I need help with excel. So in the first image is the excel output for my assignm
ID: 3312166 • Letter: I
Question
I need help with excel. So in the first image is the excel output for my assignment. I am trying to get the imformation for the bottom right but have no idea how to. I need it to look like image 2.
Dep. Price Indep.-Mileage Price 6.91 7.06 Mileage 5.2 5.9 6.2 6.7 SUMMARY OUTPUT You MUST follow the CHAP12 sheet in the Excel Templates spreadsheet to receive full credit for your output. This means, among other things that your label formulas must be in cells L1-M1, the Excel output generated by the Data Analysis utod RSquare (Regression) procedure must start in L3, and the ahservations Prediction block of information must start in 24 Multiple R R Squaro .5220 .53 75 Standard Fmor 23.0000 6.97 5.91 5,43 6.17 8.3 8.5 8.4 8.8 ANOVA Regression Residual Total 1.0000 21.0000 22.0000 7.1571 19.0473 26.2050 7,1571 0.9070 7.8507 4.31 9.7 9.8 10.4 10.6 10.4 11.1 4.05 Coefficients Standard Errar tStat P-value Lower 95% Upper 95% Click this button until you are satisfied the dependent variable is in column A and the independent variable is in column B 9.4904 0.9974 9.5026 0.0000 0.5545 6.4062 0.5312 5.2000 0.3052 0.1087 2.8090 0.0105 3.59 5.97 5.49 SE Predicted Valie Cl Lower 95% CI Upper 95% PI PY 11.8 12.8 Lower 95% Upper 95% 7.6000 5.7000Explanation / Answer
Result:
Simple Linear Regression Analysis
Regression Statistics
Multiple R
0.5557
R Square
0.3088
Adjusted R Square
0.2773
Standard Error
1.6875
Observations
24
ANOVA
df
SS
MS
F
Significance F
Regression
1
27.9844
27.9844
9.8266
0.0048
Residual
22
62.6519
2.8478
Total
23
90.6363
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
14.6172
1.8756
7.7931
0.0000
10.7273
18.5070
price
-0.9997
0.3189
-3.1347
0.0048
-1.6611
-0.3383
Predicted values for: mileage
95% Confidence Intervals
95% Prediction Intervals
price
Predicted
lower
upper
lower
upper
Leverage
7.6
7.0193
5.6202
8.4183
3.2502
10.7883
0.160
5.7
8.9187
8.2023
9.6351
5.3464
12.4911
0.042
Simple Linear Regression Analysis
Regression Statistics
Multiple R
0.5557
R Square
0.3088
Adjusted R Square
0.2773
Standard Error
1.6875
Observations
24
ANOVA
df
SS
MS
F
Significance F
Regression
1
27.9844
27.9844
9.8266
0.0048
Residual
22
62.6519
2.8478
Total
23
90.6363
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
14.6172
1.8756
7.7931
0.0000
10.7273
18.5070
price
-0.9997
0.3189
-3.1347
0.0048
-1.6611
-0.3383
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