Question: A negative correlation between a hockey player’s age and the number of minutes he spends in the penalty box indicates that:

the older a player is, the less time he spends in the penalty box.

spending more time on the ice leads hockey players to become skilled at avoiding the referees.

an older player’s greater experience has taught him how to avoid making penalties.

older players make fewer penalties because they have reduced testosterone levels.

Flag this Question Question 22 pts Gretchen, an adult, takes an intelligence test and it shows she has slightly above average intelligence. Four years later, she has the chance to take the same test again. This time it reports that she is a genius. While she wants to believe the results, she wonders if the inconsistency of results over time might mean the test:

is poorly correlated with intelligence.

has low test–retest reliability.

has high split-half reliability.

has a high coefficient alpha.

Flag this Question Question 32 pts Researchers who study the process of reading in children have discovered that better readers make smoother eye movements across the page (i.e., there is a positive correlation between reading skill and the smoothness of the eye movements). Which of the following statements is a possible cause of the correlation between smooth eye movements and reading ability?

Having good reading skills allows a child to make smooth eye movements.

All of these options are possible causes of the correlation.

The ability to make smooth eye movements improves reading ability.

Some third factor might cause both smooth eye movements and improved reading ability.

Flag this Question Question 42 pts What is the correlation between a person’s weight as measured in grams and a person’s weight as measured in pounds?

+1.00

–1.00

0.00

It is impossible to determine from the information provided.

Flag this Question Question 52 pts The model of possible causal explanations for a correlation is called the:

A-B-C model.

cause-and-effect model.

causal explanation model.

1-2-3 model.

Flag this Question Question 62 pts “The incidence of depression among college students is negatively correlated with the number of sunny days each year in the locale where they attend college.” This statement means that:

if a depressed student were to move to a locale with more sunny days, her depression would subside.

a student attending college in a locale with very few sunny days will become depressed.

the chances of a college student being depressed tend to increase as the number of sunny days increases.

the chances of a college student being depressed tend to be higher with fewer sunny days.

Flag this Question Question 72 pts A positive correlation between head size and foot size indicates that:

having large feet causes a person to have a large head.

having a large head causes a person to have large feet.

people with larger feet tend to have smaller heads.

people with larger feet also tend to have larger heads.

Flag this Question Question 82 pts A perfect linear relationship will yield a Pearson’s r value of:

1.00 or –1.00.

0.

1.00.

–1.00.

Flag this Question Question 92 pts The best and most widely used measure of reliability is:

the split-half correlation, in which the odd and even numbered items of a measure are correlated to assess internal consistency.

criterion-related reliability.

coefficient alpha, the average of all possible split-half correlations.

the test-retest reliability.

Flag this Question Question 102 pts Test-retest reliability is determined by:

correlating the odd numbered items of a measure with an individual’s performance on the even numbered items of that same measure.

correlating the odd numbered items of a measure with an individual’s performance on the even numbered items of a different measure.

administering the same measure to two different samples at two different points in time and calculating the correlation between an individual’s performance at the two different times

administering the same measure to the same sample at two different points in time and calculating the correlation between an individual’s performance on the two administrations.

Flag this Question Question 112 pts The sign of the correlation communicates:

the direction of the association.

the direction and strength of the correlation.

the direction of the causal relationship.

the strength of the correlation.

Flag this Question Question 122 pts Psychometricians are concerned with:

studying illness and the onset of psychological illness.

developing high quality tests and measures.

statistics and computers.

fixing psychological issues in people.

Flag this Question Question 132 pts One assumption for using hypothesis testing for Pearson correlation is that one variable should vary equally at each level of the other variable. What is the easiest way to determine whether this assumption has been met?

If the calculation of r is high, then the assumption has been met.

Calculate the cross-products of the deviation scores. If the result is positive, then the assumption has been met.

Conduct a post-hoc test following the calculation of r.

Draw a scatterplot to see whether the range of values is equal across all values of the other variable.

Flag this Question Question 142 pts Which of the following numbers would represent a perfect correlation?

–1.00

1.00

–1.00 or 1.00

0

Flag this Question Question 152 pts What kind of correlation would you expect to find between the severity of snowstorms and rates of attendance at college classes?

positive

perfect negative

negative

zero

Flag this Question Question 162 pts The denominator of the Pearson correlation equation corrects for ________ and ________ issues present in the numerator.

negative values; nonlinear data

sample size; nonnormality

negative values; variability

sample size; variability

Flag this Question Question 172 pts In a reanalysis of published studies, Twenge and Im (2007) found that for the time period 1958–2001, the need for social approval of people in the United States was negatively correlated with the U.S. violent crime rate during the same period (the correlation coefficient was –0.31). This correlation means that:

as the need for social approval went up, the number of violent crimes also increased.

the need for social approval prevented people from committing violent crimes.

the need for social approval spurred people to commit violent crimes.

as the need for social approval went up, the number of violent crimes decreased.

