If the coefficient of determination is high, the,
- A high amount of the variation in the response variable is determined by variation in the Explanatory
- Tells us how well the statistical model, (Linear Model or otherwise) predicts an outcome The variation thats explaned in the Response Variable by the variation in the Explanatory Variable.
What should be discussed when using
- Strength
- If Linear model is appropriate
- % of Response variation explaiend by Explanatory variation
Interpret Template
If
, we write that: 47% of the variation in {Response Variable}, can be explained by the variation in {Explanatory Variable}
Question 1 -
Calculate the coefficient of determination
Calculator Image r^2 = 0.61 = 61% The Coefficient of Determination is 61%
Interpret the coefficient of determination
62% of variation in # Of Drinks sold can be explained by variation in temperature
State the regression line that models this data
y=-2.01x+100.77
Is this model appropriate? Wy or why not?
Yes this model is appropriate, it represents 61% of the data.
Question 2a - Calculate the coefficient of determination from Pearson's Correlation Coefficient if r= 0.6
?
B)
If r=-0.95
Question 3 - If
, and the least squares regression line equation is:
A) Interpret the coefficient of determination
88% of variation in sleeping time is explained by Age
**Calculate Pearson’s Correlation Coefficient
(Negative due to least square regression line having ve gradient)