DATA AND STATISTICS
59.In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is a.0.35 b.0.65 c. 2.85 d.0.45
B
9.The interval estimate of the mean value of y for a given value of x is a.prediction interval estimate b.confidence interval estimate c.average regression d.x versus y correlation interval
B
32.In a regression analysis, the variable that is being predicted a.must have the same units as the variable doing the predicting b.is the independent variable c.is the dependent variable d.usually is denoted by x
C
41.If the coefficient of correlation is -0.4, then the slope of the regression line a.must also be -0.4 b.can be either negative or positive c.must be negative d.must be 0.16
C
97.Refer to Exhibit 14-8. The sum of squares due to error (SSE) is a.-156 b.234 c.1870 d.1974
C
57.If the coefficient of correlation is 0.90, then the coefficient of determination a.is also 0.9 b.is either 0.81 or -0.81 c.can be either negative or positive d.must be 0.81
D
60.Regression analysis was applied between sales (in $10,000) and advertising (in $100) and the following regression function was obtained.= 50 + 8 XBased on the above estimated regression line if advertising is $1,000, then the point estimate for sales (in dollars) is a.$8,050 b.$130 c.$130,000 d.$1,300,000
D
61.If the coefficient of correlation is a positive value, then a.the intercept must also be positive b.the coefficient of determination can be either negative or positive, depending on the value of the slope c.the regression equation could have either a positive or a negative slope d.the slope of the line must be positive
D
75.Refer to Exhibit 14-3. The least squares estimate of b0equals a.1 b.-1 c.-11 d.11
D
8.Shown below is a portion of a computer output for a regression analysis relating Y (dependent variable) and X (independent variable).ANOVAdfSSRegression 1115.064Residual13 82.936TotalCoefficientsStandard ErrorIntercept15.5321.457x-1.1060.261 a.Perform a t test using the p-value approach and determine whether or not Y and X are related. Let = 0.05. b.Using the p-value approach, perform an F test and determine whether or not X and Y are related. c.Compute the coefficient of determination and fully interpret its meaning. Be very specific.
a and b
Data obtained from a nominal scale
can be either numeric or nonnumeric
The process of capturing, storing, and maintaining data is known as a.methods for developing useful decision-making information from large data bases b.keeping data secure so that unauthorized individuals cannot access the data c.computational procedure for data analysis d.computing the average for data
data warehousing
Income is an example of a variable that uses the
ratio scale
The scale of measurement that has an inherent zero value defined is the
ratio scale
Temperature is an example of a variable that uses
the interval scale
The ratio scale of measurement has the properties of
the interval scale
Arithmetic operations are inappropriate for
the nominal scale
1.In a regression analysis, the error term is a random variable with a mean or expected value of a.zero b.one c.any positive value d.any value
A
10.The interval estimate of an individual value of y for a given value of x is a.prediction interval estimate b.confidence interval estimate c.average regression d.x versus y correlation interval
A
101.Refer to Exhibit 14-8. The coefficient of correlation is a.-0.2295 b.0.2295 c.0.0527 d.-0.0572
A
105.Refer to Exhibit 14-9. The sample correlation coefficient equals a.0.8045 b.-0.8045 c.0 d.1
A
106.Refer to Exhibit 14-9. The coefficient of determination equals a.0.6472 b.-0.6472 c.0 d.1
A
107.Refer to Exhibit 14-10. The slope of the regression function is a.-1 b.1.0 c.11 d.0.0
A
109.Refer to Exhibit 14-10. The coefficient of determination is a.0.1905 b.-0.1905 c.0.4364 d.-0.4364
A
111.Refer to Exhibit 14-10. The MSE is a.17 b.8 c.34 d.42
A
13.The value of the coefficient of correlation (R) a.can be equal to the value of the coefficient of determination (R2) b.can never be equal to the value of the coefficient of determination (R2) c.is always smaller than the value of the coefficient of determination d.is always larger than the value of the coefficient of determination
A
15.In regression analysis, which of the following is nota required assumption about the error term ? a.The expected value of the error term is one. b.The variance of the error term is the same for all values of X. c.The values of the error termare independent. d.The error term is normally distributed.
