In a repeated measure design, uD is sometimes equal to 0
F
A repeated measures design can be used to study changes over time
T
A researcher would like to compare before and after effects of a treatment with 30 sets of scores. This means the study will require 60 participants.
F
The null hypothesis in an ANOVA states that all of the group means are unequal.
F
F-ratios are always greater than or equal to zero
T
The distribution of F ratios is negatively skewed
F
An F ratio near 1.0 is an indication that the null hypothesis is likely to be true
T
SSbetween measures each sample variance
F
For an ANOVA, comparing four groups, dfbetween = 3
T
For an ANOVA, comparing three groups with 10 in each group, dftotal = 29
T
A negative correlation means that increases in one variable tend to be accompanied by increases in the other variable.
F
If the value of the correlation is r = -1.0, then all data points in a scatter plot fit perfectly on a straight line
T
A correlation of r = -0.90 indicates that the data points are clustered close to a line that slopes (points) up to the right
F
Correlation = Causation
F
The value of a correlation ranges from -1.0 to +1.0
T
If data points in a scatter plot are clumped together, then the correlation is near zero.
T
A value of r = -0.95 means that there is a strong relationship between two variables
T
The number of hours a person exercises and their gender is an example of a bivariate relationship
F
A researcher obtains a correlation of r = -0.41 between the amount of time each student studies for exam and their exam score. This means that people who studied more got better grades.
F
A correlation of r = 0.70 is stronger than a correlation of r = -0.80
F
The larger the difference among the sample means, the larger the numerator of the F-ratio will be
T
In an ANOVA, post hoc tests are only needed if H? is rejected and there are more than 2 groups
T
The Bonferroni test helps to reduce Type II Error
F
As the number of comparisons increases, Type I Error decreases
F
If an F ratio is equal to 25, then the t-statistic would be equal to 5
T
In ANOVA, MS values measure sample variance
T
The shape of the F distribution depends on the degrees of freedom (df)
T
An interaction examines the effect of one IV averaged across the levels of another IV
F
In a two-way anova, two hypothesis are tested
F
In a two-way ANOVA, there are two dependent variable
F
The SP determines the sign of the correlation
T
The correlation df formula is n-1
F
Homoscedasticity is a factor that affects correlations
F
In regression, error assesses the difference between predicted values and actual values
T
If a correlation coefficient is 0.40, then the coefficient of determination would be 0.20
F
In the linear equation, Y = bX + a, a indicates the X-intercept
F
The regression line indicates the center of the data
T
In regression, the slope determines the direction of the relationship
T
Regression is used to make predictions
T