Lecture 4: Research Questions for Predictions I Flashcards
What are the rules for associations?
- Statement ending in a question mark
- All relevant constructs included
- Indicated relevant population
- Use “predict” as the driving word
*What is a variation?
The total amount of variability in a distribution of scores from the mean. It is measured by the sum of squared deviation scores (sum of squares).
*What is variance?
The average sums of squares in a distribution of scores (both in population and samples). It is expressed in a squared metric, relative to the scores on which it is calculated.
*What is a standard deviation?
The square root of variance (both in populations and samples).
What is the difference between a correlation and a regression?
A correlation defines a symmetrical relationship, where a regression defines an asymmetrical relationship (X and Y axis matters).
What is a correlation?
The standardised covariance calculated by knowing the SD.
What is a covariance?
An unstandardised measure of the strength and direction of the association between scores on two variables.
What is a linear regression line?
The line of best fit.
How are regression parameters estimated?
Using the ordinary least squares (OLS) estimator.
What is the difference between a simple linear regression model and a multiple linear regression model?
A multiple linear regression model can contain more than one independent variable, and the correlation among the IVs is partial led out.
What is the intercept in a linear regression model?
The predicted value on the dependent variable (Y-axis) when the score on the independent variable (X-axis) is zero.
