The primary factor that determines the statistical test students should use is the number of independent...
- The primary factor that determines the statistical test students should use is the number of independent and dependent variables. True or False
- When investigating the relationship between two or more quantitative variables, chi-square is the appropriate test.True or False
- The Pearson correlation coefficient measures the association between two quantitative variables, distinguishing between the independent and dependent variables.True or False
- Multiple regression is used when there are several dependent variables and one independent quantitative variable.True or False
- When testing for the significance of group differences, the number of IVs, the number of DVs, and the number of categories in the DV determine the appropriate test.True or False
- The most basic statistical test that measures group difference is the T-test.True or False
- One-way analysis of variance (ANOVA) only determines the significance of group differences and does not identify which groups are significantly different.True or False
- One-way analysis of covariance (ANCOVA) is similar to ANOVA but additionally controls for a variable that may influence the DV.True or False
Homework Answers
1) The primary factor that determines the statistical test students should use is the number of independent and dependent variables. (True)
2) When investigating the relationship between two or more quantitative variables, chi-square is the appropriate test. (False)
3) The Pearson correlation coefficient measures the association between two quantitative variables, distinguishing between the independent and dependent variables. (True)
4) Multiple regression is used when there are several dependent variables and one independent quantitative variable. (False)
5) When testing for the significance of group differences, the number of IVs, the number of DVs, and the number of categories in the DV determine the appropriate test. (True)
6) The most basic statistical test that measures group difference is the T-test. (True)
7) One-way analysis of variance (ANOVA) only determines the significance of group differences and does not identify which groups are significantly different. (True)
8) One-way analysis of covariance (ANCOVA) is similar to ANOVA but additionally controls for a variable that may influence the DV. (True)
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The primary factor that determines the statistical test
students should use is the number of independent...
6. The most basic statistical test that measures group difference is the T-test. 7. One-way analysis...
6. The most basic statistical test that measures group difference is the T-test. 7. One-way analysis of variance (ANOVA) only determines the significance of group differences and does not identify which groups are significantly different. 8. One-way analysis of covariance (ANCOVA) is similar to ANOVA but additionally controls for a variable that may influence the DV. 9. Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs that are categorical. 10. Factorial analysis of...
Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs...
Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs that are categorical. True or False Factorial analysis of variance (factorial ANCOVA) examines group differences in a single quantitative dependent variable based upon two or more categorical independent variables, while controlling for a covariate that may influence the DV. True or False One-way multivariate analysis of variance (MANOVA) is utilized to simultaneously study two or more related IVs, while controlling for the correlations among...
Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs...
Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs that are categorical. True or False Factorial analysis of variance (factorial ANCOVA) examines group differences in a single quantitative dependent variable based upon two or more categorical independent variables, while controlling for a covariate that may influence the DV. True or False One-way multivariate analysis of variance (MANOVA) is utilized to simultaneously study two or more related IVs, while controlling for the correlations among...
1. Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more...
1. Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs that are categorical. True or False 2. Factorial analysis of variance (factorial ANCOVA) examines group differences in a single quantitative dependent variable based upon two or more categorical independent variables, while controlling for a covariate that may influence the DV. True or False 3. One-way multivariate analysis of variance (MANOVA) is utilized to simultaneously study two or more related IVs, while controlling for...
One-way analysis of covariance (ANCOVA) is similar to ANOVA but additionally controls for a variable that...
One-way analysis of covariance (ANCOVA) is similar to ANOVA but additionally controls for a variable that may influence the DV. T F Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs that are categorical. T F Factorial analysis of variance (factorial ANCOVA) examines group differences in a single quantitative dependent variable based upon two or more categorical independent variables, while controlling for a covariate that may influence the DV. T F One-way multivariate...
Discriminant analysis seeks to identify which combination of quantitative IVs best predicts group membership by a...
Discriminant analysis seeks to identify which combination of quantitative IVs best predicts group membership by a single DV that has two or more categories. T F In binary logistic regression, the DV is a dichotomous variable. T F Factor analysis and principal components analysis are different techniques, but they are very similar. T F Factor analysis allows the researcher to explore the underlying structures of an instrument or data set and is often used to develop and test a theory....
