Podcast
Questions and Answers
What is the major advantage of ANOVA?
What is the major advantage of ANOVA?
- It can only be used with an independent measure design
- It can evaluate mean differences between two or more treatments (correct)
- It tests specific differences among means
- It is named after Sir Ronald Fisher
What are the factors in ANOVA often referred to as?
What are the factors in ANOVA often referred to as?
- Repetitive variables
- Categorical variables (correct)
- Experimental variables
- Specific variables
Why are ANOVAs sometimes called F-tests?
Why are ANOVAs sometimes called F-tests?
- Because they compute a test statistic called F (correct)
- Because they are named after Sir Ronald Fisher
- Because they are only used with a repeated measure design
- Because they are based on specific differences among means
What does the F statistic in ANOVA represent?
What does the F statistic in ANOVA represent?
In factorial design ANOVA, what does Factor 1 represent?
In factorial design ANOVA, what does Factor 1 represent?
What can ANOVA be used to evaluate in a research study involving more than one factor?
What can ANOVA be used to evaluate in a research study involving more than one factor?
What is the purpose of the alternative hypothesis (H1)?
What is the purpose of the alternative hypothesis (H1)?
What is homoscedasticity in statistical terms?
What is homoscedasticity in statistical terms?
What does the between-treatments variance measure?
What does the between-treatments variance measure?
What does the within-treatments variance provide a measure of?
What does the within-treatments variance provide a measure of?
What is the overall goal of ANOVA?
What is the overall goal of ANOVA?
What is a possible explanation for the difference that exists between treatments?
What is a possible explanation for the difference that exists between treatments?
What does the within-treatments variance measure?
What does the within-treatments variance measure?
What is an important assumption shared by many parametric statistical methods?
What is an important assumption shared by many parametric statistical methods?
What does the null hypothesis (H0) state?
What does the null hypothesis (H0) state?
What does H1 state?
What does H1 state?
Correlation measures the relationship between three variables.
Correlation measures the relationship between three variables.
A scatter plot helps visualize patterns or trends in data.
A scatter plot helps visualize patterns or trends in data.
Correlation can only measure straight-line relationships.
Correlation can only measure straight-line relationships.
The direction of the relationship in correlation can be positive or negative.
The direction of the relationship in correlation can be positive or negative.
Correlation measures the consistency of the relationship between variables.
Correlation measures the consistency of the relationship between variables.
Correlation requires two scores for each individual, typically identified as X and Y.
Correlation requires two scores for each individual, typically identified as X and Y.
A perfect correlation is always identified by a correlation of 1.00.
A perfect correlation is always identified by a correlation of 1.00.
A correlation of 0 indicates a perfectly consistent relationship.
A correlation of 0 indicates a perfectly consistent relationship.
The sign and the strength of a correlation are dependent on each other.
The sign and the strength of a correlation are dependent on each other.
The Pearson correlation coefficient is used with ranked or ordinal-scaled data.
The Pearson correlation coefficient is used with ranked or ordinal-scaled data.
A positive correlation means that individuals who score high on X also tend to score high on Y.
A positive correlation means that individuals who score high on X also tend to score high on Y.
The value for SP is used to measure variability for a single variable.
The value for SP is used to measure variability for a single variable.
The Pearson correlation measures the relationship between an individual’s location in the X distribution and his or her location in the Y distribution.
The Pearson correlation measures the relationship between an individual’s location in the X distribution and his or her location in the Y distribution.
If two variables are known to be related in some systematic way, it is not possible to use one for prediction.
If two variables are known to be related in some systematic way, it is not possible to use one for prediction.
The Pearson correlation can be used to measure the amount of covariability between two variables.
The Pearson correlation can be used to measure the amount of covariability between two variables.
A negative correlation indicates that individuals with high X scores tend to have high Y scores.
A negative correlation indicates that individuals with high X scores tend to have high Y scores.
