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42 Cards in this Set
- Front
- Back
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Bivariate regression is effectively an extension of …
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Pearson r.
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Bivariate regression provides us information that allows us to build …
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a regression equation
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A regression equation allows us to predict what a case’s score on the dependent variable would be based on a specified value on the _____ variable.
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independent
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A useful device for the purposes of visually depicting the association between two variables is known as a …
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scatter plot |
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A visual depiction of the slope associated with a scatter plot is known as a …
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regression line |
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Another term for regression line is …
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line of best fit |
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If the correlation between two variables is zero, the regression line associated with the corresponding scatter plot would be …
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flat. |
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A regression equation helps us predict the value of ___ given a value of …
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Y, X |
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Write out the regression equation with one predictor
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Y = b0 + b1(X) + e (2 marks)
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The expected increase or decrease in the dependent variable (Y) as a function of an increase or decrease in the independent variable (X) is known as the…
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slope.
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In bivariate regression (one independent variable), the standardized slope is identical to the…
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Pearson correlation |
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the ______ slope is not usually readily interpretable in psychological research.
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unstandardized |
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The expected value of Y when X is 0 is known as the …
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intercept. |
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The point at which the regression line crosses the Y-axis is known as the …
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intercept. |
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The regression line represents the position in the scatter plot which corresponds to the ___ amount of summed squared deviations between the line and the observations.
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smallest |
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The term in the regression equation that represents the variance that is not predicted by equation is known as _____.
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error. |
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The probability with which a regression equation may be an accurate representation of the effects at the population level is estimated via the statistical significance of ____.
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model R. |
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SPSS uses an _____ approach to testing Model R for statistical significance.
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ANOVA |
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SPSS uses the term SS _____ to refer to the Sums of Squares Model (SSM)
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Reggression |
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The larger the _____ sums of squares are relative to the _____ sums of squares, the greater the chances the Model is statistically significant, rather than simply a chance occurrence.
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Regression. Residual (2 marks)
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When you conduct a regression analysis in SPSS and you select the ‘Descriptives’ option, you get the means, standard deviations, Ns, as well as the …
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Pearson correlations. |
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The average amount of error associated with predicting a single value of Y is known as…
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standard error of the estimate |
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Because R is known to be biased upwards to some degree, SPSS outputs an additional R square value known as ...
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adjusted R square. |
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Another term for R square is …
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Coefficient of determination. |
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In the SPSS table below, by how much (on average) is the prediction equation off (in absolute terms) in predicting a single Y value?
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23.929
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In the SPSS table below, if you divided SS Regression by SS Total, you would get ____.
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Model R square |
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Based on the SPSS table below, if a participant scored zero on the independent variable, what would be the best estimate of his/her score on the dependent variable?
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45.321
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Based on the SPSS table below, by how much would a person’s score increase on the dependent variable for a one unit increase in the independent variable?
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.567 |
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Based on the SPSS table below, what is the Pearson correlation between the independent and dependent variables?
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.397
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Based on the table below, what would you get if you divided the unstandardized coefficient by the standard error of the unstandardized coefficient?
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t-value
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What are the assumptions associated with regression?
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dependent variable measured on interval/ratio scale; random sampling; independence of observations; normally distributed data; homoscedasticity (5 marks)
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For the purposes of conducting parametric analyses, data should be considered sufficiently normally distributed so long as absolute skew is less than…
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2 |
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For the purposes of conducting parametric analyses, data should be considered sufficiently normally distributed so long as absolute kurtosis is less than…
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9 |
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When the residuals associated with a regression analysis have equal variance across the spectrum of the independent variable the data are considered to be…
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homoscedastic
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Observed value – predicted value = ?
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residual |
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In order to calculate residuals within SPSS in an automatic way, you need to use the _____ utility.
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Save... |
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When homoscedasticity is not satisfied, it implies that the prediction equation is not ____ _____ across the whole spectrum of the independent variable.
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equally predictive |
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In order to help evaluate the assumption of homoscedasticity, one can plot the ____ and the ____.
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standardized residuals, standardized predicted values
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A statistical approach (i.e., with a p value) to evaluating the assumption of homoscedasticity is known as the ….
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Breusch-Pagan test.
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The opposite of homoscedasticity is …..
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heteroscedasticity
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Homoscedasticity could also be called…
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Homogeneity of variance in the residuals.
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If a researcher obtained an unstandardized beta weight of 4.5 in a study that used number of years of education to predict annual salary (thousands of dollars), how much additional money would you expect someone to earn for every 2 years extra of education they achieved?
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9k |
