Analyzing Student Internet Usage and Travel Time: A Statistical Report

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Business Management and Statistics
1

Contents
Executive Summary................................................................................................................................3
Introduction.............................................................................................................................................4
Task 1......................................................................................................................................................5
Task 2......................................................................................................................................................6
Task 3....................................................................................................................................................10
Conclusion............................................................................................................................................13
References.............................................................................................................................................14
2

Executive Summary
While pursuing business operations, one finds multiple factors or things which
influence the productivity. To ascertain the value of the dominant factor, various tools
are used. Statistics is one such tool, which is applied in business and management.
There are various factors which affect the dependency of one variable over the other.
Statistics determine the relationship between these factors or variables and henceforth
present a report stating the entire life cycle of the product. By applying various
Statistical tools and techniques, we determine the importance of the product or
applicability of the product (in terms of business) in real life. In this report, we will
analyze how much time the students of Coventry University spend on internet, and
whether this influences their time to go from accommodation to University campus.
We will also investigate how factors like gender, type, and age of the student
influence their choice of stay (hostel, paying guest), while they are studying. We have
conducted linear regression analysis to analyze the relationship between two variables
which are total internet time and the duration between the accommodation to
university.
3

Introduction
Statistics is that part of mathematics analysis that uses models, interpretations,
synopses and representations to present a given set of data. Statistics implies various
methodologies to conclude data. Statistics play an important role in Business
Management. It helps the management to make swift decisions by using statistical
techniques like trend analysis, data sampling, co-relation of variance to discover
potential business ventures and establish comparisons between existing company
practices. It is also used for the analysis of quality, financial data, operations, and
production.
Statistics play an important role in decision making. There are various methods of
statistics to interpret the data. Few of those are:
1. Mean
2. Regression Analysis
3. Skewness
4. Kurtosis
5. Standard Deviation
6. Variance
The use of statistical techniques helps in finding a relation between two variables. The
industry that produces subsidiary products uses statistical tools to determine the
market share. This helps them in deciding whether or not to produce the goods.
Use of statistics can be stated in the points below:
 Proving the relationship between variables.
 Focusing on long term goals.
 Directing growth.
 Research and Development of Product.
4

Task 1
Conduct linear regression analysis
After analyzing the facts, the following regression analysis was produced.
Regression Statistics
Multiple R 0.2249379799
R Square 0.05059709482
Adjusted R Square 0.04422526324
Standard Error 31.11011663
Observations 151
ANOVA
df SS MS F Significance F
Regressio
n 1 7685.366304 7685.366304 7.940745797 0.005489826428
Residual
14
9 144208.0642 967.8393568
Total
15
0 151893.4305
Coeff
icient
s
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
47.21
2754
67
3.91222
7207
12.067
99917 0
39.4821
4216
54.94336
718
39.4821
4216
54.94336
718
Duration
On A
Compute
r?
-
0.093
8078
1693
0.03328
958511
-
2.8179
32894
0.005489
826428
-
0.15958
84758
-
0.028027
15806
-
0.15958
84758
-
0.028027
15806
Analysis
. After applying the tests, it was found that:
Multiple R The value of Multiple R is 0.2249379799. It is the correlation coefficient.
This measures the linear relationship between two variables. Here, 0.2249 indicates
that both the variables are not much correlated. Surfing on internet does not affect the
travel period to reach the campus.
5

Task 2
1.
The relationship between the two variables has no co-relation, as the scatterplot does
not show any pattern.
6

2.
The Regression Equation is derived after the formation of a scatter plot. As per the
scatter plot above, the regression Equation is
Regression Equation= Y= 0.5394x + 110.53
3.
The slope of a regression line indicates the rate of change in variable y when there is
a change in variable x. Here, we can see that are variables are not much dependent on
each factor.
7

4.
Intercept The intercept or also known as constant is the expected mean value of
variable Y, when the value of X is 0.
Coeff
icient
s
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
47.21
2754
67
3.91222
7207
12.067
99917 0
39.4821
4216
54.94336
718
39.4821
4216
54.94336
718
8

5.
R-Squared Value: R-squared Value is the method of measuring the dependability of
the variance of one variable over the second variable. The R-Squared values range
from 0-1. The R-squared value of the regression analysis is 0.506. This indicates that
there is less variability between the two models.
6.
It is difficult to say that internet surfing period can increase or decrease the time
travelling from hostel to university campus. Therefore, this relationship cannot be
calculated, as both the variables are independent, and the time spent on the internet
doesn't affect the time taken from student accommodation to Coventry University.
7.
No, the variables in the regression model are not statistically significant to the model
because both the variables are independent in nature. They are not dependent on each
other. Change in one variable does not affect the other variable. The variables do not
present a pattern in the scatterplot, which clearly indicates that the relationship has no
correlation.
9

Task 3
1.
2.
3.
10

Path Path
No.
Duration (Days)
1-2-3-5-6-8-9-10-11-
12
1 26
1-2-3-6-8-9-10-11-12 2 22
1-2-4-7-8-9-10-11-12 3 24
1-2-4-7-10-11-12 4 18
As per the solution above, 1st Path is the Critical Path as it takes longest to
complete.
4.
Activi
ty
Durati
on
Earl
y
Star
t
Tim
e
Earl
y
Finis
h
Tim
e
Lat
e
Star
t
Tim
e
Late
Finis
h
Tim
e
Fre
e
Flo
at
Interferi
ng Float
Independ
ent Float
Tot
al
Floa
t
A 5 0 5 0 5 0 0 0 0
B 3 5 8 5 8 0 0 0 0
C 2 8 10 12 14 4 0 0 4
D 7 5 12 7 14 0 0 2 2
E 6 8 14 8 14 0 0 0 0
F 2 14 16 14 16 0 0 0 0
G 2 12 14 14 16 0 0 2 2
H 2 16 18 16 18 0 0 0 0
I 6 18 24 18 24 0 0 0 0
J 2 14 16 22 24 8 0 0 8
K 2 24 26 24 26 0 0 0 0
L 0 26 26 26 26 0 0 0 0
Total 12 0 4 16
Free Float: Late Start Time – Late Start Time
Free Float: Early Start Time of Next Activity – Early Finish Time of Current
Activity
Independent Float: Total Float – Free Float
11

5.
Time taken by the critical path is also termed as the Total Duration of the Project i.e.
26 days.
12