STAT 1100Q Chapter Notes - Chapter 5: Quadratic Equation, Scatter Plot
22 May 2018
School
Department
Course
Comparison of Linear and Quadratic Regression Models
Name:________________________________________ Section:___________
The following data presents the growth in worldwide Internet usage from 1995 through 2011:
Year:
1995
1996
1997
1998
1999
2000
2001
No. of
users (in
millions):
16
36
70
147
248
361
533
Year:
2002
2003
2004
2005
2006
2007
2008
No. of
users (in
millions):
597
719
817
1018
1093
1319
1574
Year:
2009
2010
2011
No. of
users (in
millions):
1802
2013
2267
1. Enter the data into L1 and L2 and create a linear model for the data:
a. What is your linear model?___y=-279186+139.8*x________________________
b. What is the slope? _139.8____
c. Interpret the slope within the context of the problem.
If we have 1 unit increase in x then y will go up by 139.8 units. So here in this
problem we have 139.8 more people using internet in the current year then the
previous year.
d. What is the r-value? __0.98_____ What does this tell you about the linear
relationship between x and y?
It seems that x&y have a good positive linear relation.
e. What is the r2 value? What does this tell you about the relationship between x and
y?
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STAT 1100Q Full Course Notes
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Document Summary
The following data presents the growth in worldwide internet usage from 1995 through 2011: _139. 8___: interpret the slope within the context of the problem. If we have 1 unit increase in x then y will go up by 139. 8 units. The (cid:448)alue is 0. 96 (cid:449)hi(cid:272)h sa(cid:455)s that 96% of the (cid:448)aria(cid:271)ilit(cid:455) of o(cid:271)ser(cid:448)ed y(cid:859)s is e(cid:454)plained by the linear regression equation. Do a scatterplot of y1 and the data. What does that tell you about the linear model: store the predictions in l3 and the residuals in l4. It tells that as the residuals are following pattern so this linear model is not working fine: create a quadratic model: y=6. 65*x^2. It says that 99. 7% of the variability of actual y is explained by the quadratic equation: do a scatterplot of y1 and the data. What does that tell you about the quadratic. Store the predictions in l3 and the residuals in l4.