A
19.In regression analysis, the variable that is being predicted is the a.dependent variable b.independent variable c.intervening variable d.is usually x
A
2.The coefficient of determination a.cannot be negative b.is the square root of the coefficient of correlation c.is the same as the coefficient of correlation d.can be negative or positive
A
23.In a regression analysis, the coefficient of determination is 0.4225. The coefficient of correlation in this situation is a.0.65b.0.1785 c.any positive value d.any value
A
29.In a regression analysis, the regression equation is given by y = 12 -6x. If SSE = 510 and SST = 1000, then the coefficient of correlation is a.-0.7 b.+0.7 c.0.49 d.-0.49
A
35.If the coefficient of correlation is a positive value, then theregression equation a.must have a positive slope b.must have a negative slope c.could have either a positive or a negative slope d.must have a positive y intercept
A
37.In regression and correlation analysis, if SSE and SST are known, then with this information the a.coefficient of determination can be computed b.slope of the line can be computed c.Y intercept can be computed d.x intercept can be computed
A
40.SSE can never be a.larger than SST b.smaller than SST c.equal to 1 d.equal to zero
A
44.If two variables, x and y, have a strong linear relationship, then a.there may or may not be any causal relationship between x and y b.x causes y to happen c.y causes x to happen d.None of these alternatives is correct.
A
49.Compared to the confidence interval estimate for a particular value of y (in a linear regression model), the interval estimate for an average value of y will be a.narrower b.wider c.the same d.None of these alternatives is correct.
A
65.Referto Exhibit 14-1. The least squares estimate of the slope is a.1 b.2 c.3 d.4
A
67.Refer to Exhibit 14-1. The coefficient of correlation is a.0.7906 b.-0.7906 c.0.625 d.0.375
A
76.Refer to Exhibit 14-3. The sample correlation coefficient equals a.-0.4364 b.0.4364 c.-0.1905 d.0.1905
A
78.Refer to Exhibit 14-4. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is a.$66,000 b.$5,412 c.$66 d.$17,400
A
84.Refer to Exhibit 14-5. The least squares estimate of the slope is a.1 b.-1 c.0 d.3
A
87.Refer to Exhibit 14-5. The MSE is a.0 b.-1 c.1 d.0.5
A
90.Refer to Exhibit 14-6. The total sum of squares (SST) equals a.36 b.18 c.9 d.1296
A
99.Refer to Exhibit 14-8. The slope of the regression equation is a.-0.667 b.0.667 c.100 d.-100
A
102.Refer to Exhibit 14-9. The least squares estimate of b1equals a.0.923 b.1.991 c.-1.991 d.-0.923
B
113.Refer to Exhibit 14-10. The point estimate of Y when X = -3 is a.11 b.14 c.8 d.0
B
20.The equation that describes how the dependent variable (y) is related to the independent variable (x) is called a.the correlation model b.the regression model c.correlation analysis d.None of these alternatives is correct.
B
21.In regression analysis, the independent variable is a.used to predict other independent variables b.used to predict the dependent variable c.called the intervening variable d.the variable that is being predicted
B
24.In a regression analysis, the coefficient of correlation is 0.16. The coefficient of determination in this situation is a.0.4000 b.0.0256 c.4 d.2.56
B
25.In simple linear regression analysis, which of the following is nottrue? a.The F test and the t test yield the same conclusion. b.The F test and the t test may or may not yield the same conclusion. c.The relationship between X and Y is represented by means of a straight line. d.The value of F = t2.
B
27.In a regression and correlation analysis if r2= 1, then a.SSE must also be equal to one b.SSE must be equal to zero c.SSE can be any positive value d.SSE must be negative
B
30.In a regression analysis if SSE = 200 and SSR = 300, then the coefficient of determination is a.0.6667 b.0.6000 c.0.4000 d.1.5000
B
31.If the coefficient of determination is equal to 1, then the coefficient of correlation a.must also be equal to 1 b.can be either -1 or +1 c.can be any value between -1 to +1 d.must be -1
B
34.The coefficient of correlation a.is the square of the coefficient of determination b.is the square root of the coefficient of determination c.is the same as r-square d.can never be negative
B
43.It is possible for the coefficient of determination to be a.larger than 1 b.less than one c.less than -1 d.None of these alternatives is correct.