22. Questions that address structure usually distinguish between independent and dependent variables O 2017 Taylor &...
22. Questions that address structure usually distinguish between independent and dependent variables O 2017 Taylor & Francis 23. When investigating the relationship between two or more quantitative variables, the T test is the appropriate test. 24. Prediction of group membership is evaluated by ANOVA, ANCOVA, MANOVA, and MANCOVA 25. Significance of group differences is evaluated by discriminant analysis and logistic regression.
11. One-way multivariate analysis of variance (MANOVA) is utilized to simultaneously study two or more related...
11. One-way multivariate analysis of variance (MANOVA) is utilized to simultaneously study two or more related IVs, while controlling for the correlations among the IVs. 12. One-way multivariate analysis of covariance (MANCOVA) investigates group differences among several IVs, while also controlling for covariates that may influence the DVs 13. Factorial multivariate analysis of variance (factorial MANOVA) extends MANOVA to research scenarios with two or more DVs that are categorical. 14. Factorial multivariate analysis of covariance (MANCOVA) extends factorial MANCOVA to...
1. The use of multivariate statistical techniques has become more commonplace largely due to the increasingly...
1. The use of multivariate statistical techniques has become more commonplace largely due to the increasingly complex nature of research designs and related research questions. 2. A study appropriate for multivariate statistical analysis is typically defined as one with several dependent variables (DVs). The basic distinction between experimental and nonexperimental research designs is whether the levels of the independent variable(s) have been manipulated by the 3. 4. In nonexperimental research (eg, descriptive, correlational, survey, or causal- comparative designs), the researcher...
Match the correct kind of statistical test for the data described Options for answers: Dependent T-test,...
Match the correct kind of statistical test for the data described Options for answers: Dependent T-test, Independent T-test, correlation, one-way ANOVA, and two-way ANOVA 1. You are assessing the amount of linear relationship between two continuous variables. 2. You are assessing differences in the averages for two categorical variables. 3. You are looking for group differences on one categorical variable that has more than two groups 4. You are looking for differences in the averages between two groups. 5. You...
6. The most basic statistical test that measures group difference is the T-test. 7. One-way analysis of variance (ANOVA) only determines the significance of group differences and does not identify which groups are significantly different. 8. One-way analysis of covariance (ANCOVA) is similar to ANOVA but additionally controls for a variable that may influence the DV. 9. Factorial analysis of variance (factorial ANOVA) extends ANOVA to research scenarios with two or more IVs that are categorical. 10. Factorial analysis of...
22. Questions that address structure usually distinguish between independent and dependent variables O 2017 Taylor & Francis 23. When investigating the relationship between two or more quantitative variables, the T test is the appropriate test. 24. Prediction of group membership is evaluated by ANOVA, ANCOVA, MANOVA, and MANCOVA 25. Significance of group differences is evaluated by discriminant analysis and logistic regression.
11. One-way multivariate analysis of variance (MANOVA) is utilized to simultaneously study two or more related IVs, while controlling for the correlations among the IVs. 12. One-way multivariate analysis of covariance (MANCOVA) investigates group differences among several IVs, while also controlling for covariates that may influence the DVs 13. Factorial multivariate analysis of variance (factorial MANOVA) extends MANOVA to research scenarios with two or more DVs that are categorical. 14. Factorial multivariate analysis of covariance (MANCOVA) extends factorial MANCOVA to...
1. The use of multivariate statistical techniques has become more commonplace largely due to the increasingly complex nature of research designs and related research questions. 2. A study appropriate for multivariate statistical analysis is typically defined as one with several dependent variables (DVs). The basic distinction between experimental and nonexperimental research designs is whether the levels of the independent variable(s) have been manipulated by the 3. 4. In nonexperimental research (eg, descriptive, correlational, survey, or causal- comparative designs), the researcher...
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