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Job
Satisfaction
7
5
7
6
1
3
3
4
7
4
3
5
1
6
2
2
6
2
6
5
6
6
6
3
7
6
5
2
7
1
5
3
4
1
6
1
1
2
1
5
3
6
5
4
7
Social
Desirability
5
5
5
4
4
5
3
4
4
5
3
6
4
5
2
3
3
4
3
3
6
5
3
4
7
4
4
5
4
3
6
4
6
4
3
5
5
5
3
4
6
5
4
5
5
Job
Performance
6
4
5
5
4
3
4
4
5
3
3
4
1
6
3
5
4
3
4
3
5
7
4
4
7
5
4
3
4
3
6
3
5
1
4
4
4
3
1
4
4
6
6
5
7
6
1
2
7
5
6
3
3
3
3
4
4
2
5
3
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.730724268
R Square
0.533957956
Adjusted R Square
0.51412638
Standard Error
0.982144527
Observations
50
ANOVA
df
Regression
Residual
Total
Intercept
Job Satisfaction
Social Desirability
SS
MS
F
Significance F
2 51.94343 25.97171 26.92464
1.61432E-08
47 45.33657 0.964608
49
97.28
Coefficients Standard Error t Stat
P-value
0.828865307 0.572555 1.447662 0.15435
0.4013548 0.068939 5.82187
5E-07
0.378749208 0.128887 2.938624 0.005096
Lower 95% Upper 95%
-0.32296599 1.980697
0.26266712 0.540042
0.119462816 0.638036
1. What is your Regression Model?
𝐀𝐧𝐬𝐰𝐞𝐫: Job Performance Score = 0.8289 + 0.401 x Job Satisfaction Score + 0.379 x (Social Desirability
2. Interpret the value of the R-square.
Answer: R-squared or coefficient of determination evaluates the scatter of the data points around a fitted regression line. It i
the dependent variable which the model explains. So, R-Square=0.534 signifies that 53.4% of the variation in the Job perform
the regression equation.
3. From your regression model, what is the Job Performance score of an employee given their Job Satisfaction score of 5 and
3?
𝐀𝐧𝐬𝐰𝐞𝐫: 𝐽𝑜𝑏 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 𝑆𝑐𝑜𝑟𝑒 = 0.8289 + 0.401 x 5 + 0.379 x 3 = 𝟑. 𝟗𝟕𝟏𝟗
Lower 95.0%
Upper 95.0%
-0.32297 1.980697
0.262667 0.540042
0.119463 0.638036
Desirability Score)
nd a fitted regression line. It is the percentage variation of
e variation in the Job performance can be explained by
b Satisfaction score of 5 and a Social Desirability score of
Price
795000
399000
545000
909000
109900
324900
192900
215000
999000
319000
350000
249000
299000
235900
348000
314000
399000
599000
299000
425000
1100000
1500000
110000
200000
134900
250000
950000
239950
170000
285000
279000
219000
155000
389000
340000
95000
140000
1100000
360000
415000
250000
559000
525000
779000
595000
1150000
Bedrooms Bathrooms
3
3
4
3
4
3
4
4
3
1
3
3
4
2
3
2
4
3
3
2
3
2
3
2
2
2
3
2
3
2
4
3
4
2
3
3
3
2
3
3
4
3
3
3
2
1
3
2
3
1
4
3
3
4
4
2
3
2
3
2
3
3
3
2
3
2
3
2
3
1
2
1
2
2
3
3
4
3
3
3
4
2
3
3
3
3
3
3
3
2
4
5
Size
2371
2818
3032
3540
1249
1800
1603
1450
3360
1323
1750
1400
1257
1400
1600
1794
1850
2950
1719
1472
4168
3880
1000
1139
1080
2000
1920
1348
1280
2400
1700
1600
1050
1415
1110
797
1100
2602
2351
1350
1206
2628
2365
2990
1750
5500
550000
500000
279000
375000
330000
199000
165000
1399000
255000
325000
789000
498000
430000
539900
499000
275000
499000
899000
1045000
774000
239000
195000
325000
320000
275000
329000
140000
409000
167900
325000
119000
245000
259900
495000
399000
329700
199000
149000
225000
195000
359900
799000
595000
89000
129900
375000
599000
3
3
4
4
3
3
2
4
3
2
3
4
4
4
3
3
3
3
3
2
3
3
2
4
4
3
3
4
3
7
1
4
3
3
4
4
1
3
3
2
3
4
3
3
3
3
3
2
2
3
2
3
3
2
3
2
2
3
3
2
3
2
2
4
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