B
45.If the coefficient of determination is 0.81, the coefficient of correlation a.is 0.6561 b.could be either + 0.9 or -0.9 c.must be positive d.must be negative
B
47.If all the points of a scatter diagram lie on the least squares regression line, then the coefficient of determination for these variables based on these data is a.0 b.1 c.either 1 or -1, depending upon whether the relationship is positive or negative d.could be any value between -1 and 1
B
53.The coefficient of correlation a.is the square of the coefficient of determination b.is the square root of the coefficient of determination c.is the same as r-square d.can never be negative
B
54.If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the variation in the independent variable a.is 40% b.is 16%. c.is 4% d.can be any positive value
B
62.If the coefficient of determination is 0.9, the percentage of variation in the dependent variable explained by the variation in the independent variable a.is 0.90% b.is 90%. c.is 81% d.0.81%
B
64.Refer to Exhibit 14-1. The least squares estimate of the Y intercept is a.1 b.2 c.3 d.4
B
69.Refer to Exhibit 14-2. The least squares estimate of b1(slope) equals a.1 b.-1 c.6 d.5
B
74.Refer to Exhibit 14-3. The least squares estimate of b1equals a.1 b.-1 c.-11 d.11
B
79.Refer to Exhibit 14-4. The F statistic computed from the above data is a.3 b.45 c.48 d.50
B
82.Refer to Exhibit 14-4. The critical t value for testing the significance of the slope at 95% confidence is a.1.753 b.2.131c.1.746 d.2.120
B
83.Refer to Exhibit 14-5. The least squares estimate of the Y intercept is a.1 b.0 c.-1 d.3
B
89.Refer to Exhibit 14-6. The y intercept is a.-1.5 b.24 c.0.50 d.-0.707
B
93.Refer to Exhibit 14-7. The least squares estimate of b0(intercept) equals a.-10 b.10 c.0.5 d.-0.5
B
94.Refer to Exhibit 14-7. The sample correlation coefficient equals a.0.3162 b.-0.3162 c.0.10 d.-0.10
B
100.Refer to Exhibit 14-8. The Y intercept is a.-0.667 b.0.667 c.100d.-100
C
112.Refer to Exhibit 14-10. The point estimate of Y when X = 3 is a.11 b.14 c.8 d.0
C
12.If only MSE is known, you can compute the a.r square b.coefficient of determination c.standard error d.all of these alternatives are correct
C
17.Regression analysis is a statistical procedure for developing a mathematical equation that describes how a.one independent and one or more dependent variables are related b.several independent and several dependent variables are related c.one dependent and one or more independent variables are related d.None of these alternatives is correct.
C
22.Larger values of r2imply that the observations are more closely grouped about the a.average value of the independent variables b.average value of the dependent variable c.least squares line d.origin
C
3.If the coefficient of determination is a positive value, then the coefficient of correlation a.must also be positive b.must be zero c.can be either negative or positive d.must be larger than 1
C
55.In regression analysis if the dependent variable is measured in dollars, the independent variable a.must also be in dollars b.must be in some units of currency c.can be any units d.cannot be in dollars
C
6.The model developed from sample data that has the form of is known as a.regression equation b.correlation equation c.estimated regression equation d.regression model
C
66.Refer to Exhibit 14-1. The coefficient of determination is a.0.7096 b.-0.7906 c.0.625 d.0.375
C
70.Refer to Exhibit 14-2. The least squares estimate of b0(intercept)equals a.1 b.-1 c.6 d.5
C
71.Refer to Exhibit 14-2. The point estimate of y when x = 10 is a.-10 b.10 c.-4 d.4
C
72.Refer to Exhibit 14-2. The sample correlation coefficient equals a.0 b.+1 c.-1 d.-0.5
C
8.In regression analysis, the unbiased estimate of the variance is a.coefficient of correlation b.coefficient of determination c.mean square error d.slope of the regression equation
C
81.Refer to Exhibit 14-4. The t statistic fortesting the significance of the slope is a.1.80 b.1.96 c.6.708 d.0.555
C
91.Refer to Exhibit 14-6. The coefficient of determination (r2) equals a.0.7071 b.-0.7071 c.0.5 d.-0.5
C
95.Refer to Exhibit 14-7. The coefficient of determination equals a.0.3162 b.-0.3162 c.0.10 d.-0.10
C
104.Refer to Exhibit 14-9. The sum of squares due to regression (SSR) is a.1434 b.505.98 c.50.598 d.928.02
D
11.The standard error is the a.t-statistic squared b.square root of SSE c.square root of SST d.square root of MSE
D
110.Refer to Exhibit 14-10. The coefficient of correlation is a.0.1905 b.-0.1905 c.0.4364 d.-0.4364
D
16.A regression analysis between sales (Y in $1000) and advertising (X in dollars) resulted in the following equation= 30,000 + 4 XThe above equation implies that an a.increase of $4 in advertising is associated with an increase of $4,000 in sales b.increase of $1 in advertising is associated with an increase of $4 in sales c.increase of $1 in advertising is associated with an increase of $34,000 in sales d.increase of $1 in advertising is associated with an increase of $4,000 in sales
D
18.In a simple regression analysis (where Y is a dependent and X an independent variable), if the Y intercept is positive, then a.there is a positive correlation between X and Y b.if X is increased, Y must also increase c.if Y is increased, X must also increase d.None of these alternatives is correct.
