Podcast
Questions and Answers
How can causation be shown?
How can causation be shown?
An experimental study in which an independent variable is manipulated to bring about an effect in the dependent variable.
What is the purpose of mediation analyses?
What is the purpose of mediation analyses?
To test a variable as a potential pathway between an independent and dependent variable.
What does correlation determine?
What does correlation determine?
The relationship between two variables.
What is a prediction (regression) equation used for?
What is a prediction (regression) equation used for?
The higher the relationship between two variables, the less accurately you can predict one from the other.
The higher the relationship between two variables, the less accurately you can predict one from the other.
What is perfect correlation?
What is perfect correlation?
What is the significance of a 0.00 relationship?
What is the significance of a 0.00 relationship?
What is the purpose of statistics that test for differences between groups?
What is the purpose of statistics that test for differences between groups?
What are the ways to increase statistical power? (Select all that apply)
What are the ways to increase statistical power? (Select all that apply)
Why is obtaining power in research desirable?
Why is obtaining power in research desirable?
Flashcards
Experimental Study
Experimental Study
A research study where a researcher manipulates an independent variable to observe its effect on a dependent variable, allowing for causation to be shown.
Mediation Analysis
Mediation Analysis
An analytical method used to examine a potential pathway between an independent and dependent variable, seeking to understand how a mediator variable works.
Correlation
Correlation
A statistical measure of the relationship between two variables, not implying causation.
Prediction Equation
Prediction Equation
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Correlation & Prediction
Correlation & Prediction
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Group Differences
Group Differences
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Statistical Power
Statistical Power
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Perfect Correlation
Perfect Correlation
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No Correlation
No Correlation
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Repeated Measures Design
Repeated Measures Design
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Carryover Effect
Carryover Effect
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Independent Samples t-test
Independent Samples t-test
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Dependent Samples t-test
Dependent Samples t-test
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Positive Correlation
Positive Correlation
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Negative Correlation
Negative Correlation
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P-value
P-value
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Power
Power
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Control Group
Control Group
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Parametric Tests
Parametric Tests
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Stratified Sampling
Stratified Sampling
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Convenience Sampling
Convenience Sampling
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Main Effect
Main Effect
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Interaction Effect
Interaction Effect
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Effect Size
Effect Size
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Mediator
Mediator
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Study Notes
Causation in Experimental Studies
- Causation can only be shown in experimental studies where an independent variable is manipulated to affect the dependent variable.
Mediation Analyses
- A method to analyze how a variable can act as a pathway between an independent and dependent variable.
Correlation and Prediction
- Correlation measures the relationship between two variables.
- The stronger the relationship, the more accurately one variable can predict the other.
- Regression equations can be used to predict one variable based on the relationship with other variables
Testing Differences Between Groups
- Statistical tests can determine if groups differ and the strength of the relationship between the independent and dependent variables.
- Perfect correlation is represented as a value of +1.00 or -1.00, while no relationship is 0.00.
- Increasing the difference between group means and decreasing the variance within groups increases statistical power.
- A larger sample size also improves statistical power.
Repeated Measures Designs
- Used to isolate individual differences and increase power.
- Studying phenomena over time with fewer participants.
Carryover Effect
- Refers to the effect of previous conditions on subsequent conditions in an experiment
Hypothesis Testing
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A p-value determines if the observed data is consistent with the null hypothesis.
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Power is the probability of rejecting a false null hypothesis.
Statistical Tests
- Dependent and independent samples t-tests are used to examine differences between groups.
- Positive and negative patterns in variables can indicate a relationship.
- Scattered data points suggest no relationship.
- Curvilinear patterns show an indirect relationship.
Types of Sampling
- Convenience sampling is quick, inexpensive, and easy but has low generalizability.
- Stratified sampling divides a population by characteristics before random selection.
- Effect sizes describe the magnitude of experimental effects.
- Mediators show how one variable influences another.
- Interaction effects show how the influence of one variable depends on another.
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Description
This quiz explores key concepts in experimental studies, including causation, mediation analyses, and the differences between groups. It also delves into correlation and prediction methods, highlighting how variables interact in statistical analyses. Test your understanding of these critical research principles.
