Stats Module 6 quiz

The item below is based on the following scenario. An educational psychologist wants to predict how well students will do on a particular multiple-choice test based on a measure of their ability to follow instructions. Their actual scores are 3, 7, and 11, and their respective predicted scores are 5, 7, and 9. Advanced topic: What is SS Error?

(3-5) 2 + (7-7) 2 + (11-9) 2

The item below is based on the following scenario. An educational psychologist wants to predict how well students will do on a particular multiple-choice test based on a measure of their ability to follow instructions. Their actual scores are 3, 7, and 11, and their respective predicted scores are 5, 7, and 9. Advanced topic: What is SS Total?

(3-7) 2 + (7-7) 2 + (11-7) 2

An educational psychologist wants to predict how well students will do on a particular multiple-choice test based on a measure of their ability to follow instructions. Their actual scores are 3, 7, and 11, and their respective predicted scores are 5, 7, and 9. Advanced topic: What is SS Total?

(3-7)2 + (7-7)2 + (11-7)2

The item below is based on the following scenario. An educational psychologist wants to predict how well students will do on a particular multiple-choice test based on a measure of their ability to follow instructions. Their actual scores are 3, 7, and 11, and their respective predicted scores are 5, 7, and 9. Advanced topic: What is the proportionate reduction in error?

(32 - 8) / 32 = 0.75

What is the formula for the proportionate reduction in error?

(SSTotal - SSError) / SSTotal

When conducting a t test for the correlation coefficient in a study with 16 individuals, the degrees of freedom will be

14

When drawing a regression line for a linear prediction rule, the minimum number of predicted points on a graph that must be located is

2

If a child psychologist reports that age in months predicts appetite level for a group of infants using a linear prediction rule in which a = 1 and b = 2, the appetite level for a four-month-old infant is

9

what is the direction of causality when two variables, A and B, have a strong linear correlation?

All of the above are possible.

The person given credit for inventing correlation is

Francis Galton

Which limitation is applicable to both correlation and regression?

Nothing can be inferred about the direction of causality

The result of multiplying two Z scores is always

Positive if the individual has low raw scores on both variables

The items below are based on the following scenarios. Which graph depicts no correlation?

Scenario C

The items below are based on the following scenarios. Which graph depicts a negative correlation?

Scenario D

How does Ralph Rosnow and Robert Rosenthal's position on the interpretation of correlations differ from traditional views?

They argue that even low correlations can have important implications.

What does it mean when SS Total minus SS Error equals zero?

This is the worst case—it means the prediction model has reduced zero error.

The term in a linear prediction rule that represents the intercept of a regression line is

a

When making predictions using a linear prediction rule, the baseline number that is added to each prediction

a

A study indicates that in general the more fruit students eat before a test, the better they do on the test. However, beyond a certain point, the more fruit students eat, the worse they do on the test. Thus, the relation between amount of fruit eaten and test performance is an example of

a curvilinear correlation.

Why are errors squared in a regression?

because summing positive and negative errors will cancel them out

When a person's score on one variable is used to make predictions about a person's score on another variable, the procedure is called

bivariate prediction.

When figuring a correlation coefficient, an outlier

can have an strong effect on the computed correlation

If a counseling psychologist wants to predict college grades from high school grades, college grades are the

criterion variable.

The sum of squared errors is the sum of

each score on the criterion variable minus the predicted score, squared

The sum of squared errors is the sum of

each score on the criterion variable minus the predicted score, squared.

Which assumption is applicable to regression but not to correlation?

error scores are normally distributed

On a scatter diagram, the vertical distance between the dot for the actual score and the regression line represents the

error.

One way to handle a situation in which high scores go with high scores and low scores with low scores but the pattern of scores is not linear is to

figure Spearman's rho.

In a linear prediction rule using a standardized regression coefficient,

for each increase of one standard deviation in the predictor variable, the predicted standard deviation of the criterion variable increases by the standardized regression coefficient.

When figuring a correlation coefficient, the absolute value of the summed cross-products

gets larger when the scores of more people are included in the analysis.

A regression coefficient indicates

how many units of change in the predicted value of the criterion variable for each unit of change in the predictor variable.

Under what conditions can the possibility that Y causes X be ruled out when two variables, X and Y, are strongly correlated?

if X occurs before Y

Under what conditions can an experimenter be confident that X is the cause of Y if two variables, X and Y, are strongly correlated?

if people are randomly assigned to levels of X in a true experiment

The term for the subjective overestimation of the strength of the relationship between two variables is

illusory correlation.

Illusory correlations are caused by

incorrect theories based on prejudices.

When testing the significance of the correlation coefficient, the null hypothesis is usually that in the population, the true correlation

is zero.

Low reliability of the variables reduces the correlation coefficient because

it adds random noise to the computations.

Making a scatter diagram before figuring the correlation coefficient is a good idea because

it allows estimation of the degree and direction of correlation to provide a check on eventual figuring.

The statistical procedure used to make predictions about people's poetic ability based on their scores on a general writing ability test and their scores on a creativity test is

multiple regression.

Spearman's rho handles curvilinearity in the relation between two variables by first converting all scores to

ranks.

In the equation Ŷ = a + ( b)( X), b is the symbol for the

regression coefficient.

A graph that shows the pattern of the relation of two variables is a

scatter diagram.

A regression line

shows the relation between values of the predictor and criterion variables.

The best linear prediction rule is the one that has the least

squared error when predicting using that rule.

If the correlation coefficient for a study is known, figuring the proportionate reduction in error requires

squaring the correlation coefficient.

If a psychologist interested in the relation between number of years working for a particular company and loneliness at work surveyed 40 workers at this company and figured a correlation between these two variables of -.90, the correlation is considered a

strong negative linear correlation.

The regression constant is also referred to as

the Y intercept

When correlations are reported in a research article, which of the following information is least likely to be provided?

the Z scores

The standardized regression coefficient in a bivariate linear prediction rule equals

the correlation coefficient.

the standardized regression coefficient in a bivariate linear prediction rule equals

the correlation coefficient.

The regression constant in the best linear prediction rule is

the mean of the criterion variable minus the result of multiplying the regression coefficient by the mean of the predictor variable.

When making a scatter diagram,

the overall shape should be roughly square.

Considering the number of possible linear prediction rules for predicting Y from X, for any particular set of scores

there is only one best rule

If the correlation between two personality traits is .07, the correlation is considered a

weak positive linear correlation

If the correlation between two personality traits is .07, the correlation is considered a

weak positive linear correlation.

in psychology research articles,

when results for bivariate prediction are reported, it is most likely to be with regression lines

When is it inappropriate to conduct a t test for the correlation coefficient?

when the relationship is nonlinear

When is the correlation coefficient zero?

when there is no linear correlation

The multiple regression formula with two predictor variables is

Ŷ = a + (b1)(X1) + (b2)(X2).

In a bivariate linear prediction, the null hypothesis is that

β = 0 .