chapter 5: basic estimation techniques2019/04/12 · intercept 15.48 5.09 3.04 0.0008 x −21.36...

Chapter 4: BASIC ESTIMATION TECHNIQUES © 2016 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in

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Chapter 4: BASIC ESTIMATION TECHNIQUES Multiple Choice

4-1 For the equation Y = a + bX, the objective of regression analysis is to

a. estimate the parameters a and b.

b. estimate the variables Y and X.

c. fit a straight line through the data scatter in such a way that the sum of the squared errors

is minimized.

d. both a and c

Answer: d

Difficulty: 01 Easy

Topic: The Simple Linear Regression Model

AACSB: Reflective Thinking

Blooms: Understand

Learning Objective: 04-01

4-2 In a linear regression equation of the form Y = a + bX, the slope parameter b shows

a. X / Y.

b. Y / X.

c. Y / b.

d. X / b.

e. none of the above

Answer: b

Difficulty: 01 Easy



Blooms: Understand


4-3 In a linear regression equation of the form Y = a + bX, the intercept parameter a shows

a. the value of X when Y is zero.

b. the value of Y when X is zero.

c. the amount that Y changes when X changes by one unit.

d. the amount that X changes when Y changes by one unit.

Answer: b

Difficulty: 01 Easy



Blooms: Remember


4-4 In a regression equation, the ______ captures the effects of factors that might influence the

dependent variable but aren't used as explanatory variables.

a. intercept

b. slope parameter

c. R-square

d. random error term

Answer: d

Difficulty: 01 Easy





Blooms: Understand


4-5 The sample regression line

a. shows the actual (or true) relation between the dependent and independent variables.

b. is used to estimate the population regression line.

c. connects the data points in a sample.

d. is estimated by the population regression line.

e. maximizes the sum of the squared differences between the data points in a sample and the

sample regression line.

Answer: b

Difficulty: 01 Easy



Blooms: Remember


4-6 Which of the following is an example of a time-series data set?

a. amount of labor employed in each factory in the U.S. in 2010.

b. amount of labor employed yearly in a specific factory from 1990 through 2010.

c. average amount of labor employed at specific times of the day at a specific factory in

2010.

d. All of the above are time-series data sets.

Answer: b

Difficulty: 01 Easy



Blooms: Remember


4-7 The method of least squares

a. can be used to estimate the explanatory variables in a linear regression equation.

b. can be used to estimate the slope parameters of a linear equation.

c. minimizes the distance between the population regression line and the sample regression

line.

d. all of the above

Answer: b

Difficulty: 01 Easy

Topic: Fitting a Regression Line


Blooms: Understand


4-8 In a linear regression equation Y = a + bX, the fitted or predicted value of Y is

a. the value of Y obtained by substituting specific values of X into the sample regression

equation.

b. the value of X associated with a particular value of Y.

c. the value of X that the regression equation predicts.

d. the values of the parameters predicted by the estimators.

e. the value of Y associated with a particular value of X in the sample.



Answer: a

Difficulty: 01 Easy



Blooms: Understand


4-9 A parameter estimate is said to be statistically significant if there is sufficient evidence that the

a. sample regression equals the population regression.

b. parameter estimated from the sample equals the true value of the parameter.

c. value of the t-ratio equals the critical value.

d. true value of the parameter does not equal zero.

Answer: d

Difficulty: 02 Medium



Blooms: Understand


4-10 An estimator is unbiased if it produces

a. a parameter from the sample that equals the true parameter.

b. estimates of a parameter that are close to the true parameter.

c. estimates of a parameter that are statistically significant.

d. estimates of a parameter that are on average equal to the true parameter.

e. both b and c

Answer: d

Difficulty: 01 Easy



Blooms: Understand


4-11 The critical value of t is the value that a t-statistic must exceed in order to

a. reject the hypothesis that the true value of a parameter equals zero.

b. accept the hypothesis that the estimated value of parameter equals the true value.

c. reject the hypothesis that the estimated value of the parameter equals the true value.

d. reject the hypothesis that the estimated value of the parameter exceeds the true value.

Answer: a


Topic: Testing For Statistical Significance


Blooms: Understand


4-12 To test whether the overall regression equation is statistically significant one uses

a. the t-statistic.

b. the R 2 -statistic.

c. the F-statistic.

d. the standard error statistic.

