Question 1

Statistical tests were designed to test for relationships and differences on normally distributed variables.

Accepted Answer

A) True 
 B)False  True

Question 2

Describe the limitations of correlation as a statistical test.

Accepted Answer

Correlation as a statistical test has several limitations that should be taken into consideration when interpreting the results.

Firstly, correlation does not imply causation. Just because two variables are correlated does not mean that one variable causes the other. There could be other factors at play that are influencing the relationship between the variables.

Secondly, correlation coefficients can be influenced by outliers in the data. A few extreme data points can greatly affect the strength and direction of the correlation, leading to potentially misleading results.

Additionally, correlation measures only linear relationships between variables. If the relationship between the variables is non-linear, the correlation coefficient may not accurately capture the strength of the relationship.

Furthermore, correlation does not account for confounding variables. There may be other variables that are influencing the relationship between the two variables being studied, and correlation alone cannot control for these potential confounders.

Finally, correlation coefficients can be sensitive to the scale of measurement. Different units of measurement for the variables can lead to different correlation coefficients, making it difficult to compare the strength of relationships across different studies or datasets.

In conclusion, while correlation can be a useful tool for exploring relationships between variables, it is important to be aware of its limitations and to interpret the results with caution. It is often necessary to complement correlation analysis with other statistical tests and consider the broader context of the research question.

Question 3

To use a correlation as a statistical test, each participant must have provided measurements on two separate variables.

Accepted Answer

A) True 
 B)False  True

Question 4

Statistically significant results ensure practical application of the results.

Accepted Answer

A) True 
 B)False

Question 5

Correlations can also be computed for variables based on ordinal or nominal data. These tests include:

Accepted Answer

A)  point biserial correlation 
B)  spearman correlation coefficient 
C)  coefficient of determination 
D)  a and b 
E)  b and c 
A)  point biserial correlation 
B)  spearman correlation coefficient 
C)  coefficient of determination 
D)  a and b 
E)  b and c

Question 6

A correlation matrix is used to:

Accepted Answer

A)  display how every variable is correlated with every other variable. 
B)  display the shared variance between pairs of variables. 
C)  identify all of the possible hypotheses in a research study. 
D)  determine which relationships are significant and worthy of further study. 
E)  none of the above. 
A)  display how every variable is correlated with every other variable. 
B)  display the shared variance between pairs of variables. 
C)  identify all of the possible hypotheses in a research study. 
D)  determine which relationships are significant and worthy of further study. 
E)  none of the above.

Question 7

Exogenous variables are:

Accepted Answer

A)  Used in structural equation modeling (SEM) 
B)  Also known as endogenous variables 
C)  Variables that are not caused by another variable 
D)  Variables that are caused by another variable 
E)  Both a and c 
A)  Used in structural equation modeling (SEM) 
B)  Also known as endogenous variables 
C)  Variables that are not caused by another variable 
D)  Variables that are caused by another variable 
E)  Both a and c

Question 8

A correlation is the statistical test for:

Accepted Answer

A)  testing the linear relationship between two continuous level variables. 
B)  testing the linear relationships among three continuous level variables. 
C)  determining degrees of freedom. 
D)  determining the significance level of other statistical tests. 
E)  examining two variables of nominal level data. 
A)  testing the linear relationship between two continuous level variables. 
B)  testing the linear relationships among three continuous level variables. 
C)  determining degrees of freedom. 
D)  determining the significance level of other statistical tests. 
E)  examining two variables of nominal level data.

Question 9

Describe the steps the researcher takes to interpret the regression statistic once it can be determined that the test is significant.

Accepted Answer

Once the researcher has determined that

Question 10

Statistical tests for relationship are limited to two variables.

Accepted Answer

A) True 
 B)False

Question 11

A significant r value would cause the researcher to retain the null hypothesis.

Accepted Answer

A) True 
 B)False

Question 12

Regression is of particular advantage to communication researchers because it allows researchers to study variables that cannot be experimentally manipulated.

Accepted Answer

A) True 
 B)False

Question 13

Explain the phrase "variance accounted for"as it would be used with a test of regression.

Accepted Answer

In the context of a test of regression,

Question 14

Describe how the researcher interprets a correlation if the .05 significance level is not achieved.

Accepted Answer

If the .05 significance level is not ach

Question 15

Researchers use inferential statistics to determine if the relationship observed in the data is stronger than the relationship that might occur due to chance.

Accepted Answer

A) True 
 B)False

Question 16

Regardless of how the research hypothesis is stated, there is a complementary null hypothesis.

Accepted Answer

A) True 
 B)False

Question 17

Because there is no theoretical limit to the number of predictor variables tested in multiple regression, it is common for researchers to include 10 or more.

