Which of the following statements is NOT true regarding confirmatory factor analysis (CFA)?

Which of the following statements regarding exploratory factor analysis (EFA) is NOT correct?

Which of the following is NOT one of the primary goals of factor analysis?

What is factor analysis?

T/F: Chi-Square looks to see if two categorical variables are related.

T/F: Sampling error is any error that is due to variance in your sampled group of people.

T/F: Type 2 error is the possibility of rejecting the null hypothesis when the null is actually true.

T/F: Type 1 error is the possibility of rejecting the null hypothesis when the null is actually true.

T/F: Type 2 error is the possibility of failing to reject the null hypothesis.

T/F: Effect size helps readers understand the magnitude of differences found, whereas statistical significance examines whether the findings are likely to be due to chance

T/F: Statistical significance is the final determinant of an effective treatment

Which of the following statements is NOT true regarding Cohen's d?

T/F: the t test rescales the difference between the means into standard error units, while Cohen’s d rescales the same difference between the means into standard deviation units.

T/F: Advantage of scaling over standard deviation in Cohen’s d is that the standard deviation is not materially affected by sample size.

T/F: advantage of scaling over standard error term in t test is that the standard error term is not materially affected by sample size.

The results from a rigorous study must meet three requirements. What are the three requirements?

T/F: Increasing Type I error means accepting a greater chance of making a Type I error.

Wolverine wants to know if his new multivitamins work for humans. He samples 20 participants before giving them his WolveVits and re-evaluates them 4 weeks after the treatment. What type of research design should you use?

Professor P wanted to know if the color of paper had an effect on test scores. On test day, he randomly handed out the tests printed on white paper or blue paper to his students. What research design should you use?

I want to know if the colors in my M&Ms bag match the average colors of M&Ms as stated on their website (e.g., 3 red, 4 blue, etc.). What type of research design should you use?

A botanist wants to determine whether there are any differences in the nesting bird species among avocado trees that were grown using different propagation methods. More specifically, she wants to know if more crows than blue jays prefer making nests in trees that were propagated from leaf cuttings than trees that were propagated from simple layering. What type of research design should you use?

Dr. Y's previous studies suggests that people’s love for animals can predict how likely they are to become vegetarian. However, their research group thinks that the relationship can be explained by how much people love cows. What type of research design should you use?

The average weight for a Pembroke Welsh Corgi living in America is 26 pounds. A concerned citizen wants to weigh a random sample of Corgis to ensure that pet owners are not under-feeding or over-feeding their dogs. What type of research design should you use?

Dr. James is studying nerac (a categorical variable with 2 levels) and neutronium file (a continuous variable) to see how they predict alkali megadestabilazation (a continous variable) and mean-spirited sociality ( a continous variable). What type of research design should you use?

Researchers wanted to know if the amount of ice cream consumed and the time of consumption could improve stress levels. Participants were randomly assigned to eat either 1 scoop, 2 scoops, or none every day for a week. Some were told to eat their ice cream in the morning and others at night. What type of research design should you use?

This analysis tells you if there is a relationship between 2 variables while this analysis between 2 variables tells you if one can predict the other 

A study was done to see if financial status could affect the relationship between happiness and life satisfaction.  What analysis is this example?

This is a test I should use if I only have categorical data.

This is a test I should use if I only have continuous data.

A study done with first year college students want to know if the time they take class and the gender of the professors can impact end of the year grades. Participants were randomly assigned to have classes in the afternoon or in the morning, and if the professors is a female or a male in the first semester. During the second semester participants had their classes in the other time or with opposite gender.

Dr. X conducted a study on a fraternity house to measure the effects of literature read and dinner type on residents satisfaction. Participants were assigned to read a romance or horror book in the first day, and read the opposite book in day two. Participants were also assigned to eat either Italian or Mexican food for both days. Residents satisfaction was measure using a Likert scale. 

An experimenter shows a video to participants about the dangers of SeaWorld. Participants either see Steve Irwin, Jane Goodall, or no celebrity in the video. Afterwards, their willingness to sign a petition is measured. The experimenter wants to know which campaign works best (which produces the highest average willingness to sign the petition)? Or does one campaign work better for females, another for males?

T/F: Analysis of Variance is what ANOVA stands for 

A basketball player only scored 10 points in his game last week. However, this week, he scored closer to his usual performance, around 30 points. This is the name of the statistical phenomenon being described.

T/F: Confounds and artifacts threaten these internal and external validity, respectively

T/F: Regression, ANOVA, t-test, correlation, ANCOVA, and MANOVA all fall under the General linear model

When we increase sample size, power _________, p value _________, and effect size _______.

This is the minumum number of articles I need in order to run a meta-analysis

In FA, this is the name of the plot I should examine to see how many factors I have

T/F: Eigenvalue is the name of the value I look for to see if it is greater than 1 (indicating a separate factor) 

T/F: When comparing models, Delta R2 (change in R2) value specifically tells me if Model 2 is a better fitting model than Model 1

Which is NOT a part of the process of doing a meta-analysis?