Mod 3 Practice KEY
True/False
1. __True__The dependent variable is the variable that is being described,
predicted, or controlled.
2. ____True ____A simple linear regression model is an equation that describes
the straight-line relationship between a dependent variable and an
independent variable.
3.___ True _____The residual is the difference between the observed value
of the dependent variable and the predicted value of the dependent
variable.
4. ___False_____When using simple linear regression analysis, if there is a
strong correlation between the independent and dependent variable, then we
can conclude that an increase in the value of the independent variable causes
an increase in the value of the dependent variable.
5.__ True ___In a simple linear regression model, the correlation coefficient
not only indicates the strength of the relationship between independent and
dependent variable, but also shows whether the relationship is positive or
negative.
6.____True _ If r = -1, then we can conclude that there is a perfect
relationship between X and Y.
7.___ True _____ The slope of the simple linear regression equation
represents the average change in the value of the dependent variable per
unit change in the independent variable (X).
8.__ False __The least squares simple linear regression line minimizes the sum
of the vertical deviations between the line and the data points.
9._ False The notation Yˆ refers to the average value of the dependent
variable Y.
10. ____ False _A significant positive correlation between X and Y implies that
changes in X cause Y to change.
11. __True _ The estimated simple linear regression equation minimizes the
sum of the squared deviations between each value of Y and the line.
Multiple Choice
12. In a simple linear regression analysis, the correlation coefficient ( r ) and the
slope (m) _____ have the same sign.
A) always
B) sometimes
C) never
13. ________measures the strength of the linear relationship between the
dependent and the independent variable.
A) Correlation coefficient
B) Distance value
C) Y Intercept
D) Residual
14. ________The least squares regression line minimizes the sum of the
A) Differences between actual and predicted Y values
B) Absolute deviations between actual and predicted Y values
C) Absolute deviations between actual and predicted X values
D) Squared differences between actual and predicted Y values
E) Squared differences between actual and predicted X values
15. In a simple linear regression analysis the quantity that gives the amount by
which Y (dependent variable) changes for a unit change in X (independent variable)
is called the
A) Coefficient of determination
B) Slope of the regression line
C) Y intercept of the regression line
D) Correlation coefficient
E) Standard error
16. The correlation coefficient may assume any value between
A) 0 and 1
B) - and 
C) 0 and 8
D) -1 and 1
E) -1 and 0
17. In simple regression analysis, if the correlation coefficient is a positive value,
then
A) The Y intercept must also be a positive value.
B) The coefficient of determination can be either positive or negative, depending
on the value of the slope.
C) The least squares regression equation could either have a positive or a negative
slope.
D) The slope of the regression line must also be positive.
E) The standard error of estimate can either have a positive or a negative value.
18. The strength of the relationship between two quantitative variables can be
measured by the:
A) slope of a simple linear regression equation
B) Y intercept of the simple linear regression equation
C) coefficient of correlation
19. After plotting the data point s on a scatter diagram, we have the relationship
to be falling to the right between the independent variable (X) and the dependent
variable (Y). Therefore, we can expect both the sample _____ and the sample
_____________ to be negative values.
A) Intercept, slope
B) Slope, SSE
C) Intercept, correlation coefficient
D) Slope, correlation coefficient
E) Slope, standard error of estimate
Fill-in-the-Blank
20. While the range for r2 is between 0 and 1, the range for r is between
-1 and 1
21. The __y-intercept___ of the simple linear regression model is the value of y
when the mean value of x is zero.
22. The least squares point estimates of the simple linear regression model
minimize the _SSE_.
23. _Linear Regression Analysis__ is a statistical technique in which we use
observed data to relate a dependent variable to one or more predictor
(independent) variables.
24. The simple linear regression model assumes there is a _linear_ relationship
between the dependent variable and the independent variable.
25. In a simple linear regression model, they intercept term is the mean value of y
when x equals ___0__.
26. In a simple linear regression model, the slope term is the change in the mean
value of y associated with a __1___ unit increase in x.
27. A_____Correlation coefficient__ measures the strength of the linear
relationship between a dependent variable (Y) and an independent variable (X). It is
a unitless measure, therefore does not have an interpretative connotation, as does
the coefficient of determination.
28. After plotting the data point s on a scatter diagram, we have observed an
inverse relationship between the independent variable (X) and the dependent
variable (Y). Therefore, we can expect both the sample slope and the sample ___
Correlation coefficient _______ to be a negative value.