Answer: c

Difficulty: 01 Easy

Topic: Evaluation of the Regression Equation




Blooms: Understand


4-13 In the regression model Y = a + bX + cZ , a test of the hypothesis that parameter c equals zero is

a. an F-test.

b. an R 2 -test.

c. a zero-statistic.

d. a t-test.

e. a Z-test.

Answer: d

Difficulty: 01 Easy



Blooms: Understand


4-14 If an analyst believes that more than one explanatory variable explains the variation in the

dependent variable, what model should be used?

a. a simple linear regression model

b. a multiple regression model

c. a nonlinear regression model

d. a log-linear model

Answer: b

Difficulty: 01 Easy

Topic: Multiple Regression


Blooms: Understand


4-15 The linear regression equation, Y = a + bX, was estimated. The following computer printout was

obtained:

DEPENDENT VARIABLE: Y R−SQUARE F−RATIO P−VALUE ON F

OBSERVATIONS: 18 0.3066 7.076 0.0171 VARIABLE

PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 15.48 5.09 3.04 0.0008

X −21.36 8.03 −2.66 0.0171

Given the above information, the parameter estimate of a indicates

a. when X is zero, Y is 5.09.

b. when X is zero, Y is 15.48.

c. when Y is zero, X is –21.36.

d. when Y is zero, X is 8.03.

Answer: b

Difficulty: 01 Easy





Blooms: Understand



obtained:



PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 15.48 5.09 3.04 0.0008

X −21.36 8.03 −2.66 0.0171

Given the above information, the parameter estimate of b indicates

a. X increases by 8.03 units when Y increases by one unit.

b. X decreases by 21.36 units when Y increases by one unit.

c. Y decreases by 2.66 units when X increases by one unit.

d. a 10-unit decrease in X results in a 213.6 unit increase in Y.

Answer: d




Blooms: Understand



obtained:



PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 15.48 5.09 3.04 0.0008

X −21.36 8.03 −2.66 0.0171

Given the above information, what is the critical value of t at the 1% level of significance?

a. 1.746

b. 2.120

c. 2.878

d. 2.921



Answer: d

Difficulty: 03 Hard



Blooms: Understand



obtained:



PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 15.48 5.09 3.04 0.0008

X −21.36 8.03 −2.66 0.0171

Given the above information, which of the following statements is correct at the 1% level of

significance?

a. Both a and b are statistically significant.

b. Neither a nor b is statistically significant.

c. a is statistically significant, but b is not.

d. b is statistically significant, but a is not.

Answer: c




Blooms: Understand



obtained:



PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 15.48 5.09 3.04 0.0008

X −21.36 8.03 −2.66 0.0171

Given the above information, the value of the R 2 statistic indicates that

a. 0.3066% of the total variation in Y is explained by the regression equation.

b. 0.3066% of the total variation in X is explained by the regression equation.

c. 30.66% of the total variation in Y is explained by the regression equation.

d. 30.66% of the total variation in X is explained by the regression equation.

Answer: c






Blooms: Understand



obtained:



PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 15.48 5.09 3.04 0.0008

X −21.36 8.03 −2.66 0.0171

Given the above information, the exact level of significance of b is

a. 0.171 percent.

b. 1 percent.

c. 1.71 percent.

d. 2.66 percent.

e. 2.921 percent.

Answer: c




Blooms: Understand



obtained:



PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 15.48 5.09 3.04 0.0008

X −21.36 8.03 −2.66 0.0171

Given the above information, if X equals 20, what is the predicted value of Y?

a. 186.42

b. 165.69

c. −186.42

d. −411.72

Answer: d





AACSB: Analytic

Blooms: Apply


4-22 A firm is experiencing theft problems at its warehouse. A consultant to the firm believes that the

dollar loss from theft each week (T ) depends on the number of security guards (G ) and on the

unemployment rate in the county where the warehouse is located (U measured as a percent). In

order to test this hypothesis, the consultant estimated the regression equation T = a + bG + cU and

obtained the following results:

