Flashcards in Lecture 11 definitions Deck (10):

1

## Regression coefficients (b and β)

### Indicates the effect of the IV on the DV. Specifically, for each unit change of the IV, there is an expected change equal to the size of b or β in the DV.

2

## b

### Unstandardized regression coefficient indicates the strength of relationship between a given predictor, I, of many and an outcome in the units of measurement of the predictor. It is the change in the outcome associated with a unit change in the predictor.

3

## β

### Standardized regression coefficient. Indicates the strength of relationship between a given predictor, I, of many and an outcome in a standardized form. It is the change in the outcome (in standard deviations) associated with a one standard deviation change in the predictor.

4

## F-ratio

### A test statistic with a known probability distribution (the F-distribution). It is the ratio of the average variability in the data that a given model can explain to the average variability unexplained by the same model. It is used to test the overall fit of the model in simple regression and multiple regression, and to test for overall differences between group means in experiments.

5

## Outcome variable

### A variable whose values we are trying to predict from one or more predictor variables.

6

## Predictor variable

### A variable that is used to try to predict values of another variable known as an outcome variable.

7

## Predicted value

### The value of an outcome variable based on specific values of the predictor variable or variables being placed into a statistical model.

8

## Residual

### The difference between the value a model predicts and the value observed in the data on which the model is based. Basically, an error. When the residual is calculated for each observation in a data set, the resulting collection is referred to as the residuals.

9

## Simple regression

### A linear model in which one variable or outcome is predicted from a single predictor variable (Do we need to know the model/ formula?).

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