Flag this Question Question 182 pts Imagine that you’ve just read the results of a study that finds a positive correlation between gum chewing and life expectancy. Which of the following statements would be a statistically appropriate response to the results of the study?

You bemoan the possibility of living so long that you will have to chew lots of gum.

You become curious about what third variables might cause both increases in gum chewing and increases in life expectancy.

You purchase a lifetime supply of gum because chewing gum is good for your health.

You tell all your friends and family members to chew gum because it is good for their health.

Flag this Question Question 192 pts If all the points on a scatterplot fall on a single line:

there is a positive correlation between the two variables.

the relation between the variables is perfect.

there is no relation between the variables.

the variables are causally related.

Flag this Question Question 202 pts What kind of correlation would you expect to find between levels of family income and household spending on consumer goods?

zero

perfect positive

positive

negative

Flag this Question Question 212 pts The numerator (top half) of the Pearson correlation coefficient formula includes:

the difference between the two sample means.

the sum of the product of the deviations for each variable.

.

the square root of the product of the two sums of squares.

Flag this Question Question 222 pts Suppose a researcher discovers that length of time spent following a Mediterranean diet is negatively correlated with risk of developing cancer. Which of the statements logically follows from this information?

Eating a Mediterranean diet reduces the risk of developing cancer.

People who ate a Mediterranean diet for more time were more likely to have cancer.

Eating a Mediterranean diet increases the risk of developing cancer.

People who ate a Mediterranean diet for more time were less likely to have cancer.

Flag this Question Question 232 pts Figure: Student-Faculty Ratio

Reference: Figure 1

(Figure: Student–Faculty Ratio) The relation depicted in the scatterplot is potentially deceptive because of:

poor validity.

poor reliability.

the presence of outliers.

restriction of range.

Flag this Question Question 242 pts Assume that the correlation coefficient between class attendance and number of problems missed on an exam is (–0.77). Which statement regarding this finding is correct?

There is definitely no causal relationship between the two variables.

The correlation provides definitive information pertaining to causation.

If you attend class regularly, you are more likely to do well on the exam than someone who does not attend class regularly.

If you start attending class more regularly, the number of problems you miss on the next exam is certain to be reduced.

Flag this Question Question 252 pts The Pearson correlation coefficient is symbolized:

x

r

c

t

Flag this Question Question 262 pts The ________ quantifies the relationship between two variables.

magnitude of the correlation

sign of the correlation

correlation coefficient

correlation

Flag this Question Question 272 pts A ________ is a graphical representation of the relation between two variables.

polygon

correlation coefficient

scatterplot

histogram

Flag this Question Question 282 pts The proportionate reduction in error is a measure of the:

correlation between two variables.

variability of the dependent measure.

amount of variance in the dependent variable explained by the independent variable.

slope of a regression line.

Flag this Question Question 292 pts With regression we are concerned about variability around the ________, rather than variability around the ________ which would be the case in t tests or ANOVAs.

line of best fit; mean

median; tails of the distribution

mean; outliers

outliers; line of best fit

Flag this Question Question 302 pts To determine the slope of the line of best fit using the z-score regression information, we compare the values of:

X at zero versus X at 1.0.

X at zero versus Y at zero.

Y at zero versus X at zero.

Y at zero versus Y at 1.0.

Flag this Question Question 312 pts The regression line is also called the:

prediction estimate.

error of estimate.

line of best fit.

line of central limit.

Flag this Question Question 322 pts If we have information about the slope of the line of best fit that corresponds to two sets of data about class grades for different instructors, we cannot make comparisons based on these slopes because:

they are based on different populations.

slopes cannot be compared meaningfully.

they are not on a common scale.

the slopes have to share the same sign.

Flag this Question Question 332 pts Every year it seems as though last season’s baseball rookie of the year fails to live up to expectations for his sophomore season. What might explain this phenomenon?

regression to the mean

standard error of the estimation

overestimation of effect size

proportionate reduction in error

Flag this Question Question 342 pts Multiple regression predicts scores on a single ________ from scores on more than one ________.

dependent variable; independent variable

scale variable; nominal variable

independent variable; predictor variable

predictor; dependent variable

Flag this Question Question 352 pts As the standard error of estimate becomes larger, predictions become:

less accurate.

more accurate.

smaller.

larger.

Flag this Question Question 362 pts Proportionate reduction in error is sometimes called:

coefficient phi.

correlation coefficient.

alpha coefficient.

the coefficient of determination.

Flag this Question Question 372 pts A researcher calculates a standardized regression coefficient on data from 52 events and computes β as 0.274. Assuming a two-tailed hypothesis test of the relation between these two variables is being conducted with an alpha of 0.05, what are the critical cutoffs?

–0.288 and 0.288

–0.273 and 0.273

–0.361 and 0.361

–0.250 and 0.250

Flag this Question Question 382 pts The measure of effect size used with regression is:

R2, just like with ANOVA.

the proportionate reduction in error, r2.

the alpha coefficient.

standard error of correlation.