DEPENDENT VARIABLE: T R−SQUARE F−RATIO P−VALUE ON F


PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 5150.43

1740.72 2.96 0.0068

G −480.92 130.66 −3.68 0.0012

U 211.0 75.0 2.81 0.0096

Based on the above information, which of the following is correct at the 1% level of significance? a. The regression equation as a whole is statistically significant because the p-value of F is

smaller than 0.01. b. The estimates of the parameters a, b, and c are all statistically significant because the

absolute values of their t-ratios exceed 2.797. c. The estimates of the parameters a, b, and c are all statistically significant because the p-

values for, a , b and c are all less than 0.01. d. The critical value of t is 2.797. e. all of the above

Answer: e

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply











PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 5150.43

1740.72 2.96 0.0068

G −480.92 130.66 −3.68 0.0012

U 211.0 75.0 2.81 0.0096

Based on the above information, hiring one more guard per week will decrease the losses due to

theft at the warehouse by _________ per week.

a. $5,150

b. $211

c. $130

d. $480.92

Answer: d

Difficulty: 01 Easy


AACSB: Analytic

Blooms: Apply









PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 5150.43

1740.72 2.96 0.0068

G −480.92 130.66 −3.68 0.0012

U 211.0 75.0 2.81 0.0096



Based on the above information, if the firm hires 6 guards and the unemployment rate in the

county is 10% (U = 10), what is the predicted dollar loss to theft per week?

a. $4,375 per week

b. $5,150 per week

c. $8,300 per week

d. $9,955 per week

Answer: a



AACSB: Analytic

Blooms: Apply









PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 5150.43

1740.72 2.96 0.0068

G −480.92 130.66 −3.68 0.0012

U 211.0 75.0 2.81 0.0096

Based on the above information, a one percent increase in the level of unemployment in the

county results in an increase in losses due to theft of __________ more losses per week.

a. $75

b. $211

c. $280

d. $460

Answer: b



AACSB: Analytic

Blooms: Apply


4-26 In the nonlinear function Y = aXbZ

c , the parameter c measures

a. Y /Z.

b. the percent change in Y for a 1 percent change in Z.

c. the elasticity of Y with respect to Z.

d. both a and c

e. both b and c

Answer: e

Difficulty: 03 Hard



Topic: Nonlinear Regression Analysis

AACSB: Analytic

Blooms: Analyze


4-27 Tests for statistical significance must be performed

a. because the TRUE values of the intercept and slope parameters are random variables.

b. because the ESTIMATED values of the intercept and slope parameters are not, in general,

equal to the true values of the intercept and slope parameters.

c. because the computed t-ratios are random variables and may be too large to provide

evidence that b is not equal to zero.

d. in order to determine whether or not the parameter estimates are far enough away from

zero to conclude that the true parameter values are not equal to zero.

e. both b and d

Answer: e

Difficulty: 03 Hard



Blooms: Understand


4-28 If the p-value is 10%, then the

a. level of significance is 10%.

b. level of confidence is 90%.

c. probability of a Type I error is 90%.

d. both a and b

e. null hypothesis should not be rejected if the level of significance is 5%

Answer: e




Blooms: Understand


4-29 Suppose you are testing the statistical significance (at the 5% significance level) of a parameter

estimate from the regression equation:

Y = a + bR + cS + dW

which is estimated using a time-series sample containing monthly observations over a 30−month

time period. The critical value of the appropriate test statistic is

a. tcritical = 2.042.

b. tcritical = 2.056.

c. Fcritical = 4.22.

d. Fcritical = 7.76.

Answer: b

Difficulty: 03 Hard



Blooms: Understand




4-30 Suppose you are testing the statistical significance (at the 1% significance level) of a parameter

estimate from the regression model:

M = a + bR + cI

which is estimated using a cross−section data set on 22 firms. The critical value of the appropriate

test statistic is

a. tcritical = 2.861.

b. tcritical = −2.845.

c. tcritical = 2.845.

d. Fcritical = 5.93.

e. Fcritical = 19.44.

