This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Question 1 a) It is t rue that R 2 measures strength of linear association, but it does not measure whether or not a linear relationship is appropriate for a particular set of data points. So much as one outlier can adjust the R 2 value so that it is higher than what it should be. Therefore, it is incorrect to assume that a linear model is appropriate because of a strong R 2 value. b) Even though it is a natural instinct to assume causation between variables, it is wrong to do so just because there is a strong linear relationship between the two variables. Further study needs to be taken into account as well. c) This is incorrect because it assumed percentages to be whole numbers. If the slope were really 0.2, this would state that an increase by 500% in the literacy rate will cause a $1 billion increase in GDP. 5% should be treated as .05 which makes the slope 20. Question 2 a) Y^= 1.2151 + .003171 X b) The slope indicates that an increase of 1 point on an SAT score will cause GPA to rise by approximately 0.003171. The y intercept indicates that if a GPA to rise by approximately 0....
View
Full
Document
This note was uploaded on 09/01/2011 for the course COMM 291 taught by Professor E.fowler during the Winter '10 term at UBC.
 Winter '10
 E.Fowler

Click to edit the document details