Deck 8: Correlational Research

Question 1

Sam concluded in his research report that as class size increased teaching efficacy also increased. Of the following which is a correlation coefficient would best support Sam's claim.

A) -.82
B) .09
C) .24
D) .68

Answer 1

D

Question 2

Which of the following correlation coefficients best represents the plot below?

A) -.45
B) -.25
C) .15
D) .75

Answer 2

C

Question 3

Joyce read a study that reported students' age was correlated r = -.68 with classroom management referrals. This correlation indicates as age increases,

A) classroom management referrals are about equally likely to decrease or increase.
B) classroom management referrals are more likely to decrease.
C) classroom management referrals are more likely to increase.
D) classroom management referrals are likely to remain at the same level.

Answer 3

B

Question 4

Correlational studies are used primarily to

A) examine relationships among quantifiable variables.
B) examine if differences between groups exist.
C) determine causal relationships.
D) determine if experimental treatments work.

Question 5

Of the following, which is most likely an example of a correlational study?

A) A study that indicated differences in GPA between ROTC and non ROTC students.
B) A study that examines organizational variables that predict retention of special education teachers.
C) A study that examines characteristics of exchange student host families.
D) A study that examines the effect of overt displays of teacher empathy on student class behavior.

Question 6

According to your text, the fewest number of participants required for a correlation study is

A) 15.
B) 30.
C) 45.
D) 60.

Question 7

Suzanne reported a correlation between reading ability and math grades of r = .90 in the first grade. This correlation indicates that in Suzanne's study

A) reading ability is strongly related to math grades.
B) reading and math grades are independent.
C) reading ability and math grades are mutually exclusive.
D) reading ability and math grades are moderately related.

Question 8

Qi's analysis indicated that for those students who took calculus in high school and then introductory calculus in the first year of University, grades were correlated r = .45. This indicates that high school grades and university grades are

A) strongly related.
B) independent.
C) moderately related.
D) mutually exclusive.

Question 9

The correlation that Kim found in her study between math self-efficacy and enrollment in advanced mathematics was r = .25. Her correlation can be described as

A) weak.
B) meaningful.
C) strong.
D) predictive.

Question 10

Which of the following demonstrates the strongest correlation coefficient?

A) 0.0
B) 1.5
C) .65
D) -.72

Question 11

Correlation studies must include

A) two or more levels of independent variable.
B) two or more quantifiable variables.
C) three or more variables and two groups.
D) one independent variable and two dependent variables.

Question 12

Given the graph below what is the most likely correlation between these variables?

A) -.60
B) .30
C) .80
D) 1.0

Question 13

Which of the following cannot be a correlation coefficient?

A) -.80
B) 0.0
C) .72
D) 2.1

Question 14

Given a correlation of r = .60, the common variance shared by the variables is

A) 16%.
B) 36%.
C) 60%.
D) 90%.

Question 15

In a prediction study of low achieving students academic motivation, Hillary was surprised that achievement scores were not a significant predictor of motivation. Hillary's analysis is most likely is displaying

A) shrinkage.
B) attenuation.
C) standard variance.
D) restriction of range.

Question 16

Which of the following represents the strongest correlation?

A) -.85
B) 0.0
C) .35
D) .65

Question 17

Computing the statistical significance of a correlation requires the

A) mean, sample size, level of significance.
B) mean and level of significance.
C) level of confidence and sample size.
D) sample size and mean.

Question 18

A strong negative correlation coefficient indicates that

A) two variables are not related.
B) two variables are inversely related.
C) there has been measurement error.
D) there has been calculation error

Question 19

Attenuation refers to

A) stating there is not a relationship between two variables when there is one
B) lowered accuracy in a prediction equation when it is applied to a new sample.
C) combining many variables in order to predict the most amount of variance.
D) reduction of correlation coefficients when measures have low reliability.

