# Answers to the checkpoints of chapter 7

**Checkpoint 1 **

- Hypotheses about relationships (correlations) between continuous variables.
- The correlation is moderately strong.
- -1 <
*r*< 1. - The more you cycle, the fitter you are. So there is a strong positive correlation.

**Checkpoint 2**

- A correlation is two way; an effect has a direction and it is one way.
- You would use regression analysis if you want to test the effect of one or more variables on a dependent variable and the variables used are continuous.
- The population formula has a residual (referred to as “error” in SPSS) to indicate that your prediction can never be 100% correct.

**Checkpoint 3**

- The constant in the regression equation is the starting point of the regression line. The point on Y where X = 0.
- The regression coefficient gives the direction of the regression line.

**Checkpoint 4**

- The amount of variance in a dependent variable that is explained by the independent variables in the model.
- You can use explained variance to check how well your model “fits.”
- If
*R*^{2}= 0.60, the model is strong. - Observed (
*y*) value minus expected (*y*) value.

**Checkpoint 5**

- Linear effects.
- The test statistic for this is
*t*. - Two-tailed, because there is no direction to the assumption.

**Checkpoint 6**

- The bèta coefficient (
*β*coefficient). - The difference between the
*b*coefficient and the*β*coefficient: the*b*coefficient is unstandardized, each is based on its own scale. This means that*b*coefficients cannot be compared in terms of strength.*β*coefficients, on the other hand, can be compared. Standardization allows for this.