1. A data point (observation) that does not fit the trend shown by the remaining data is called a (an)    narrower
2. A least squares regression line    may be used to predict a value of y if the corresponding x value is given
3. A measure of the strength of the relationship between two variables is the    correlation coefficient
4. A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is the   least squares method
5. A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation
   
   y hat = 9 – 3x
   
   The above equation implies that if the price is increased by $1, the demand is expected to    decrease by 3,000 units
6. A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation
   = 9 − 3x
   The above equation implies that if the price is increased by $1, the demand is expected to   decrease by 3,000 units
7. A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation
   
   y hat = 50,000 – 8x
   
   The above equation implies that an    increase of $1 in price is associated with a decrease of $8000 in sales
8. A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation
   
   = 50,000 − 8x    increase of $1 in price is associated with a decrease of $8000 in sales
9. A regression analysis between sales (y in $1000) and advertising (x in dollars) resulted in the following equation
   = 50,000 + 6x
   
   The above equation implies that an    increase of $1 in advertising is associated with an increase of $6,000 in sales
10. A term that means the same as the term “population” in an ANOVA procedure is   Treatment
11. An ANOVA procedure is used for data obtained from five populations. Five samples, each comprised of 20 observations, were taken from the five populations. The numerator and denominator (respectively) degrees of freedom for the critical value of F are   4 and 95
12. An ANOVA procedure is used for data that was obtained from four sample groups each comprised of five observations. The degrees of freedom for the critical value of F are   3 and 16
13. An observation that has a strong effect on the regression results is called a (an)   influential observation
14. Application of the least squares method results in values of the y intercept and the slope that minimizes the sum of the squared deviations between the   observed values of the dependent variable and the predicted values of the dependent variable
15. As the goodness of fit for the estimated regression equation increases   the value of the coefficient of determination increases
16. 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   narrower
17. 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   narrower
18. If a data set has SST = 2,000 and SSE = 800, then the coefficient of determination is   .6
19. 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 this data is     1
20. If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the estimated regression equation    is 16%
21. If the coefficient of correlation is 0.4, the percentage of variation in the dependent variable explained by the estimated regression equation   is 16%
22. If the coefficient of correlation is a negative value, then the coefficient of determination   must be positive
23. If the coefficient of correlation is a positive value, then the slope of the regression line   must also be positive
24. If the coefficient of determination is a positive value, then the regression equation   could have either a positive or a negative slope
25. If the coefficient of determination is a positive value, then the regression equation   could have either a positive or a negative slope
26. If the coefficient of determination is equal to 1, then the coefficient of correlation   can be either -1 or +1
27. If the coefficient of determination is equal to 1, then the coefficient of correlation   can be either -1 or +1
28. If there is a very strong correlation between two variables, then the coefficient of correlation must be    can be either -1 or +1
29. If two variables, x and y, have a strong linear relationship, then   there may or may not be any causal relationship between x and y
30. In a completely randomized experimental design involving five treatments, 13 observations were recorded for each of the five treatments (a total of 65 observations). The following information is provided.
    
    SSTR = 200 (Sum Square Between Treatments)
    SST = 800 (Total Sum Square)   50.00
31. In a regression analysis if r2 = 1, then    SSR = SST
32. In a regression analysis if r2 = 1, then   SSE must be equal to zero
33. In a regression analysis if SSE = 200 and SSR = 300, then the coefficient of determination is  0.6000
34. In a regression analysis if SSE = 500 and SSR = 300, then the coefficient of determination is   .3750
35. In a regression analysis if SST = 4500 and SSE = 1575, then the coefficient of determination is   0.65
36. In a regression analysis, the variable that is being predicted   is the dependent variable
37. In a regression analysis, the variable that is being predicted    is the dependent variable
38. In a residual plot against x that does not suggest we should challenge the assumptions of our regression model, we would expect to see    a horizontal band of points centered near zero
39. In an analysis of variance problem if SST = 120 and SSTR = 80, then SSE is   40
40. In multiple regression analysis,    there can be several independent variables, but only one dependent variable
41. In regression analysis if the dependent variable is measured in dollars, the independent variable   can be any units
42. In regression analysis, the independent variable is    used to predict the dependent variable
43. In regression analysis, the variable that is being predicted is the    dependent variable
44. In regression analysis, which of the following is not a required assumption about the error term ε?    All are required assumptions about the error term
45. In regression and correlation analysis, if SSE and SST are known, then with this information the    coefficient of determination can be computed
46. In simple linear regression analysis, which of the following is not true?    The F test and the t test may or may not yield the same results.
47. In simple linear regression, r2 is the    coefficient of determination
48. In simple linear regression, r2 is the    coefficient of determination
49. It is possible for the coefficient of determination to be    less than one
50. Larger values of r2 imply that the observations are more closely grouped about the   least squares line
51. Larger values of r2 imply that the observations are more closely grouped about the   least squares line
52. Regression analysis is a statistical procedure for developing a mathematical equation that describes how     one dependent and one or more independent variables are related
53. Regression analysis is a statistical procedure for developing a mathematical equation that describes how    one dependent and one or more independent variables are related
54. Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained.
    
    y hat = 80 + 6.2x
    
    Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is   $700,000
55. Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained.
    
    = 80 + 6.2x      $700,000
56. Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.
    
    y hat = 500 + 4x
    
    Based on the above estimated regression line if advertising is $10,000, then the point estimate for sales (in dollars) is    $900,000
57. Regression analysis was applied between sales (in $1000) and advertising (in $100) and the following regression function was obtained.
    
    = 500 + 4x     $900,000
58. simple linear regression EQUATION    y(hat)= Bo + B1x
59. Simple linear regression model    y= Bo + B1x + E
60. SSE can never be       larger than SST
61. The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is the    residual
62. The equation that describes how the dependent variable (y) is related to the independent variable (x) is called     the regression model
63. The interval estimate of the mean value of y for a given value of x is the     confidence interval
64. The least squares criterion is     min
65. The numerical value of the coefficient of determination    can be larger or smaller than the coefficient of correlation
66. The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the    coefficient of determination
67. The required condition for using an ANOVA procedure on data from several populations is that the    Sampled populations have equal variances
68. Which of the following is correct?     SST = SSR + SSE
69. Which of the following is not a required assumption for the analysis of variance?   Populations have equal means.

Other Links:

Statistics Quiz

Networking Quiz

See other websites for quiz:

Check on QUIZLET

Check on CHEGG