1. ____ intercept is the point where the regression line crosses the Y-axis and where X = 0.
Answer
Correct Answer:
Y
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2. Standardized slope coefficient is the slope The slope between the dependent variable and a specific independent variable when all scores are standardized or expressed as ___scores
Answer
Correct Answer:
Z
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3. The amount of change in a dependent variable per unit change in an independent variable is called
Answer
Correct Answer:
Slope
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4. ___ diagram is a visual method used to display a relationship between two interval-ratio variables.
Answer
Correct Answer:
Scatter
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5. Residual sum of squares is sum of squared differences between observed and predicted ____
Answer
Correct Answer:
Y
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6. Regression sum of squares reflects the improvement in the prediction error resulting from using the linear prediction equation, SST (sum of squared total) − SSE (residual sum of squares).
Answer
Correct Answer:
True
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7. A linear prediction model using one or more independent variables to predict the values of a dependent variable is called
Answer
Correct Answer:
Regression
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8. Pearsons multiple correlation coefficient is the measure of the ___relationship between the independent variable and the combined effect of two or more independent variables.
Answer
Correct Answer:
Linear
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9. The square root of r2; it is a measure of association for interval-ratio variables, reflecting the strength and direction of the linear association between two interval-ratio variables is pearson correlation Coefficient
Answer
Correct Answer:
True
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10. The amount of change in Y for a unit change in a specific independent variable while controlling for the other independent variable(s) is ___ slopes
Answer
Correct Answer:
Partial
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11. _____ regression model that examines the effects of several independent variables on the values of one dependent variable.
Answer
Correct Answer:
Multiple
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12. Multiple coefficient of determination is measure that reflects the proportion of the total variation in the dependent variable that is explained jointly by two or more independent variables.
Answer
Correct Answer:
True
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13. ____ square residual is an average computed by dividing the residual sum of squares (SSE) by its corresponding degrees of freedom.
Answer
Correct Answer:
Mean
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14. Mean square ____ is an average computed by dividing the regression sum of squares (SSR) by its corresponding degrees of freedom.
Answer
Correct Answer:
Regression
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15. ___ relationship between two interval-ratio variables in which the observations displayed in a scatter diagram can be approximated with a straight line.
Answer
Correct Answer:
Linear
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16. The technique that produces the least squares line is least square method
Answer
Correct Answer:
True
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17. ____ square line is where the residual sum of squares, or Σe2, is at a minimum.
Answer
Correct Answer:
Least
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18. A relationship between two interval-ratio variables in which all the observations (the dots) fall along a straight line is deterministic linear relationship
Answer
Correct Answer:
True
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19. A measure of association used to determine the existence and strength of the relationship between interval-ratio variables is called
Answer
Correct Answer:
Correlation
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20. A PRE measure reflecting the proportional reduction of error that results from using the linear regression is coefficient of determination
Answer
Correct Answer:
True
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21. ____ regression is a regression model that examines the effect of one independent variable on the values of a dependent variable.
Answer
Correct Answer:
Bivariate
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22. In a regression equation, the slope is equal to the ______.
Answer
Correct Answer:
Change in y with a unit change in x
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23. How many independent variables are considered in the following multiple regression equation? ______ = a + b1´1 + b2´2 + b3´3 + b4´4
Answer
Correct Answer:
4
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24. What distinguishes a linear regression equation from a multiple regression equation?
Answer
Correct Answer:
The number of independent variables
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25. The least squares (best fitting) line is one where the ______.
Answer
Correct Answer:
Residual sum of squares is closest to zero
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26. For which of the following values of the coefficient of determination, r2, is a regression model said to best fit the data?
Answer
Correct Answer:
R2 = 1.0
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27. For which of the following values of Pearson’s correlation coefficient, r, is a regression model said to best fit the data?
Answer
Correct Answer:
R = 1.0
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28. ______reflects the proportion of the total variation in the dependent variable explained by the independent variable.
Answer
Correct Answer:
Coefficient of determination
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29. ______ is a linear prediction model using one or more independent variables to predict values of a dependent variable.
Answer
Correct Answer:
Regression
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30. If r = .40, what percent of the variation in the dependent variable is left unexplained by the independent variable?
Answer
Correct Answer:
84.00%
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31. In the linear regression equation, Y = a + b(X), the coefficient, b, is said to represent ______.
Answer
Correct Answer:
The change in y per unit change in x
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32. Pearson’s r is also referred to as the ______.
Answer
Correct Answer:
Product moment correlation coefficient
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33. What is the correct formula for the linear regression equation?
Answer
Correct Answer:
Y = a + b(X)
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34. The coefficient of determination, ______, is a PRE statistic.
Answer
Correct Answer:
R2
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35. If the value of the slope, b, in a linear regression equation is positive, then the value of Pearson’s correlation coefficient, ______, must also be positive.
Answer
Correct Answer:
R
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36. A linear relationship shows the relationship between two ______variables.
Answer
Correct Answer:
Interval–ratio
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