Question 20

Kevin's analysis indicated that in his dataset SES was correlated r = .25 with absenteeism. This indicates that

A) as SES increases there is a corresponding increase in absenteeism.
B) SES is moderately correlated with absenteeism.
C) SES is weakly correlated with absenteeism.
D) absenteeism is strongly correlated with SES.

Question 21

Generally, when more variables are added to a prediction equation

A) more variance in the criterion variable is accounted for.
B) more variance in the predictor variables are accounted for.
C) less variance in the criterion variable is accounted for.
D) less variance in the predictor variable is accounted for.

Question 22

A Pearson r correlation is best used for data that is expressed as

A) ordinal and continuous.
B) only rank.
C) only ordinal.
D) only continuous.

Question 23

Low reliability of variables

A) does not effect interrelatedness of variables.
B) decreases the chance of finding significant relationships.
C) increases the chance of finding number of significant relationships.
D) may either increase of decrease the chance of finding significant relationship.

Question 24

In a single prediction question (Y=a + bX), X represents a(n)

A) predicted criterion score.
B) distribution of scores in the sample.
C) individual's score on the predictor variable.
D) constant calculated from the scores.

Question 25

Joe uses age, family size, and income to predict scores on a survey of happiness. The results were statistically significant with a coefficient of determination of 64%. He collects a new sample and examines the regression equation. In Joe's second sample, the common variance will likely __________ due to __________.

A) decrease, attenuation
B) increase, replication
C) decrease, shrinkage
D) increase, regression.

Question 26

George suspects that there is a curvilinear relationship in his data set. Which of the following correlation coefficient should George calculate?

A) Pearson
B) Eta
C) Kendall's tau
D) Spearman rho

Question 27

Gretchen wanted to see whether, given a sample of teachers' that graduated from colleges and Universities, GPA in college was related to starting salary as a teacher. Which correlation coefficient should Gretchen calculate?

A) Pearson r
B) eta
C) Kendall's tau
D) Spearman rho

Question 28

Which of the following measures is used when the criterion variable in a prediction study is categorical?

A) Multiple regression
B) Path analysis c Discriminate function analysis
D) Canonical correlation

Question 29

Joni teaches a preschool class. She has eight students and ranks them based upon math and reading ability. She would like to see if there is a relationship between how well her students are ranked in math and in reading. Which of the following correlations should she use?

A) Kendall's tau
B) Phi coefficient
C) Biserial
D) Eta

Question 30

The common variance shared by the predictor and criterion variables is referred to as the

A) coefficient of determination.
B) standard error of regression.
C) coefficient of regression.
D) standard error of determination.

Question 31

A Phi coefficient is used for

A) rank level data.
B) continuous level data.
C) artificial dichotomous level data.
D) true dichotomous level data.

Question 32

Data collection for types of correlation studies is generally

A) longer than most qualitative approaches.
B) shorter for prediction studies than for correlation studies.
C) longer than most types of quantitative research.
D) shorter than most types of quantitative research.

Question 33

The criterion variable in a prediction study is the name for the

A) the variable used to select participants.
B) the variable that is predicted.
C) the variable used to make a prediction.
D) the independent variable.

Question 34

In a single prediction question (Y=a + bX), Y represents a(n)

A) predicted criterion score.
B) distribution of scores in the sample.
C) individual's score.
D) constant calculated from the scores.

Question 35

When using correlational analysis with multiple predictors and multiple criterion variables, the appropriate procedure is

A) Multiple Linear Regression
B) Canonical correlation
C) Discriminate function analysis
D) Path analysis

Question 36

Cheryl used age, education, and income to predict scores on a life satisfaction survey. Her regression equation accounted for 58% of the variance in life satisfaction. She collects a new sample and applies her equation. This process is referred to as

A) discriminate testing.
B) sample attenuation.
C) regression reliability.
D) cross-validation.

Question 37

Jack administered an achievement test with an internal consistency reliability of .65. Jack should interpret this result as

A) high internal consistency reliability.
B) moderate internal consistency reliability.
C) acceptable internal consistency reliability.
D) low internal consistency reliability.

