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42 Cards in this Set
 Front
 Back
Bivariate regression is effectively an extension of …

Pearson r.


Bivariate regression provides us information that allows us to build …

a regression equation


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.

independent


A useful device for the purposes of visually depicting the association between two variables is known as a …

scatter plot 

A visual depiction of the slope associated with a scatter plot is known as a …

regression line 

Another term for regression line is …

line of best fit 

If the correlation between two variables is zero, the regression line associated with the corresponding scatter plot would be …

flat. 

A regression equation helps us predict the value of ___ given a value of …

Y, X 

Write out the regression equation with one predictor

Y = b0 + b1(X) + e (2 marks)


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…

slope.


In bivariate regression (one independent variable), the standardized slope is identical to the…

Pearson correlation 

the ______ slope is not usually readily interpretable in psychological research.

unstandardized 

The expected value of Y when X is 0 is known as the …

intercept. 

The point at which the regression line crosses the Yaxis is known as the …

intercept. 

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.

smallest 

The term in the regression equation that represents the variance that is not predicted by equation is known as _____.

error. 

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 ____.

model R. 

SPSS uses an _____ approach to testing Model R for statistical significance.

ANOVA 

SPSS uses the term SS _____ to refer to the Sums of Squares Model (SSM)

Reggression 

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.

Regression. Residual (2 marks)


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 …

Pearson correlations. 

The average amount of error associated with predicting a single value of Y is known as…

standard error of the estimate 

Because R is known to be biased upwards to some degree, SPSS outputs an additional R square value known as ...

adjusted R square. 

Another term for R square is …

Coefficient of determination. 

In the SPSS table below, by how much (on average) is the prediction equation off (in absolute terms) in predicting a single Y value?

23.929


In the SPSS table below, if you divided SS Regression by SS Total, you would get ____.

Model R square 

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?

45.321


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?

.567 

Based on the SPSS table below, what is the Pearson correlation between the independent and dependent variables?

.397


Based on the table below, what would you get if you divided the unstandardized coefficient by the standard error of the unstandardized coefficient?

tvalue


What are the assumptions associated with regression?

dependent variable measured on interval/ratio scale; random sampling; independence of observations; normally distributed data; homoscedasticity (5 marks)


For the purposes of conducting parametric analyses, data should be considered sufficiently normally distributed so long as absolute skew is less than…

2 

For the purposes of conducting parametric analyses, data should be considered sufficiently normally distributed so long as absolute kurtosis is less than…

9 

When the residuals associated with a regression analysis have equal variance across the spectrum of the independent variable the data are considered to be…

homoscedastic


Observed value – predicted value = ?

residual 

In order to calculate residuals within SPSS in an automatic way, you need to use the _____ utility.

Save... 

When homoscedasticity is not satisfied, it implies that the prediction equation is not ____ _____ across the whole spectrum of the independent variable.

equally predictive 

In order to help evaluate the assumption of homoscedasticity, one can plot the ____ and the ____.

standardized residuals, standardized predicted values


A statistical approach (i.e., with a p value) to evaluating the assumption of homoscedasticity is known as the ….

BreuschPagan test.


The opposite of homoscedasticity is …..

heteroscedasticity


Homoscedasticity could also be called…

Homogeneity of variance in the residuals.


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?

9k 