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 R² = 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.