Question 38

Shrinkage refers to

A) lowered accuracy in a prediction equation when it is applied to a new sample.
B) combining many variables in order to predict the most amount of variance.
C) effects of unreliable instruments underestimating the correlation.
D) a measure of the error found in a regression equation.

Question 39

A correlation between reading and math achievement scores on a national standardized test for first graders indicates a correlation of r = .90. How much variance do these scores share?

A) 30%
B) 45%
C) 81%
D) 90%

Question 40

Regarding sampling, one strategy to facilitate obtaining accurate results when there will be subgroup correlations is to select a

A) stratified sample.
B) cluster sample.
C) random sample.
D) purposive sample.

Question 41

Yeung reported a correlation of .70 between hours of exercise and self-reported stress-level in graduate students. Which of the following is an accurate statement regarding this result?

A) The two variables were unrelated in her study.
B) As hours of exercise increased, stress generally increased.
C) Her finding represents a moderate effect.
D) Her results represent significant differences.

Question 42

Duffy's research addresses the relationships among amount of practice time, race times, and motivation for running in high school athletes. He measures motivation for running by a Likert scale. Given Duffy's research, which one of the following correlation coefficients should he use to analyze his data?

A) Kendall's tau
B) Spearman's rho
C) Pearson r
D) Phi coefficient

Question 43

Laura is designing a study of the extent to which standardized achievement test scores in high school predict college GPA using a large dataset of 50,000 students. Which of the following potential problems is most important to consider?

A) The sample size may be too small to detect a correlation.
B) The sample size may result in a correlation that is practically unimportant.
C) The variables require the use of a phi coefficient.
D) The sample size may require factor analysis.

Question 44

Kenji reported a correlation of r = -.85 between hours spent in community service and adolescent drug use. This finding suggests that

A) there is no relationship between community service and adolescent drug use.
B) the more community service one performs the more likely one is to use drugs.
C) the more community service one performs the less likely one is to use drugs.
D) Kenji has calculated the correlation incorrectly because he has a negative number.

Question 45

Of the following research topics, which is most likely to be a relationship study?

A) The relationship between motivation and acheivement.
B) The difference in minutes a day exercising between boys and girls.
C) The types of exercise students engage in after school.
D) The experiences of John at after school track practice.

Question 46

Which of the following illustrates a correlational research topic?

A) Do weight and number of days per week of exercise predict life satisfaction?
B) Are there differences between men and women in life satisfaction?
C) What are is someone with a high life satisfaction score like?
D) Are there self-esteem differences in children from either families with or without high life satisfaction?

Question 47

When considering the use of Spearman rho or Pearson r for use with a small sample of less than 30.

A) Spearman's rho is more accurate than Pearson r
B) Spearman's rho is easier to calculate.
C) Pearson r is the appropriate measure to use.
D) Pearson r is easier to calculate.

Question 48

Jamie found an internal consistency reliability coefficient of .60 for his measure of spatial ability. Jaime's instrument

A) shows high internal consistency reliability.
B) shows adequate internal consistency reliability.
C) shows minimally acceptable internal consistency reliability.
D) shows poor internal consistency reliability.

Question 49

Of the following research topics, which is most likely to represent a prediction study?

A) The mathematics activities found in a sixth grade math class.
B) The teaching philosophy of a new mathematics teacher.
C) The relationship between mathematics grades and math class in the next semester.
D) The differences in mathematics grades based upon parents' educational level.

Question 50

Monica, on the other hand, reported a correlation of 3.4 between community service and interest in helping professions among adolescents. This finding suggests that

A) there is no relationship between community service and interest in helping professions.
B) the more community service one performs the more likely one is to have interest in a helping profession.
C) the more community service one performs the less likely one is to have interest in a helping profession.
D) Monica has calculated the correlation incorrectly because 3.4 is not a possible correlation coefficient.