Taltson Lake is in the Canadian Northwest Territories. This lake has many fish. The following data was obtained by two fishermen visiting the lake. Let x = length of a fish in inches and let y = weight in pounds. x (inches) y (pounds) 20 24 36 41 Headings you add to the document appear here. 46 24 7 12 15 34. Find the following values. a. SSxy= b. SSx= C. r d slope= ey-intercept= f. linear regression equation:

Mathematics For Machine Technology
8th Edition
ISBN:9781337798310
Author:Peterson, John.
Publisher:Peterson, John.
Chapter34: Customary Micrometers
Section: Chapter Questions
Problem 56A
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1 I 2 I 3 I 4 5 I 6 I 7
Taltson Lake is in the Canadian Northwest Territories. This lake has many fish. The following data was
obtained by two fishermen visiting the lake. Let x = length of a fish in inches and let y = weight in pounds.
x (inches)
y (pounds)
20
24
36
41
46
Headings you add to the document will
appear here.
2
7
12
15
24
34. Find the following values.
a. SSxy=
b. SSx=
C. r=
d slope=
ey-intercept=
f. linear regression equation:
9. coefficient of determination=
h. The point that must be used to find the y intercept is:
i. The y value when x is 25:
j. Make a scatterplot of the data and insert the line of best fit along with its equation (don't forget titles/labels)
k. calculate the predicted y values, residuals, make the residual plot (don't forget titles/labels), and interpret what
the residual plot tells us:
hp
Transcribed Image Text:1 I 2 I 3 I 4 5 I 6 I 7 Taltson Lake is in the Canadian Northwest Territories. This lake has many fish. The following data was obtained by two fishermen visiting the lake. Let x = length of a fish in inches and let y = weight in pounds. x (inches) y (pounds) 20 24 36 41 46 Headings you add to the document will appear here. 2 7 12 15 24 34. Find the following values. a. SSxy= b. SSx= C. r= d slope= ey-intercept= f. linear regression equation: 9. coefficient of determination= h. The point that must be used to find the y intercept is: i. The y value when x is 25: j. Make a scatterplot of the data and insert the line of best fit along with its equation (don't forget titles/labels) k. calculate the predicted y values, residuals, make the residual plot (don't forget titles/labels), and interpret what the residual plot tells us: hp
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