Flashcards in Regression Deck (14)

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1

## How does regression take correlation a step further?

### Regression takes correlation a step further by using information about the association between two variables to predict a dependent variable as a function of an independent variable

2

## What is the simplest mathematical model used in regression?

### Linear function or 'line of best fit'

3

## What is simple regression? Multiple regression?

###
Single: one predictor variable

Multiple: two or more predictor variables

4

## What is the regression line and how is it determined?

###
The linear function that best fits the data (best describes the relationship between predictor and outcome variables )

It is determined by using the method of least squares

5

## What does the least squares procedure do?

### minimizes the sum of the squared deviations (residuals) around the line of best fit

6

## What is the 'residual'

### the distance between a point and the predicted value on the regression line

7

## What is the predicted value?

### the predicted value is actually the mean of all obtained outcome values for a given predictor value

8

## What is Heteroscedastic

### Variability of a predicted value is NOT consistent across different values of the independent variable

9

## What is Homoscedastic

### Variability of a predicted value is consistent across different values of the independent variable

10

## What are the assumptions of regression?

###
(1) variables are normally distributed

(2) best fitting function is linear

(4) homoscedasticity

(4) interval or ratio

11

## What are the Standard error of estimate and R squared and what is the difference between them?

###
Measures of how well a model predicts the observed data

Standard error: absolute measure of the typical distance that the data points fall from the regression line

-> used to calculate confidence intervals

R squared: relative measure of the percentage of the dependent variable variance that the model explains

e.g. this model explains 70% of the variance in variable Y

12

## What does 'regression' to the mean mean?

### Regression has the tendency to predict closer to the mean and away from the extremes (i.e. normally distributed means)

13

## What happens if you restrict the range in a Regression?

### the correlation coefficient will underestimate the true degree of relationship

14