Deck 14: Simple Regression
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Deck 14: Simple Regression
1
Simple regression is appropriate for examining the bivariate relationships between two continuous variables.
True
2
A scatterplot is a plot of the data points of two continuous variables.
True
3
The slope of the regression line is also called the regression coefficient.
True
4
The null hypothesis in regression is that the intercept is zero.
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5
The slope indicates the steepness of the regression line.
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6
A negative slope indicates an upward sloping line.
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7
The statistical significance of regression slopes is indeterminable.
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8
R2 is the percent variation of the dependent variable explained by the independent variable(s).
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9
R2 varies from 1 to 2.
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10
A perfect fit is indicated when the coefficient of determination is zero.
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11
The standard error of the estimate is a measure of the spread of the y values around the regression line as calculated for the mean value of the independent variable, only, and assuming a large sample.
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12
A regression line assumes a linear relationship that is constant over the range of observations.
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13
The dependent variable is also called the error term.
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14
Pearson's correlation coefficient, r, measures the association (significance, direction, and strength) between two continuous variables.
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15
R = r and |R| = |r|.
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16
The Pearson's correlation coefficient, r, always has the same sign as b.
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17
The Spearman rank order correlation coefficient tests whether the rank orders of responses of two variables are statistically associated.
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18
The Spearman rank order correlation coefficient is appropriate for nominal-, ordinal-, and continuous-level variables.
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