1. For the x-independent and y-dependent variables listed below,
No.
1
2
3
4
5
6
7
8
9
10
x
39
43
21
64
57
47
28
75
34
52
y
65
78
52
82
92
89
73
98
56
75
a)
b)
c)
d)
e)
f)
g)
h)
i)
Calculate the mean of x and y.
Calculate Σxi2, Σyi2 , and Σ xi yi.
Estimate the slope (m) and intercept (c) by the least squares method.
Plot the data points and the regression lines
What is the residual value when x = 47?
What is the sum of squares for error?
What is the degree of the freedom?
Calculate the variance of the data.
Determine whether a linear relationship exists between x and y by using the null
hypothesis.
j) Find a 95 percent confidence interval for c based on the data.
k) Find a 95 percent confidence interval for the expected value of y at x = 50.
l) Calculate the correlation coefficient.
2. The data in the table-below give the moisture contents of samples in a core taken from a
small inlet on the Gulf Coast in eastern Virginia. The measurements were taken immediately
after the samples were removed from the core barrel and forced dried.
Depth (ft)
0.1000
0.2000
0.3000
0.4000
0.5000
0.6000
0.7000
0.8000
0.9000
1.0000
1.1000
1.2000
1.3000
1.4000
1.5000
1.6000
1.7000
1.8000
1.9000
2.0000
a)
b)
c)
d)
e)
f)
Moisture
(gram/kg dried solid)
12.7167
12.8760
12.5019
12.9697
12.4105
13.3901
12.8671
13.0331
13.8288
13.8373
13.3454
13.2790
14.1562
13.3807
13.3112
13.4038
12.6431
12.3180
11.2649
11.3883
Perform least squares linear regression on this data.
Plot the data and linear regression model.
Does the model fit the data?
Use ANOVA to quantify (c) above.
Calculate the correlation coefficient.
What model would you recommend for fitting the data?