D
28.In a regression and correlation analysis if r2= 1, then a.SSE = SST b.SSE = 1 c.SSR = SSE d.SSR = SST
D
36.If the coefficient of correlation is 0.8, the percentage of variation in the dependent variable explained by the variation in the independent variable is a.0.80% b.80% c.0.64% d.64%
D
38.In regressionanalysis, if the independent variable is measured in pounds, the dependent variable a.must also be in pounds b.must be in some unit of weight c.cannot be in pounds d.can be any units
D
4.In regression analysis, the model in the form is called a.regression equation b.correlation equation c.estimated regression equation d.regression model
D
42.If the coefficient of correlation is a negative value, then the coefficient of determination a.must also be negative b.must be zero c.can be either negative or positive d.must be positive
D
48.If a data set has SSR = 400 and SSE = 100, then the coefficient of determination is a.0.10 b.0.25 c.0.40 d.0.80
D
50.A regression analysis between sales (in $1000) and price(in dollars) resulted in the following equation= 60 -8XThe above equation implies that an a.increase of $1 in price is associated with a decrease of $8 in sales b.increase of $8 in price is associated with an decrease of $52,000 in sales c.increase of $1 in price is associated with a decrease of $52 in sales d.increase of $1 in price is associated with a decrease of $8000 in sales
D
51.In a regression analysis if SST = 500 and SSE = 300, then the coefficient of determination is a.0.20 b.1.67 c.0.60 d.0.40
D
56.If there is a very strong correlation between two variables then the coefficient of determination must be a.much larger than 1, if the correlation is positive b.much smaller than -1, if the correlation is negative c.any value larger than 1 d.None of these alternatives is correct.
D
77.Refer to Exhibit 14-3. The coefficient of determination equals a.-0.4364 b.0.4364 c.-0.1905 d.0.1905
D
80.Refer to Exhibit 14-4. To perform an F test, the p-value is a.less than .01 b.between .01 and .025 c.between .025 and .05 d.between .05 and 0.1
D
85.Refer to Exhibit 14-5. The coefficient of correlation is a.0 b.-1 c.0.5 d.1
D
86.Refer to Exhibit 14-5. The coefficient of determination is a.0 b.-1 c.0.5 d.1
D
88.Refer to Exhibit 14-6. The slope of the regression equation is a.18 b.24 c.0.707 d.-1.5
D
96.Refer to Exhibit 14-8. The total sum of squares (SST) is a.-156 b.234 c.1870 d.1974
D
98.Refer to Exhibit 14-8. The mean square error (MSE) is a.1870 b.13 c.1974 d.935
D
Arithmetic operations are appropriate for
None of these alternatives is correct
The interval scale of measurement has the properties of the
None of these alternatives is correct
The nominal scale of measurement has the properties of the
None of these alternatives is correct.
10.Shown below is a portion of a computer output for a regression analysis relating Y (demand) and X (unit price).ANOVAdfSSRegression 15048.818Residual463132.661Total478181.479CoefficientsStandard ErrorIntercept80.3903.102X-2.1370.248 a.Perform a t test and determine whether or not demand and unit price are related. Let = 0.05. b.Perform an F test and determine whether or not demand and unit price are related. Let = 0.05. c.Compute the coefficient of determination and fully interpret its meaning. Be very specific. d.Compute the coefficient of correlation and explain the relationship between demand and unit price.
a and b
Methods for developing useful decision-making information from large data bases is known as a.data manipulation b.data monitoring c.data warehousing d.category analysis
data mining
The subject of data mining deals with a.ordinal scale b.nominal scale c.ratio scale d.interval scale
methods for developing useful decision-making information from large data bases
In a questionnaire, respondents are asked to mark their gender as male or female. Gender is an example of the
nominal scale
The ordinal scale of measurement has the properties of the
nominal scale
Some hotels ask their guests to rate the hotel's services as excellent, very good, good, and poor. This is an example of the
ordinal scale
The scale of measurement that is used to rank order the observation for a variable is called the
ordinal scale
