FINAL EXAM STATS 200
According to guidelines published by Cohen (1988), a correlation value of ________ is considered small, ________ is medium, and _______ is strong. A. 0.10; 0.30; 0.50 B. 1.00; 2.00; 3.00 C. 0.25; 0.50; 0.75 D. 0.40; 0.60; 0.80
A
An important point to remember about correlation is that while there is a _______________ relationship, correlation does not equal____________. A. statistical; causation B. plausible; causation C. probable; causation D. factual; causation
A
In the equation for a regression line, the slope is: A. the amount that Y is predicted to increase for a 1-unit increase in X. B. the value for X when Y is equal to 0. C. the predicted value for Y when X is equal to 0. D. the z score of the amount that Y is predicted to increase as X increases.
A
In the formula, Ŷ = a + b(X), a is the: A. intercept. B. predicted value for the dependent variable. C. observed value on the independent variable. D. slope.
A
In which situation would it be necessary to use a between-groups ANOVA? A. A researcher is interested in the effects of distraction on driving performance and randomly assigns participants to one of three distraction groups. B. A researcher classifies a group of college students on the basis of their political leanings as liberal or conservative. C. A researcher is interested in a longitudinal study that follows a group of kindergarten children through high school and assesses their body mass index at four time points. D. A researcher is interested in whether a sensitivity training class changes attitudes toward minority populations. The researcher assesses these attitudes before and after the sensitivity training class.
A
Regression is to ________ as correlation is to ________. A. prediction; relation B. association; causation C. relation; prediction D. causation; association
A
Researchers who study the process of reading in children have discovered that better readers make smoother eye movements across the page (e.g., there is a positive correlation between reading skill and the smoothness of the eye movements). Which of the following is a possible cause of this correlation between smooth eye movements and reading ability? A. All of these options are possible causes of the correlation. B. Some third factor might cause both smooth eye movements and improved reading ability. C. Having good reading skills allows a child to make smooth eye movements. D. The ability to make smooth eye movements improves reading ability.
A
The z, t, and F distributions have something in common—the numerator of the test statistic: A. contains a measure of difference among group means. B. represents what would be expected to happen by chance. C. contains a measure of difference within the various groups. D. is a squared number.
A
What kind of correlation would you expect to find between the severity of snowstorms and rates of attendance at college classes? A. negative B. positive C. perfect negative D. zero
A
Which of the following represents degrees of freedom for r? A. N - 2 B. Σ(X - Mx)2 C. N - 1 D. (N1 - 1)(N2 -1)
A
1995 data from over 1,000 colleges published in U.S. News & World Report were used to predict the percent of alumni who donate to a college from the average SAT score of students attending that college. The resulting regression equation was Yˆ = -29.29 + 0.05(X). Using the regression equation what would you predict to be the percent of alumni who will donate to a college whose students' average SAT score is 1065? A. 0.02% B. 23.96% C. 0.08% D. 82.54%
B
1995 data from over 1,000 colleges published in U.S. News & World Report were used to predict the percent of alumni who donate to a college from the average SAT score of students attending that college. The resulting regression equation was Yˆ = -29.29 + 0.05(X). Using the regression equation what would you predict to be the percent of alumni who will donate to a college whose students' average SAT score is 1065? A. 82.54% B. 23.96% C. 0.02% D. 0.08%
B
Cohen's d cannot be used as a measure of effect size for ANOVA because: A. there is no effect size measure for ANOVA. B. it can only compare two means. C. its values no longer have meaning when more than two groups are compared. D. it must be saved to compute effect size for the post hoc tests.
B
Given a scale dependent variable and a nominal independent variable with three or more levels, a(n) _____ could be used to analyze the data. A. t test B. ANOVA C. PRE test D. z test
B
If all the points on a scatterplot fall on a single line: A. there is a positive correlation between the two variables. B. the relation between the variables is perfect. C. there is no relation between the variables. D.the variables are causally related.
B
If an F statistic is negative, which of these is true? A. The difference among the group means is greater than what would have occurred by chance. B. There has been a calculation error. C. The within-groups variance exceeds the between-groups variance. D. The difference among the group means is less than what would have occurred by chance.
