Deck 19: Correlation Analysis and Regression Analysis

Question 1

When an understanding of the relationship between X and Y is the motivation behind data analysis, the estimate of the parameter is of primary importance.

Answer 1

True

Question 2

In interpreting parameter coefficients, indicates that if the independent variable X is changed by one unit, the dependent variable Y will change by 11efcb9b_6ea8_cb8d_b057_a37dcce9d7b9_TB7490_00 units.In multiple regression, we add the constraint that the values of all other independent variables remain constant.

Answer 2

True

Question 3

In regression analysis, the dependent variable is sometimes called the predictor variable.

Answer 3

False

Question 4

r² is the square of the correlation between X and Y and also the square of the correlation between Ŷ and Y.

Question 5

A least squares criterion minimizes the squared vertical deviations from the regression line.

Question 6

The model: Y = + X² + e hypothesizes a curvilinear relationship between X and Y.

Question 7

The larger the beta coefficient value, the stronger the effect of that variable upon the dependent variable.

Question 8

Correlation analysis provides a measure of the strength of association between two variables, but tells us nothing about the nature of the relationship between them

Question 9

A regression model can be used to explain, predict and control the dependent variable, on the basis of independent variables.

Question 10

The total variation in Y, the dependent variable, can be expressed as the sum of the explained variance, the unexplained variance, and an unknown error.

Question 11

The unexplained variation in Y is estimated by n Y_i - Ŷ₁)² i=1

Question 12

If a variable that is excluded from the model is correlated with an independent variable in the model, the regression coefficient will reflect the impact of the excluded variable on the dependent variable.

Question 13

When testing the hypothesis that, in fact, = 0, the researcher is actually testing the hypothesis that the independent variable has no linear) effect on the dependent variable.

Question 14

An independent variable which takes a small number 3 or 4) of discrete values is often termed a dummy variable.

Question 15

A regression model can be used to accurately predict the level of a dependent variable, given extreme values of an independent variable.

Question 16

A regression model can accurately predict the level of a dependent variable in a changing market environment.

Question 17

Regression is an analysis of dependence technique since it involves a dependent variable as the focus of analysis.

Question 18

In the expression Ŷ = 7.26 + 28.9 X, the estimated value of = 28.9 and the estimated value of β = 7.26.

Question 19

If the standard deviation of X is approximated by s, then the standard deviation of the mean based on a sample size of n) is s/n.

Question 20

If the parameter is zero, the value of b must also always be zero.

Question 21

If you tested a null hypothesis on problem 7, and accepted it, the probability of Type I error would be a) .95 b) .50 c) .10 d) zero

Question 22

The coefficient of determination r²) measure the ability of the model to predict, and is the ratio of the explained variation to the total variation

Question 23

Snow Belt Airlines weighed the baggage of 100 passengers and found the mean weight to be 34.2 pounds with a standard deviation of 14 pounds.What is the 95% confidence interval for the actual weight of the baggage? Round Z to the nearest whole number) a) 20.0 - 48.2 b) 32.8 - 35.6 c) 31.4 - 37.0 d) 0.0 - 50.0

Question 24

In analysis of variance, the hypothesis that the means are equal will be rejected if a) the total mean square error is significantly greater than either the explained or unexplained mean square error b) the total mean square error is significantly greater than the unexplained c) the mean square error explained is significantly greater than the mean square unexplained d) the mean square error unexplained is significantly greater than the mean square explained

Question 25

The point estimates b₀ and b₁ in a regression analysis, tend to increase the total sum of squares.

Question 26

The degree of linear association between two intervally scaled variables is measured by a) Pearson correlation coefficient b) significance level c) analysis of variance d) β

Question 27

A regression analysis has shown that there is a definite, positive relationship between sales dependent variable) and advertising and sales promotion all units in dollars).The estimated relationship is sales = 3) advertising + 1) sales promotion + 1,500.Based on the given information

A)all marketing resources should be allocated to advertising, if possible.
B)all marketing resources should be allocated to sales promotion, if possible.
C)the allocation between advertising and sales promotion should be split in the ratio 3 to 1 in all circumstances.
D)none of the above.

Question 28

Which of the following data analysis techniques can be termed analysis of dependence techniques?

A)Correlation analysis
B)Regression analysis
C)Multidimensional scaling
D)Cluster analysis

Question 29

Which one of the following is the same as standard deviation of regression coefficient? a) sum of squares of errors b) standard error c) predicted value d) standard error of the estimate

Question 30

Partial correlation coefficient is the measure of association between two variables controlling for the effect of one or more additional variables.

Question 31

Although the least-squares regression line provides a reasonable fit of the data points, there are some deviations in the sample data about the line.

Question 32

Consider the following model: Y = + X +

A)The model involves one dependent and one independent variable.
B)The parameters of the model are Y and X.
C)The parameters of the model are and https://d2lvgg3v3hfg70.cloudfront.net/TB7490/11efcb99_328a_3d73_b057_b9893a205b64_TB7490_00.
D)e represents the error in the model.
E)Which of the following statements is not true?

Question 33

The measures of association represented by r and r² are a) symmetric b) dependent c) asymmetric d) independent

Question 34

To examine the association between two variables after controlling for the other variables the researcher should use a) bivariate correlation b) partial correlation c) product moment correlation d) simple correlation

Question 35

The knowledge of the regression coefficient and the t value can suggest the extent of association an independent variable has on the dependent variable.

Question 36

In the simple linear regression model, Y = + X + e,

A)the errors are assumed to be as likely to occur above the line as below the line.
B)the errors are assumed to be more likely to occur above the line than below it.
C)the errors are assumed to be more likely to occur below the line than above it.
D)it is assumed that the error is larger for larger values of X.

Question 37

The difference between the actual and the predicted values in a regression equation is called residuals.

Question 38

The Pearson correlation coefficient measures the degree to which there is a linear association between two intervally scaled variables.

Question 39

Correlation coefficient implies a causal relationship between variables.

Question 40

Correlation analysis involves measuring the strength of the relationship between two variables.

Question 41

In a scatter diagram, the sample correlation value is 1 if,

A)the points fall along a straight line running from the lower left to the upper right
B)the points are clustered in a pattern sloping from lower left to upper right
C)the points are clustered in a pattern sloping from upper left to lower right
D)the points are clustered in no clear, defined pattern

Question 42

Which of the following is not a property of the product moment correlation coefficient?

A)it is independent of sample size and units of measurement.
B)it is a measure of association between two variables.
C)it always lies between 1 and -1.
D)it implies a causal relationship between two variables.