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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.


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