Flag this Question Question 392 pts Which of the following statistics quantifies the improvement in ability to predict a person’s score when using the regression line rather than the mean?

standard deviation

proportionate reduction in error

standard error of the estimation

slope

Flag this Question Question 402 pts The standardized regression coefficient is not equal to the correlation coefficient when:

both variables are measured on an interval scale.

there is greater variability in the X variables compared to the Y variable.

the equation includes more than one independent variable.

a negative relationship is present.

Flag this Question Question 412 pts In a study designed to predict blood cholesterol levels from amount of daily saturated fat in grams (X1) and number of hours of daily exercise (X2), we determine that the slope of X1 is 5, the slope of X2 is –4, and the y intercept is 130. Which of the following formulas is the regression equation for these data?

Ŷ = 130 + 5(X1) – 4(X2)

Ŷ = 130 + 5(X1) + 4(X2)

Ŷ = 130 + 1(X)

Ŷ = 130 – 5(X1) – 4(X2)

Flag this Question Question 422 pts The standardized regression coefficient expresses the:

likelihood of rejecting the null hypothesis with a regression analysis.

relation between the independent and dependent variable in terms of squared units.

strength of the correlation between the two variables that are now incorporated into a regression analysis.

predicted change in the dependent variable in terms of standard deviation units as a result of a 1 standard deviation increase in the independent variable.

Flag this Question Question 432 pts The standardized regression coefficient is often called a:

normalized regression.

beta weight.

weighted estimate.

estimate of best fit.

Flag this Question Question 442 pts The regression line is the line that:

minimizes the correlation coefficient.

is the mean of the dependent variable.

minimizes error in predicting scores on the independent variable.

minimizes error in predicting scores on the dependent variable.

Flag this Question Question 452 pts The standardized regression coefficient expresses a predicted change in the dependent variable in terms of:

error units.

slope.

a 1-unit change in the independent variable.

standard deviations units.

Flag this Question Question 462 pts We can examine a graph to get a sense of how much error there is in a regression equation. Which of the following describes a graph that reveals there will be a high amount of error when using our regression equation?

Data points cluster very close to the line with several outlier exceptions.

The data points consistently cluster far away from the line of best fit.

Data points cluster close around the line of best fit.

Data points fall directly on the line.

Flag this Question Question 472 pts In the equation Ŷ = 98 + 4.30(X1) + 7.20(X2), what is the slope?

98

4.30

Both 4.30 and 7.20 are slopes.

7.20

Flag this Question Question 482 pts In the equation for a regression line, the intercept is the:

predicted value for Y when X is equal to 0.

value for X when Y is equal to 0.

z score of the amount that Y is predicted to increase as X increases.

amount that Y is predicted to increase for a one-unit increase in X.

Flag this Question Question 492 pts In a study designed to predict blood cholesterol levels from amount of daily saturated fat in grams (X1) and number of hours of daily exercise (X2), we determine that the slope of X1 is 5, the slope of X2 is –4, and the y intercept is 130. If someone reports that she typically eats 10 grams of saturated fat daily and exercises 1 hour daily, what would you predict for the person’s cholesterol level?

184

180

176

150

Flag this Question Question 502 pts A small standard error of the estimate means that:

your two variables are poorly correlated.

confounding variables may be present.

variability is high in your Y variable.

you are making predictions with great accuracy.

Flag this Question Question 512 pts The table includes information for creating a regression equation to predict students’ attitude toward statistics from their attitudes toward Britney Spears and beer.

Table: Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta

1 (Constant) 4.974 0.590 8.432 0.000

attbritneyspears 0.264 0.155 0.256 1.701 0.097

attbeer -0.309 0.122 -0.381 -2.536 0.015

a Dependent variable: attstatistics Reference: Table 1

(Table: Coefficients) What is the y intercept for this problem?

0.590

0.000

4.974

8.432

Flag this Question Question 522 pts The table includes information for creating a regression equation to predict students’ attitude toward statistics from their attitudes toward Britney Spears and beer.

Table: Coefficients(a)

Model Unstandardized Coefficients Standardized Coefficients t Sig.

B Std. Error Beta

1 (Constant) 4.974 0.590 8.432 0.000

attbritneyspears 0.264 0.155 0.256 1.701 0.097

attbeer -0.309 0.122 -0.381 -2.536 0.015

a Dependent variable: attstatistics Reference: Table 1

(Table: Coefficients) Was either variable a significant predictor for attitude toward statistics?

Attitude toward Britney Spears was a significant predictor but attitude toward beer was not.

No; neither was a signigicant predictor.

Yes; both were significant predictors.

Attitude toward beer was a significant predictor but attitude toward Britney Spears was not.

Flag this Question Question 532 pts If two variables, independently, can help us predict the outcome of a third variable, we say that they are:

orthogonal.

autonomous.

standardized.

proportionate.