Answer: a

Difficulty: 03 Hard



Blooms: Understand


4-31 Refer to the following computer output from estimating the parameters of the nonlinear model

Y = aRbS cT d

The computer output from the regression analysis is:

DEPENDENT VARIABLE: LNY R−SQUARE F−RATIO P−VALUE ON F


PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT −0.6931 0.32 −2.17 0.0390

LNR 4.66 1.36 3.43 0.0019

LNS −0.44 0.24 −1.83 0.0774

LNT 8.28 4.6 1.80 0.0826

Based on the info above, the nonlinear relation can be transformed into the following linear

regression model:

a. Y = ln(aRbS cT d )

b. lnY = ln(aRbScT d )

c. lnY = lna × ln R × lnS × lnT d. lnY = lna + bln R + c lnS + d lnT Answer: d

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply





Y = aRbS cT d




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT −0.6931 0.32 −2.17 0.0390

LNR 4.66 1.36 3.43 0.0019

LNS −0.44 0.24 −1.83 0.0774

LNT 8.28 4.6 1.80 0.0826

Based on the info above, the estimated value of a is

a. −0 .6931

b. 0.50

c. −3.67

d. 2.66

Answer: b

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



Y = aRbS cT d




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT −0.6931 0.32 −2.17 0.0390

LNR 4.66 1.36 3.43 0.0019

LNS −0.44 0.24 −1.83 0.0774

LNT 8.28 4.6 1.80 0.0826

Based on the info above, which of the parameter estimates are statistically significant at the 90%

level of confidence? a. All the parameter estimates are statistically significant. b. All parameter estimates except a and b are statistically significant. c. a is not statistically significant, but all the rest of the parameter estimates are significant. d. c is not statistically significant, but all the rest of the parameter estimates are significant.

Answer: a



Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



Y = aRbS cT d




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT −0.6931 0.32 −2.17 0.0390

LNR 4.66 1.36 3.43 0.0019

LNS −0.44 0.24 −1.83 0.0774

LNT 8.28 4.6 1.80 0.0826

Based on the info above, if R = 1, S = 2, and T = 3, what value do you expect Y will have?

a. 143

b. 1,345

c. 3,289

d. 6,578

e. −4 ,559

Answer: c

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



Y = aRbS cT d




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT −0.6931 0.32 −2.17 0.0390

LNR 4.66 1.36 3.43 0.0019

LNS −0.44 0.24 −1.83 0.0774

LNT 8.28 4.6 1.80 0.0826



Based on the info above, if R decreases by 10% (all other things constant), Y will

a. increase by 4.66%.

b. increase by 46.6%.

c. decrease by 4.66%.

d. decrease by 46.6%.

Answer: d

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Analyze



Y = aRbS cT d




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT −0.6931 0.32 −2.17 0.0390

LNR 4.66 1.36 3.43 0.0019

LNS −0.44 0.24 −1.83 0.0774

LNT 8.28 4.6 1.80 0.0826

Based on the info above, if S increases by 8% (all other things constant), Y will

a. decrease by 3.52%.

b. decrease by 0.44%.

c. decrease by 4.4%.

d. increase by 0.44%.

Answer: a

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Analyze




4-37 Refer to the following nonlinear model which relates W to P, Q, and R:

W = aPbQc Rd

The computer output form the regression analysis is:

DEPENDENT VARIABLE: LNW R−SQUARE F−RATIO P−VALUE ON F


PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010

Based on the info above, the nonlinear relation can be transformed into the following linear

regression model:

a. W = ln(aPbQcRd )

b. lnW = ln(aPbQc Rd )

c. lnW = ln a × ln P × lnQ × ln R

d. lnW = ln a + bln P + c lnQ + d ln R

Answer: d

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



W = aPbQc Rd




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010



Based on the info above, which of the parameter estimates are statistically significant at the 5%

level of significance?

a. All the parameter estimates are statistically significant.

b. All parameter estimates except a and bare statistically significant.

c. a is not statistically significant, but all the rest of the parameter estimates are significant.

d. c is not statistically significant, but all the rest of the parameter estimates are significant.

Answer: a

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



W = aPbQc Rd




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010

Based on the info above, the estimated value of a is

a. 0.916

b. 12.182

c. 2.50

d. 2.66

Answer: b

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



W = aPbQc Rd






PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010

Based on the info above, if P = 0.5, Q = 1.5, and R = 0.8, what value do you expect W will have?

a. 16,712

b. 243,200

c. 1,345

d. 3,289

Answer: b

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



W = aPbQc Rd




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010

Based on the info above, if R decreases by 12% (all other things constant), W will

a. decrease by 72%.

b. decrease by 6%.

c. increase by 6%.

d. increase by 72%.

