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33 Cards in this Set

  • Front
  • Back

Negative Correlation

As one variable increases, the other decreases

Positive Correlation

As one variable increases, the other increases

No relationship vs Curvilinear

Both give r=0

Curvilinear actually has a relationship though

Types Of Regression



Linear Regression

Assumes that increasing or decreasing one variable changes the value of the other

Can look not only at the relationship, but also the r2

Multiple Regression

Simply means you have more than one predictor

So instead of just study time, you would also think that intelligence can influence test performance


a study that has at least one IV and one DV

IV is also called?

A factor

Types of IV





Changing something physically in the environment


Changing the instructions before a study

Participants do the same task, the only difference is the instructions beforehand


Changing physical aspects within the participants


Injecting a drug

Giving participants sugary drinks

How to know iv had an effect

Compare it to something

Another IV


Subject Variables

Particular Demographics

Any relevant facts about our participants

Typical;y, we ask standard demos but may add others depending on what we think matter

What Makes A Good Experiment

1) At least one IV

2) The researcher must have adequate power

3) The experimenter must try to control all extraneous variables

What Can Threaten Internal Validity

- Biased assignment

- Differential attrition

- History effects

- Demand characteristics

- Experimenter expectancy effects

- Placebo effects

One-Way Designs

-Only one IV is manipulated

- Minimum number of conditions is 2

- Experimental vs control

- Experimental vs experimental

3 Types of Participant Assignment

Randomized group design (between-subjects)

Repeated measures design (within-subjects)

Matched-subjects design

Randomized Group Designs

Between-subjects design

We examine behaviors between different conditions

Conditions are based on how many ways you manipulate the IV

Test each participant only once

Repeated Measures Design


Interested in examining differences in behavior over time

Each participant is measured two or more times after the IV

Order effects


Practice effects


Helps counteract order effects

If you have more than 2 DV's you need to create every order possible

Randomizing order over computer is another way that tends to be easier

Matched Subjects Design

A design in which participants are matched based on particular variable and then put into conditions

Factorial Designs

When two or more IVs are manipulated

Mixed Factorial Design

Participants have within and between measures

Quasi-experimental designs

Pretest-posttest designs

Time series designs

Longitudinal Designs


An experiment is considered quasi when

The researcher is not able to randomly assign participants to conditions or The researcher is unable to manipulate the variable of interest


These type of designs allow us to have multiple measurements of the dependent variable

Tests before and after IV

Tells us how much the IV changed the DV

Simple interrupted Time Series

Measure the DV multiple times before and after the IV happens

Control Group Interrupted Time Series

Measure multiple groups, multiple times before and after the IV

Longitudinal Designs

Used to examine developmental effects

Used to evaluate programs to see if they have long-term impact to its participants

Longitudinal vs Cross-sectional

Longitudinal uses the same people over time

Cross-Sectional compares different groups of people at different ages

Cross-sequential cohort design

Different groups of people at different ages over time