Data set 2 presents a sample of the number of defective flash drives produced by
ID: 3229084 • Letter: D
Question
Data set 2 presents a sample of the number of defective flash drives produced by a small manufacturing company over the last 30 weeks. Use Excel’s Analysis ToolPak (or any statistical package that you are comfortable with) to compute the regression equation for predicting the number of defective flash drives over time (in weeks), the correlation coefficient r and the coefficient of determination R2. Submit your statistical output from Excel, which should include values for a slope, y-intercept, regression equation, r, and R2. Struggling to get the answer to this data set correct using statistics toolpak in excel. Any help would be appreciated.
Week #Flashdrives 51 61 10 11 12 13 15 16 17 18 19 20 81 21 22 23 24 25 10 26 27 28 29 30 899 75688976 768097876 v676 5 678 9 01234 567890- 12 9 0 1 2 3 4 345678 2 3 14 15 1 1 1 1 2 2 2 222 22223 111 -Explanation / Answer
Answer:
Data set 2 presents a sample of the number of defective flash drives produced by a small manufacturing company over the last 30 weeks. Use Excel’s Analysis ToolPak (or any statistical package that you are comfortable with) to compute the regression equation for predicting the number of defective flash drives over time (in weeks), the correlation coefficient r and the coefficient of determination R2. Submit your statistical output from Excel, which should include values for a slope, y-intercept, regression equation, r, and R2. Struggling to get the answer to this data set correct using statistics toolpak in excel. Any help would be appreciated.
Regression Analysis
r²
0.092
n
30
r
0.303
k
1
Std. Error
1.335
Dep. Var.
flashdrives
ANOVA table
Source
SS
df
MS
F
p-value
Regression
5.0466
1
5.0466
2.83
.1036
Residual
49.9201
28
1.7829
Total
54.9667
29
Regression output
confidence interval
variables
coefficients
std. error
t (df=28)
p-value
95% lower
95% upper
Intercept
6.2989
0.5000
12.597
4.69E-13
5.2746
7.3231
week
0.0474
0.0282
1.682
.1036
-0.0103
0.1051
Regression Analysis
r²
0.092
n
30
r
0.303
k
1
Std. Error
1.335
Dep. Var.
flashdrives
ANOVA table
Source
SS
df
MS
F
p-value
Regression
5.0466
1
5.0466
2.83
.1036
Residual
49.9201
28
1.7829
Total
54.9667
29
Regression output
confidence interval
variables
coefficients
std. error
t (df=28)
p-value
95% lower
95% upper
Intercept
6.2989
0.5000
12.597
4.69E-13
5.2746
7.3231
week
0.0474
0.0282
1.682
.1036
-0.0103
0.1051
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