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Non- & Quasi- Experimental
Experimental design
Variables, Controls & Confounds
Stats
Textbook
100
This is the primary reason we use case studies.
What is to: 1) test phenomena impossible to recreate in the lab and 2) find exceptions/contradictions to theories?
100
You p-value reflects this type of error.
What is Type 1?
100
In a classic 2 X 2, how many main effects and interactions are there?
What is 2, 1?
100
What can stats tell you vs not tell you?
What is probability/odds vs. ethics/design?
100
Falsifiability is the idea that a hypothesis can be proven:
What is wrong?
200
Both survey/correlational studies and quasi-experimental studies lack:
What is random assignment?
200
The greater your power, the lower is this type of error.
What is Type 2?
200
In a 2 X 2 X 3 design, how many IVs and cells are there?
What is 3 IVs, and 12 cells?
200
These factors determine your likelihood of getting a significant p value.
What is sample size, effect size, and variability?
200
What is the difference between reliability and internal-validity?
What is consistency of your measure vs. the extent to which your measure accurately captures what you intend?
300
You can either measure development by comparing an existing sample of 3 yo's and 4 yo's or you can take a group of 3 yo's and follow them for a year. This is called ___ vs. ___ design.
What is cross-sectional, longitudinal?
300
What are some disadvantages of within subject design?
What are carryover effects, fatigue, order effects, participant bias?
300
What are general things you should control for?
What is environmental, measurement, grouping and people issues?
300
Give examples of descriptive vs. inferential stats.
What is measures of central tendency vs. t tests/correlations/ANOVAs/regressions, etc.?
300
What is a demand characteristic and how do cover stories relate to them?
What is social desirability concerns, and cover stories alleviate them?
400
Name some classic between-subjects non-equivalent groups.
What is gender, race, culture, SES?
400
Name the 4 types of DVs you can have.
What is continuous, discrete, ordinal, nominal?
400
Define the difference between a confound and a control and give an example of each.
What is a variable that can explain your IV-DV relationship vs. an extraneous variable that you hold constant?
400
Draw a main effect vs. an interaction.
What is a graph that never intersects vs. intersects?
400
1-way, 2-way, 3-way ANOVAs: here, 1, 2, and 3 refer to...
What is number of IVs?
500
Name the different types of survey questions ( and give examples).
What are dichotomous/continuous, closed vs. open-ended?
500
You can have multivariate design by doing either of these.
What is increase the levels of your IV or have more than 1 DV?
500
How can you deal with confounds?
What is pretesting, controlling, or randomizing the confound?
500
Define practical vs. statistical significance.
What is the meaningfulness of your effect (e.g., effect size) vs. p-value?
500
Measuring husbands and wives, siblings, roommates, partners--these would all be cases where a ___ t-test might be appropriate.
What is paired-samples?