Question 1

The proportion of variability in one variable that can be determined or explained by a second variable is known as the

Accepted Answer

The coefficient of determination, also known as R-squared, is a measure of how well the variation in one variable can be explained by another variable. It ranges from 0 to 1, with higher values indicating a stronger relationship between the two variables. It is often used in regression analysis to evaluate the effectiveness of a regression model in predicting the values of the dependent variable based on the values of the independent variable(s).

Question 2

The following are correlation coefficients that you might find when correlating scores for two variables EXCEPT?

Accepted Answer

The correlation coefficient cannot exceed 1, so a value of 1.35 is impossible.

Question 3

Correlational designs have benefited from what quantitative developments in the history of research?

Accepted Answer

A

Question 4

A researcher conducts a study to determine if good interpersonal skills should be used to hire new competent bus drivers for the public school district.What type of correlational design would this researcher use?

Accepted Answer

This design is appropriate because the researcher is trying to determine if a candidate's interpersonal skills (the predictor variable) can be used to predict their competence as a bus driver (the outcome variable). This design does not establish causality, but it can provide valuable information for making hiring decisions.

Question 5

What is the basic feature of multiple regression analysis?

Accepted Answer

Multiple regression analysis examines the effect of multiple independent variables on one dependent variable. It is used to determine the extent to which a set of independent variables can predict a dependent variable.

Question 6

Examine the following correlation matrix and then answer the following questions.
A Correlation Matrix
 $\begin{array}{|lcccccc|}
\hline \text { Variables }&1&2&3&4&5&6\
\hline  \text { 1. School climate } &\underline{\quad\quad}  \
\text { 2. Number of teachers } &.36^{**} &\underline{\quad\quad} \
\text { 3. School in-service } & .45 &-.03\
\text { activities } & \
\text { 4. Funding } & .22&.51^{**} &.30^{*}&\underline{\quad\quad}  \
\text { 5. Support from } & -.09&-.02&-.60^{**}&.16 &\underline{\quad\quad} \
\text { community } & \
\text { 6. Yrs. Experience of }  & .25^{**} &-.10&.39^{**}&.29^{*}&.10 &\underline{\quad\quad}  \
\text { leaders }\
\hline 
\end{array}$
 *p<.05 and **p<.01
-From examining the matrix,what type of relationship exists between school climate the outcome)and the other variables measured in the study?

Accepted Answer

The answer of Examine the following correlation matrix and then...

Question 7

A researcher conducting a study examining the influence of stress on achievement in a middle school draws the conclusion that stress causes low achievement scores.What correlational ethical issue is the researcher breaching?

Accepted Answer

The researcher is breaching the ethical issue of establishing causality when the results show patterns of relationships. Correlation does not imply causation. Thus, by concluding that stress causes low achievement scores, the researcher is not considering the possibility of reverse causality or third variable explanations. It is important to avoid making causal claims when only correlational data is available.

Question 8

Which of the following advanced correlational statistical procedures provides extensive information about which variables affect others variables and the direction of these effects?

Accepted Answer

Structural equation modeling is an advanced correlational statistical procedure that provides extensive information about which variables affect others variables and the direction of these effects. SEM is a statistical method for testing and estimating causal relationships using a combination of statistical data and qualitative causal assumptions. It allows researchers to examine complex, multivariate relationships among variables and provides a framework for testing complex theories. The other options do not provide as much information regarding the direction of relationships among variables.

Question 9

Which of the following steps is most important to remember when conducting a meta-analysis?

Accepted Answer

Coding the studies based on criteria about the study and its basic characteristics is the most important step in conducting a meta-analysis. This helps ensure that the studies being included are relevant and comparable. While the other options are also important considerations for conducting a meta-analysis, they are not as crucial as ensuring that the studies being included are coded accurately.

Question 10

Examine the following correlation matrix and then answer the following questions.
A Correlation Matrix
 $\begin{array}{|lcccccc|}
\hline \text { Variables }&1&2&3&4&5&6\
\hline  \text { 1. School climate } &\underline{\quad\quad}  \
\text { 2. Number of teachers } &.36^{**} &\underline{\quad\quad} \
\text { 3. School in-service } & .45 &-.03\
\text { activities } & \
\text { 4. Funding } & .22&.51^{**} &.30^{*}&\underline{\quad\quad}  \
\text { 5. Support from } & -.09&-.02&-.60^{**}&.16 &\underline{\quad\quad} \
\text { community } & \
\text { 6. Yrs. Experience of }  & .25^{**} &-.10&.39^{**}&.29^{*}&.10 &\underline{\quad\quad}  \
\text { leaders }\
\hline 
\end{array}$
 *p<.05 and **p<.01
-What association is the strongest of all of the variables in the matrix?

Accepted Answer

The answer of Examine the following correlation matrix and then...

Question 11

A researcher collects scores for male and female students and scores running from a 50 to a 99 on a math final test.This researcher is interested in correlating these scores to determine if there is an association between gender and test scores.What correlation statistic would this researcher use?

Accepted Answer

Point-biserial correlation is the appropriate correlation statistic to use when one variable is dichotomous (in this case, gender) and the other variable is continuous (scores on the math test). Pearson correlation would be appropriate if both variables were continuous, Phi-coefficient would be appropriate if both variables were dichotomous, and regression statistic would be appropriate if the researcher wanted to predict scores on the math test based on gender.

