The measure of the strength of the relationship between two numerical variables.
ID: 3332003 • Letter: T
Question
The measure of the strength of the relationship between two numerical variables.
Simple linear regression
Correlation Coefficient
Logistic Regression Model
Durbin Watson Statistic
Coefficient of Determination
In this design, each participant has two scores on the variable being measured, one collected before, and the second collected after, the experimental treatment.
Two way factorial Z test for the proportion
T-test for dependent means
Chi-Square test for the difference among more than
Two Proportions
Tukey Kramer Method where a single numerical independent variable is used to predict a numerical dependent variable.
Simple linear regression (bivariate)
Logistic Regression
Model Coefficient of Determination
Multiple regression
Variance Inflationary Factor
Used to analyze the differences in means of more than two groups.
Durbin Watson Statistic
One Way Anova
Multiple regression
Tukey Kramer
Wilcoxon Rank Sum Test
Explanation / Answer
Answer to the question is as follows:
1.The measure of the strength of the relationship between two numerical variables.
Correlation Coefficient
2.In this design, each participant has two scores on the variable being measured, one collected before, and the second collected after, the experimental treatment.
T-test for dependent means - A dependent t-test is an example of a "within-subjects" or "repeated-measures" statistical test. This indicates that the same participants are tested more than once.
3.Tukey Kramer Method where a single numerical independent variable is used to predict a
Simple linear regression (bivariate)
4.Used to analyze the differences in means of more than two groups.
One Way Anova
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