B
If between-groups variance is much larger than within-groups variance, we infer that the sample means are _____ one another, and we _____ the null hypothesis. A. different from; fail to reject B. different from; reject C. similar to; fail to reject D. similar to; reject
B
In a re-analysis of published studies, Twenge and Im (2007) found that for the time period of 1958 to 2001, the need for social approval of people in the United States was positively correlated with changes in the Dow Jones Industrial Average during that same period (the correlation coefficient was +0.10). This means that: A. the need for social approval prevented people from investing money in the stock market. B. as the need for social approval went up the Dow Jones also increased. C. the need for social approval caused people to invest more money in the stock market. D. as the need for social approval went up the Dow Jones decreased.
B
Partial correlation allows for the control of _________ variables. A. independent B. third C. dependent D. weakly related
B
Simple linear regression allows us to: A. determine the relation among four or more variables. B. predict an individual's score on the dependent variable from their score on the independent variable. C. infer the direction of causal relations. D. predict an individual's score on a dependent variable from their score on multiple independent variables.
B
The standardized regression coefficient expresses a predicted change in the dependent variable in terms of: A. slope. B. standard deviations units. C. a 1-unit change in the independent variable. D. error units.
B
Which of the following values of the correlation coefficient indicates the weakest relationship between two variables? A. -0.32 B. +0.25 C. +0.27 D. -0.54
B
A positive correlation between hand size and foot size indicates that: A. having large hands causes a person to have large feet. B. having large feet causes a person to have large hands. C. people with larger feet also tend to have larger hands. D. people with larger feet tend to have smaller hands.
C
A post hoc test is warranted when one: A. has an a priori prediction about which group means will differ. B. fails to reject the null hypothesis in an ANOVA. C. rejects the null hypothesis and there are more than two groups. C. rejects the null hypothesis when performing an independent-groups t test.
C
A post hoc test is warranted when one: A. has an a priori prediction about which group means will differ. B. fails to reject the null hypothesis in an ANOVA. C. rejects the null hypothesis and there are more than two groups. D. rejects the null hypothesis when performing an independent-groups t test.
C
A researcher wants to be able to predict first semester college grade point averages with as much accuracy as possible and so she would like to use both high school grade point averages and SAT scores as predictor variables. Which of the following techniques would be most appropriate to make this prediction? A. proportionate reduction in error B. standardized regression coefficient C. multiple regression D. simple linear regression
C
An F statistic calculated on 2 and 26 degrees of freedom equals 2.23. Which decision should be made about a hypothesis tested at the p = 0.05 level? A. Reject the null hypothesis and conclude there are differences among the groups. B. Fail to reject the null hypothesis and conclude there are differences among the groups. C. Fail to reject the null hypothesis and conclude no significant differences are indicated among the groups. D. Reject the null hypothesis and conclude no significant differences are indicated among the groups.
C
If the p level is 0.05 and the null hypothesis is true, what is the probability of making a Type I error (i.e., that one will fail to reject the null hypothesis)? A. 0.95 B. 0.00 C. 0.05 D. 0.90
C
If the p level is 0.05 and the null hypothesis is true, what is the probability of making a Type I error (i.e., that one will fail to reject the null hypothesis)? A. 0.95 B. 0.00 C. 0.05 D. 0.90
C
In the equation for a regression line, the intercept is: A. the z score of the amount that Y is predicted to increase as X increases. B. the value for X when Y is equal to 0. C. the predicted value for Y when X is equal to 0. D. the amount that Y is predicted to increase for a 1-unit increase in X.
C
In the formula, Ŷ = a + b(X), b is the: A. observed value on the independent variable. B. predicted value for the dependent variable. C. slope. D. intercept
C
To predict a single dependent variable from more than one independent variable, which statistical technique would you use? A. correlation B. simple linear regression C. multiple regression D. structural equation modeling
C
What kind of correlation would you expect to find between the age of a home and its value? A. zero B. positive C. negative D. perfect positive
C
Which of the following would indicate the strongest relationship between two variables? A. -0.52 B. +0.04 C. -0.83 D. +0.81
C
Y is the symbol for a(n) ________ and Ŷ is the symbol for a(n) ________. A. score on the dependent variable; score on the independent variable B. score on the independent variable; score on the dependent variable C. observed score; predicted score D. predicted score; observed score
C
"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: A. the chances of a college student being depressed tend to increase as the number of sunny days increases. B. a student attending college in a locale with very few sunny days will become depressed. C. if a depressed student were to move to a locale with more sunny days, the student's depression would subside. D. the chances of a college student being depressed tend to increase as there are fewer sunny days.
