be used to construct a regression model: The value of the slope is ___.

Consider the following scatter plot and regression line.At x = 17,the residual (error term)is ___.

To determine whether the overall regression model is significant,the F test is used.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Multiple Regression Analysis

Building Multiple Regression Models

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

The F value to test the overall significance of a regression model is computed by dividing the sum of squares regression (SS_reg)by the sum of squares error (SS_err).