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1 | |
The concept of statistical significance is used to measure which of the following aspects of the relationship between variables? |
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| | A) | presence |
| | B) | dispersion |
| | C) | direction |
| | D) | strength of associations |
| | E) | type |
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2 | |
A linear, positive relationship between two variables (x and y) indicates that when: |
|
| | A) | x goes up, y goes down |
| | B) | x goes down, y goes up |
| | C) | x goes up, y stays the same |
| | D) | x goes down, y goes down |
| | E) | None of the above |
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3 | |
A researcher creates a cross-tabulation table of two variables, education (college educated or not) and annual income (above $50,000 or not). She wants to determine if there is any association between the frequency distribution. An appropriate test to determine this is: |
|
| | A) | chi-square test |
| | B) | Pearson correlation coefficient |
| | C) | coefficient of determination |
| | D) | Spearman rank-order correlation coefficient |
| | E) | All of the above |
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4 | |
A visual way to describe the relationship between two variables and to get a sense of the amount of covariation is to draw a: |
|
| | A) | splatter plot |
| | B) | splinter plot |
| | C) | scatter plot |
| | D) | slotted plot |
| | E) | bar plot |
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5 | |
Pearson correlation coefficient can tell a researcher about which aspect of the relationship between two variables? |
|
| | A) | presence |
| | B) | type |
| | C) | direction |
| | D) | strength of association |
| | E) | all of the above |
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6 | |
Based on data obtained from 100 respondents, a researcher determines that the Pearson correlation coefficient between the two variables is -0.6. The coefficient of determination for this relationship is: |
|
| | A) | +0.6 |
| | B) | -60 |
| | C) | -0.006 |
| | D) | 0.36 |
| | E) | impossible to determine without additional information |
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7 | |
A bi-serial correlation coefficient would be appropriate to measure association between which of the following pairs of variables? |
|
| | A) | gender (male/female) and income (open ended question) |
| | B) | age (open ended question) and income (closed ended question, with five response options) |
| | C) | age (open ended question) and income (open ended question) |
| | D) | age (closed ended question, with four options) and income (closed ended question, with five response options) |
| | E) | none of the above |
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8 | |
A simple regression model assumes all of the following EXCEPT: |
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| | A) | the variables of interest are measured on interval or ration scales (except in the case of dummy variable regression) |
| | B) | the variables come from a bivariate normal distribution |
| | C) | there is no association between dependent and independent variables |
| | D) | the error terms are normally distributed |
| | E) | the error terms are independently distributed |
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9 | |
The procedure that produces predictions with the lowest sum of squared distances between actual and predicted values in a bivariate regression analysis is called: |
|
| | A) | sum of square analysis |
| | B) | ordinary least squares |
| | C) | simple short square method |
| | D) | summated short squares |
| | E) | square root analysis |
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10 | |
Another term for error (the difference between actual and predicted values of Y) is: |
|
| | A) | residuals |
| | B) | leftovers |
| | C) | carry-outs |
| | D) | carry-overs |
| | E) | shorts |
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11 | |
A researcher wants to include a predictor variable in a multiple regression analysis. This variable is a nominal variable and has four response options. Which one of the following options applies best to this scenario? |
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| | A) | Add three dummy variables for the nominal variable |
| | B) | Add four dummy variables for the nominal variable |
| | C) | Add one dummy variable for the nominal variable |
| | D) | Add five dummy variables for the nominal variable |
| | E) | Nominal variables cannot be included in multiple regression |
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12 | |
In order to determine if the correlation coefficient is meaningful or not, it is not sufficient to look at only the statistical significance of the coefficient (one also needs to examine the substantive significance of the difference). |
|
| | A) | True |
| | B) | False |
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13 | |
When doing a regression analysis, one can say that the independent variable causes changes in the dependent variable. |
|
| | A) | True |
| | B) | False |
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14 | |
In regression analysis, Adjusted—R—square is always greater than R2. |
|
| | A) | True |
| | B) | False |
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15 | |
The problem of multicollinearity cannot happen in bivariate regression analysis. |
|
| | A) | True |
| | B) | False |