Answer: d

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply





W = aPbQc Rd




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010

Based on the info above, if Q increases by 8% (all other things constant), W will

a. decrease by 99.2%.

b. decrease by 12.5%.

c. increase by 0.99%.

d. increase by 99.2%.

Answer: d

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



W = aPbQc Rd




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010

Based on the info above, if P = Q = R = 1, what value do you expect W will have?



a. 0

b. 1

c. 12.182

d. 2.50

Answer: c

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply



W = aPbQc Rd




PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 2.50 0.45 5.56 0.0001

LNP −5.10 1.75 −2.91 0.0113

LNQ 12.4 3.2 3.88 0.0017

LNR −6.00 1.5 −4.00 0.0010

Based on the info above, the value of R 2 tells us that

a. 0.9023% of the total variation in ln W is explained by the regression equation.

b. 90.23% of the total variation in ln W is explained by the regression equation.

c. 0.9023% of the total variation in P, W, and R is explained by the regression equation.

d. 0.9023% of the total variation in ln P, ln Q, and ln R is explained by the regression

equation.

Answer: b

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Apply


4-45 In a multiple regression model, the coefficients on the independent variables measure

a. the percent of the variation in the dependent variable explained by a change in that

independent variable, all other influences held constant.

b. the change in the dependent variable from a one-unit change in that independent variable,

all other influences held constant.

c. the change in that independent variable from a one-unit change in the dependent variable,

all other influences held constant.

d. the change in the dependent variable explained by the random error, all other influences

held constant.

Answer: b






Blooms: Understand


4-46 The quadratic equation Y = a + bX +cX 2 can be estimated using linear regression by estimating

a. Y = a + bX + ZX where Z = c2

b. Y = a + ZX where Z = (b + c)

c. Y = a + bZ where Z = X 2

d. Y = a + ZX where Z = (b + c)2

e. none of the above will work

Answer: e

Difficulty: 03 Hard


AACSB: Analytic

Blooms: Analyze


4-47 A manager wishes to estimate an average cost equation of the following form:

C = a + bQ + cQ2

where Q is the level of output. Letting Z = Q 2 and using least-squares estimation, the manager

obtains the following computer output:

DEPENDENT VARIABLE: C R−SQUARE F−RATIO P−VALUE ON F


PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 200 38.00 5.26 0.0001

Q −12.00 4.36 −2.75 0.0111

Z 0.50 0.16 3.13 0.0046

Given the above information, which of the parameter estimates are statistically significant at the 1%

significance level?

a. All parameter estimates are statistically significant.

b. All parameter estimates except b are statistically significant.

c. a is not statistically significant, but all the rest of the parameter estimates are significant.

d. c is not statistically significant, but all the rest of the parameter estimates are significant.

Answer: b




Blooms: Understand





C = a + bQ + cQ2





PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 200 38.00 5.26 0.0001

Q −12.00 4.36 −2.75 0.0111

Z 0.50 0.16 3.13 0.0046

Given the above information, the value of R 2 indicates that _______ of the total variation in C is

explained by the regression equation.

a. 0.7679%

b. 76.79%

c. 7.679%

d. 7679%

Answer: b




Blooms: Understand



C = a + bQ + cQ2





PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 200 38.00 5.26 0.0001

Q −12.00 4.36 −2.75 0.0111

Z 0.50 0.16 3.13 0.0046

Given the above information, when output is 40 units, what is average cost?

a. $200

b. $280

c. $360

d. $480

e. $520



Answer: d




Blooms: Understand



C = a + bQ + cQ2





PARAMETER ESTIMATE

STANDARD ERROR

T−RATIO

P−VALUE

INTERCEPT 200 38.00 5.26 0.0001

Q −12.00 4.36 −2.75 0.0111

Z 0.50 0.16 3.13 0.0046

Given the above information, when output is 20 units, what is average cost?

a. $160

b. $200

c. $280

d. $340

e. $360

Answer: a




Blooms: Understand


chapter 5: basic estimation techniques2019/04/12 · intercept 15.48 5.09 3.04 0.0008 x −21.36...

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