Which of the following is an assumption of between-subjects analysis of variance?
homogeneity of variance
chi square distribution of populations
What can we conclude in an ANOVA if MSB = MSE (so F=1)?
a treatment effect occurred
too few subjects were sampled
reject the null hypothesis, conclude that the population means are different
do not reject the null hypothesis that the population means are equal
If relationship success is correlated with extroversion at r = .6, what proportion of the variance in relationship success is explained by extroversion?
The proportion of the variance in Y explained by (or associated with) the variance in X
All else equal, a within-subjects ANOVA has more _______ than a between-subjects ANOVA.
If we do not reject the null hypothesis in a one-factor ANOVA we can conclude:
At least one of the population means is different from at least one other population mean
Precisely which of the levels differ from which other levels
The evidence does not allow us to conclude that any of the means differ.
Every sample mean is different from each other sample mean
All of the population means are equal
If the effect of factor A differs across levels of factor B then there is __________.
A simple effect
For which of the following would a 2-way (Goodness of Fit) Chi-square (χ2) test be appropriate?
(Hint: Think about the scale that each variable is measured on. What scale of measurement is the χ2 used for?)
If the problem is to determine whether there is a relationship between math test scores and enrollment in an after school program.
If the problem is to determine whether there is a relationship between amount of water consumed and time to finish the race.
If the problem is to determine whether there is a relationship between occupation and average score on the Beck Depression Inventory (an interval scale measure of depression).
If the problem is to determine whether there is a relationship between religious affiliation and who a person voted for in the last presidential election.
A researcher was interested in how education and teaching style affects children’s learning. He classified 40 teachers on their level of education (bachelors degree, master’s degree) and their teaching style (lecture, hands-on), and he measured the average progress of each of their classes for a year. He conducted a 2-way ANOVA and found a significant interaction. What can he conclude from this result?
People with bachelors degrees are better teachers than people with masters degrees.
Hands-on teaching is more effective than lecture.
The effectiveness of teaching style depends on the teacher’s level of education.
He cannot draw any conclusions.
What effect is present in the graph below?
Main effect of factor B
Main effect of factor A AND an interaction
Main effect of factor A