# Analysis of Manufacturing Industries in Terms of Employees, Sales, and Revenue

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Results and discussions
There are 150 manufacturing industries and each industry is labeled in numbers for example
8,18,10,11 etc. The data also indicate the period the industries have been operating and we
realize that most industries have been operating for four years. From our data in excel we notice
that the number of males for both industries owners and managers were more than the number of
managers and owners who were females.
ACTUALNumberEmploy
ees
%SalesLocal
%SuppLoc
GrossRevenue
Mean
30.026
67 Mean 61.54 Mean 47.2 Mean
Standard Error
4.3988
1 Standard Error
2.9564
87 Standard Error
3.0297
7 Standard Erro
Median 8 Median 79 Median 50 Median
Mode 1 Mode 100 Mode 0 Mode
Standard Deviation
53.874
19 Standard Deviation
36.209
43 Standard Deviation
37.106
96 Standard Dev
Sample Variance
2902.4
29 Sample Variance
1311.1
23 Sample Variance
1376.9
26 Sample Varia
Kurtosis
9.7379
57 Kurtosis -1.2866 Kurtosis
-
1.5623
3 Kurtosis
Skewness
3.0195
12 Skewness
-
0.5357
7 Skewness
0.0871
17 Skewness
Range 307 Range 100 Range 100 Range
Minimum 1 Minimum 0 Minimum 0 Minimum
Maximum 308 Maximum 100 Maximum 100 Maximum
Sum 4504 Sum 9231 Sum 7080 Sum
Count 150 Count 150 Count 150 Count
Confidence
Level(95.0%)
8.6921
06
Confidence
Level(95.0%)
5.8420
58
Confidence
Level(95.0%)
5.9868
66
Confidence
Level(95.0%)
Table 1
From Table 1 above we observe that most industries have employed 30 people averagely and
again the mean of percentage of sales generated from these industries is approximately 62 and
the percentage mean of supplies purchased from these industries are 47. The mean for the gross
revenue is \$2991.25 and that for annual salary is \$82.1. The minimum number of employees is 1
and the maximum is 308. On the managers ages the minimum is 18 years and the maximum is 77
years.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.5910
59
R Square
0.3493
51
Square
0.3267
59
Standard
Error
11.328
62
Observations 150
ANOVA
df
SS
MS
F
Significanc
e F
Regressi
on 5
9922.7
24
1984.5
45
15.463
47 3.68E-12
Residual 144
18480.
61
128.33
76
Total 149
28403.
33
Coefficie
nts
Standar
d Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
11.7829
4
5.4266
38
2.1713
14
0.0315
45
1.0567
78
22.509
09
1.0567
78
22.509
09
ACTUALNumberEmployee
s
0.19679
8
0.1095
72
1.7960
66
0.0745
81
-
0.0197
8
0.4133
75
-
0.0197
8
0.4133
75
%SalesLocal
0.00572
7
0.0268
95
0.2129
57
0.8316
62
-
0.0474
3
0.0588
87
-
0.0474
3
0.0588
87
%SuppLoc
0.02019
5
0.0260
97
0.7738
31
0.4402
99
-
0.0313
9
0.0717
78
-
0.0313
9
0.0717
78
GrossRevenue(\$'000) -0.00233
0.0010
63 -2.1921
0.0299
78
-
0.0044
3
-
0.0002
3
-
0.0044
3
-
0.0002
3
ManagerAnnualSalary(\$'0
00)
0.44153
7
0.0651
55
6.7767
53
2.92E-
10
0.3127
54
0.5703
21
0.3127
54
0.5703
21
Table 2

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