Question 12

Examine the following correlation matrix and then answer the following questions.
A Correlation Matrix
 $\begin{array}{|lcccccc|}
\hline \text { Variables }&1&2&3&4&5&6\
\hline  \text { 1. School climate } &\underline{\quad\quad}  \
\text { 2. Number of teachers } &.36^{**} &\underline{\quad\quad} \
\text { 3. School in-service } & .45 &-.03\
\text { activities } & \
\text { 4. Funding } & .22&.51^{**} &.30^{*}&\underline{\quad\quad}  \
\text { 5. Support from } & -.09&-.02&-.60^{**}&.16 &\underline{\quad\quad} \
\text { community } & \
\text { 6. Yrs. Experience of }  & .25^{**} &-.10&.39^{**}&.29^{*}&.10 &\underline{\quad\quad}  \
\text { leaders }\
\hline 
\end{array}$
 *p<.05 and **p<.01
-What pattern of association would you expect to find if the scores were plotted for the variable,funding,and the variable,number of teachers?
________

Accepted Answer

The answer of Examine the following correlation matrix and then...

Question 13

Examine the following correlation matrix and then answer the following questions.
A Correlation Matrix
 $\begin{array}{|lcccccc|}
\hline \text { Variables }&1&2&3&4&5&6\
\hline  \text { 1. School climate } &\underline{\quad\quad}  \
\text { 2. Number of teachers } &.36^{**} &\underline{\quad\quad} \
\text { 3. School in-service } & .45 &-.03\
\text { activities } & \
\text { 4. Funding } & .22&.51^{**} &.30^{*}&\underline{\quad\quad}  \
\text { 5. Support from } & -.09&-.02&-.60^{**}&.16 &\underline{\quad\quad} \
\text { community } & \
\text { 6. Yrs. Experience of }  & .25^{**} &-.10&.39^{**}&.29^{*}&.10 &\underline{\quad\quad}  \
\text { leaders }\
\hline 
\end{array}$
 *p<.05 and **p<.01
-Why are some cells left blank?
______________________________________________________
______________________________________________________

Accepted Answer

The answer of Examine the following correlation matrix and then...

Question 14

Student scores on a "positive outlook toward life" and the number of close friends were plotted on a graph.The points on the graph show that high scores on the "positive outlook" scale were related to low scores on the number of friends and that high scores on the number of friends were related to low scores on the "positive outlook" scale.What type of relationship do these scores depict?

Accepted Answer

The relationship depicted is a negative relationship, as high scores on one variable are related to low scores on the other variable.

Question 15

An explanatory and a prediction correlational design have what factor in common?

Accepted Answer

Both designs involve examining the relationship between two or more variables. In the explanatory design, this is done to explain the cause and effect relationship between variables, while in the predictive design, the goal is to use the relationship between variables to make accurate predictions about future outcomes.

Question 16

Which one of the factors below best distinguishes between experimental and correlational research?

Accepted Answer

The use of an intervention is the best factor that distinguishes between experimental and correlational research. Experimental research involves the manipulation of an independent variable to observe its effect on a dependent variable, while correlational research involves the measurement of two or more variables to observe their relationship. An intervention is only used in experimental research, whereas in correlational research variables are simply measured without any manipulation or intervention. Thus, the use of an intervention is the best factor to distinguish between these two types of research designs.

Question 17

Which one of the following is a good example of the concept of co-variance in correlational research?

Accepted Answer

Co-variance in correlational research refers to the extent to which two variables change together, allowing for prediction of one variable based on the other.

Question 18

If you were to examine two plots of scores on two scatterplots and draw circles around the scores,which two plots listed below would be the most similar in form?

Accepted Answer

Positive linear and negative linear scatterplots would be most similar in form because both exhibit a clear, linear pattern, albeit in opposite directions. Positive linear shows a direct relationship where as scores on one variable increase, scores on the other variable also increase. Negative linear shows an inverse relationship where as scores on one variable increase, scores on the other variable decrease. Both, however, maintain a consistent linear form.

Quiz 11: Correlational Designs

The proportion of variability in one variable that can be determined or explained by a second variable is known as the

The following are correlation coefficients that you might find when correlating scores for two variables EXCEPT?

Correlational designs have benefited from what quantitative developments in the history of research?

A researcher conducts a study to determine if good interpersonal skills should be used to hire new competent bus drivers for the public school district.What type of correlational design would this researcher use?

What is the basic feature of multiple regression analysis?

A researcher conducting a study examining the influence of stress on achievement in a middle school draws the conclusion that stress causes low achievement scores.What correlational ethical issue is the researcher breaching?

Which of the following advanced correlational statistical procedures provides extensive information about which variables affect others variables and the direction of these effects?

Which of the following steps is most important to remember when conducting a meta-analysis?

A researcher collects scores for male and female students and scores running from a 50 to a 99 on a math final test.This researcher is interested in correlating these scores to determine if there is an association between gender and test scores.What correlation statistic would this researcher use?

An explanatory and a prediction correlational design have what factor in common?

Which one of the factors below best distinguishes between experimental and correlational research?

Which one of the following is a good example of the concept of co-variance in correlational research?

If you were to examine two plots of scores on two scatterplots and draw circles around the scores,which two plots listed below would be the most similar in form?