Question

In: Statistics and Probability

Calculate the sample correlation and covariance for (i) Final_exam and assignment_grade; (ii) Final_exam and Tutorial_attend; and...

Calculate the sample correlation and covariance for (i) Final_exam and assignment_grade; (ii) Final_exam and Tutorial_attend; and (iii) assignment_grade and Tutorial_ attend. Once again using Excel formulae without the use of Data Analysis Tool Pack very important the teacher wants us to use hand by hand using excel in a step by step manner: e.g. calculating the sample mean which would be sum (x) /n...

we can't use excel formula that is (=covariance(A..)

please show steps with snipping tool.

Final_exam assignment_grade Tutorial_attend
100 90 5
100 75 5
90 75 5
85 85 5
85 100 5
80 95 5
70 80 5
60 95 5
60 80 5
55 95 5
55 25 4
50 80 5
45 90 5
40 65 5
40 65 4
35 0 3
30 70 4
30 55 4
25 85 5
25 90 4
15 5 3
15 80 5
15 50 5
15 45 3
5 75 3
5 70 4
100 100 5
95 75 5
90 100 5
85 85 5
80 95 5
70 45 5
70 100 5
65 90 5
60 100 5
55 65 4
55 90 5
55 80 4
50 50 5
45 50 4
45 75 3
40 75 5
40 70 5
35 90 4
30 95 5
30 55 5
25 75 4
25 20 3
25 65 2
15 60 4
15 60 4
15 80 5
10 55 4
10 80 2
0 0 2

Solutions

Expert Solution

a)

Final_exam   assignment_grade

sample size , n    = 55
here,   x̅   = Σx / n= 46.64             ,       ȳ = Σy/n = 70.91
ΣX ΣY Σ(x-x̅)² Σ(y-ȳ)² Σ(x-x̅)(y-ȳ)
total sum 2565 3900 43402.72727 33504.5 17993.18
mean 46.64 70.91 SSxx SSyy SSxy

correlation coefficient ,    r = Sxy/√(Sx.Sy) =   0.4718

covariance=Σ(x-x̅)(y-ȳ) / (n-1) =   17993.1818/54=   333.207

.........................

Final_exam Tutorial_attend

sample size , n    = 55
here,   x̅   = Σx / n= 46.64             ,       ȳ = Σy/n = 4.36
ΣX ΣY Σ(x-x̅)² Σ(y-ȳ)² Σ(x-x̅)(y-ȳ)
total sum 2565 240 43402.72727 42.7 807.27
mean 46.64 4.36 SSxx SSyy SSxy

correlation coefficient ,    r = Sxy/√(Sx.Sy) =   0.5928
covariance=Σ(x-x̅)(y-ȳ) / (n-1) =   807.2727/54=   14.9495

................

assignment_grade   Tutorial_attend

sample size , n    = 55
here,   x̅   = Σx / n= 70.91             ,       ȳ = Σy/n = 4.36
ΣX ΣY Σ(x-x̅)² Σ(y-ȳ)² Σ(x-x̅)(y-ȳ)
total sum 3900 240 33504.54545 42.7 696.82
mean 70.91 4.36 SSxx SSyy SSxy

correlation coefficient ,    r = Sxy/√(Sx.Sy) =   0.5824
covariance=Σ(x-x̅)(y-ȳ) / (n-1) =   696.8182/54=   12.904

....................


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