D
A measure is said to be valid if: A. its results are consistent. B. the specific procedures used in the measure are identified. C. it is low in measurement error. D. it measures what it is supposed to measure.
D
A measure of the differences among group means is: A. the z score. B. the proportionate reduction in error. C. within-groups variance. D. between-groups variance.
D
A negative correlation between a hockey player's age and the number of minutes he spends in the penalty box indicates that: A. older players make fewer penalties because they have reduced testosterone levels. B. an older player's greater experience has taught him how to avoid making penalties. C. spending more time on the ice leads hockey players to become skilled at avoiding the referees. D. the older a player is, the less time he spends in the penalty box.
D
A researcher can't just run multiple t tests when the independent variable has more than two levels because as more statistical tests are run: A. the probability of making a Type III error in one of the tests increases. B. it becomes harder and harder to reject the null hypothesis. C. degrees of freedom are lost. D. the probability of making a Type I error in one of the tests increases.
D
Between-groups degrees of freedom is calculated by: A. subtracting 1 from the total number of subjects in the study. B. subtracting 1 from the number of subjects within each group and then adding those numbers together. C. multiplying the number of subjects by the number of conditions in the study and then subtracting 1. D. subtracting 1 from the total number of groups in the study.
D
Data from the 1993 World Almanac and Book of Facts were used to predict the life expectancy for men in a country from the life expectancy of women in that country. The resulting regression equation was Yˆ = 9.32 + 0.79(X). Using the regression equation, what would you predict to be the life expectancy of men in a country whose life expectancy for women is 72 years? A. 47.56 years B. 79.36 years C. 64.64 years D. 66.20 years
D
If a negative relation exists between two variables, then low scores on one variable will be associated with ________ scores on the other variable. A. neither high nor low B. both high and low C. low D. high
D
In a re-analysis of published studies, Twenge and Im (2007) found that for the time period of 1958 to 2001, the need for social approval of people in the United States was negatively correlated with the U.S. divorce rate during that same period (the correlation coefficient was -0.38). This means that: A. the need for social approval spurs people to get divorced. B. as the need for social approval increased, divorce rates increased. C. the need for social approval prevents people from seeking divorce. D. as the need for social approval increased, divorce rates decreased.
D
R2, the effect size for ANOVA, is calculated as a ratio of: A. within-groups mean squares to between-groups mean squares. B. total sum of squares to within-groups sum of squares. C. total mean squares to total sum of squares. D. between-groups sums of squares to total sum of squares.
D
The F ratio is calculated by: A. squaring all the scores. B. averaging the results from the t tests for all possible two-group comparisons. C. dividing a measure of within-groups variability by a measure of between-groups variability. D. dividing a measure of between-groups variability by a measure of within-groups variability.
D
The F ratio is calculated by: A. squaring all the scores. B. dividing a measure of within-groups variability by a measure of between-groups variability. C. averaging the results from the t tests for all possible two-group comparisons. D. dividing a measure of between-groups variability by a measure of within-groups variability.
D
The regression line is the line that: A. minimizes the correlation coefficient. B. is the mean of our dependent variable. C. minimizes our error in predicting scores on the independent variable. D. minimizes our error in predicting scores on the dependent variable.
D
There is a different F distribution for every: A. level of the independent variable. B. within-groups degrees of freedom. C. sample size. D. combination of sample size and number of samples.
D
What is the null hypothesis when testing for significance using the Pearson correlation coefficient? A. ρ =/ 0 B. r =/ 0 C. μ1 = μ2 D. ρ= 0
D
When F is significant: A. the values of the means that are farthest apart are the only ones that are significant. B. we fail to reject the null hypothesis. C. the values of the means that are closest together are the only ones that are significant. D. we do not know which specific means differ significantly.
D
Within-groups degrees of freedom is calculated by: a. for each condition, subtracting 1 from the number of subjects in that group and then adding together the totals for all the groups. b. multiplying the number of subjects by the number of conditions in the study and then subtracting 1. C. subtracting 1 from the total number of groups in the study. D. subtracting 1 from the total number of subjects in the study.
NOT D