Accepted Answer

A) True 
 B)False

Question 18

Tests for relationship are most commonly computed for variables of continuous level data.

Accepted Answer

A) True 
 B)False

Question 19

Multiple regression allows the researcher to determine the relative importance of each variable to the regression relationship.

Accepted Answer

A) True 
 B)False

Question 20

If the data for the variables being tested are not normally distributed, the statistical test:

Accepted Answer

A)  cannot be used. 
B)  is not affected. 
C)  provides only an approximation of the relationship. 
D)  must be done on other variables. 
E)  can control for this by adding additional degrees of freedom. 
A)  cannot be used. 
B)  is not affected. 
C)  provides only an approximation of the relationship. 
D)  must be done on other variables. 
E)  can control for this by adding additional degrees of freedom.

Statistical tests were designed to test for relationships and differences on normally distributed variables.

Describe the limitations of correlation as a statistical test.

To use a correlation as a statistical test, each participant must have provided measurements on two separate variables.

Statistically significant results ensure practical application of the results.

Correlations can also be computed for variables based on ordinal or nominal data. These tests include:

A correlation matrix is used to:

Exogenous variables are:

A correlation is the statistical test for:

Describe the steps the researcher takes to interpret the regression statistic once it can be determined that the test is significant.

Statistical tests for relationship are limited to two variables.

A significant r value would cause the researcher to retain the null hypothesis.

Regression is of particular advantage to communication researchers because it allows researchers to study variables that cannot be experimentally manipulated.

Explain the phrase "variance accounted for"as it would be used with a test of regression.

Describe how the researcher interprets a correlation if the .05 significance level is not achieved.

Researchers use inferential statistics to determine if the relationship observed in the data is stronger than the relationship that might occur due to chance.

Regardless of how the research hypothesis is stated, there is a complementary null hypothesis.

Because there is no theoretical limit to the number of predictor variables tested in multiple regression, it is common for researchers to include 10 or more.

Tests for relationship are most commonly computed for variables of continuous level data.

Multiple regression allows the researcher to determine the relative importance of each variable to the regression relationship.

If the data for the variables being tested are not normally distributed, the statistical test:

Introduction to Communication Research

The Research Process: Getting Started

Research Ethics

Introduction to Quantitative Research

Measurement

Populations, Samples, and Sample Size

Quantitative Research Designs

Surveys and Questionnaires

Descriptive Statistics, Significance Levels, and Hypothesis Testing

Testing for Differences

Quantitative Analysis of Text

Reading and Writing the Quantitative Research Report

Introduction to Qualitative Research

Designing Qualitative Research

Qualitative Methods of Data Collection

Analyzing Qualitative Data

Reading and Writing the Qualitative Research Report

Filters

Exam 11: Testing for Relationships

Statistical tests were designed to test for relationships and differences on normally distributed variables.

Describe the limitations of correlation as a statistical test.

To use a correlation as a statistical test, each participant must have provided measurements on two separate variables.

Statistically significant results ensure practical application of the results.

Correlations can also be computed for variables based on ordinal or nominal data. These tests include:

A correlation matrix is used to:

Exogenous variables are:

A correlation is the statistical test for:

Describe the steps the researcher takes to interpret the regression statistic once it can be determined that the test is significant.

Statistical tests for relationship are limited to two variables.

A significant r value would cause the researcher to retain the null hypothesis.

Regression is of particular advantage to communication researchers because it allows researchers to study variables that cannot be experimentally manipulated.

Explain the phrase "variance accounted for"as it would be used with a test of regression.

Describe how the researcher interprets a correlation if the .05 significance level is not achieved.

Researchers use inferential statistics to determine if the relationship observed in the data is stronger than the relationship that might occur due to chance.

Regardless of how the research hypothesis is stated, there is a complementary null hypothesis.

Because there is no theoretical limit to the number of predictor variables tested in multiple regression, it is common for researchers to include 10 or more.

Tests for relationship are most commonly computed for variables of continuous level data.

Multiple regression allows the researcher to determine the relative importance of each variable to the regression relationship.

If the data for the variables being tested are not normally distributed, the statistical test:

Introduction to Communication Research

The Research Process: Getting Started

Research Ethics

Introduction to Quantitative Research

Measurement

Populations, Samples, and Sample Size

Quantitative Research Designs

Surveys and Questionnaires

Descriptive Statistics, Significance Levels, and Hypothesis Testing

Testing for Differences

Quantitative Analysis of Text

Reading and Writing the Quantitative Research Report

Introduction to Qualitative Research

Designing Qualitative Research

Qualitative Methods of Data Collection

Analyzing Qualitative Data

Reading and Writing the Qualitative Research Report

Filters