1986
6.914266
1987
7.002957
1988
7.798921
1989
9.273581
1990
8.255382
1991
5.939953
1992
3.747256
1993
3.194261
1994
4.457833
1995
5.969845
1996
5.450182
1997
5.641893
1998
5.570281
1999
5.232833
2000
6.41915
2001
3.88868
2002
1.774069
2003
1.209925
2004
1.495331
2005
3.381748
2006
5.094795
2007
5.250115
2008
2.682669
2009
0.335605
2010
0.27298
2011
0.231861
2012
0.236032
Plot these data on a scatterplot with the interest rates on the y-axis and the years on the x-axis. Include the scatterplot in below. Describe what you see, including the form, direction, strength, and any outliers.
Perform a linear regression with the interest rate as the response variable and the year as the predictor variable. Give the equation and the r-squared statistic for the line.
Explain what the slope means about interest rates.
For the linear regression, create a normal plot of the residuals, a plot of the residuals vs. the fits, and a plot of the residuals in time order. Explain any patterns that you see.
Give the p-value for the linear regression. Explain what this means about the relationship between interest rates and years.
Choose a subset of at least 3 consecutive years from these data that would show a positive linear relationship. Plot them and give the resulting equation and r-squared value.
7. Facts about correlation. Answer the following questions about correlation (r).
a) What is the strongest the correlation can ever be? _____
b) If there is no relationship, r is equal to __________.
c) The correlation coefficient ranges from ________ to _______.
d) If the points fall in an almost perfect, negative linear pattern, r is close to: _____
e) If the points fall in an almost perfect, positive linear pattern, r is close to: _____
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