PART A
QUESTION 1
a. i
Discrete variable is defined as variables with a limited number of possible
values There are no continuous qualitative variables. Some quantitative variables,
such as performance ratings of 1,2,3,4, or 5, and temperature rounded to the nearest
degree, are discrete. For practical purposes, a variable that takes on enough discrete
values can be deemed continuous. Time to the closest millisecond is one example
(Chakraborty and Chakravarty, 2012).
ii
According to Thompson (2015) a postal survey is a quantitative data gathering
approach in which potential participants are handed paper questionnaires by mail
and must complete the questions themselves. For example, self-administered and
returned to the survey organisation by mail.
iii
Snowball sampling is where research participants enlist the help of other people
to take part in a test or study. It's employed when finding potential participants is
difficult. Snowball sampling is named for the fact that as the ball starts rolling, it
gathers up more "snow" along the way and grows larger and larger. A nonprobability sampling approach is snowball sampling (Etter and Perneger, 2010).
1 (b)
According to Bryman and Bell (2013) primary data is information gathered for
the first time from personal experiences or proof, usually for study purposes. It's also
known as unprocessed data or firsthand information. Secondary data, on the other hand,
is information that has previously been collected and documented by some researchers
for their own purposes, rather than the current research problem. It is available in the
form of data gathered from a variety of sources, including government publications,
censuses, organisational internal records, books, journal articles, websites, and reports,
among others (Harris, 2011).
A major disadvantage of using secondary data is that it may not provide
particular answers to the researcher's study questions or contain information that the
researcher requires (Heaton, 2018). Furthermore, because the data was not collected by
the researcher, they have no control over what is contained in the data collection. This
can often limit the study or change the original questions the researcher was attempting
to address. Another key disadvantage of using secondary data is that the researcher has
no idea how or how well the data collection process was carried out (Boslaugh, 2017).
c
(i)
The population from the above information was 102 customers whereas the
sample could be the selected randomly of 10 officers which consider a group of
member or individuals participate in the study.
(ii)
Variable of interest is a tentative study which change the quantity that measured.
Basically, its is factor of the study
(iii)
Simple random sampling one of the best probability sampling techniques that
assist to saving time and resources, Moreover, Systematic sampling could be
the best method also consider least time consuming
(iv)
Random sampling method will be the best method. The benefit of random
sampling method is lack of bias. The disadvantage of the method is difficulty accessing
lists of the full population
QUESTION 2
a)
No of classes
b)
2^k>n
2^k>60
32
128
7
100
89
111
97
102
110
111
92
103
112
111
99
88
92
107
102
97
98
80
91
130
98
120
104
113
103
111
87
89
102
99
110
121
90
92
89
99
97
117
88
111
97
110
101
96
99
99
100
122
104
111
100
95
94
88
115
104
106
100
111
80
87
88
88
88
89
89
89
90
91
92
92
92
94
95
96
97
97
97
97
98
98
99
99
99
99
99
100
100
100
100
101
102
102
102
103
103
104
104
104
106
107
110
110
110
111
111
111
111
111
111
111
112
113
115
117
120
121
122
130
Range
Highest -lowest
50
c)
Class Interval =
d)
Total
e)
Class size= range/class interval
7.1429
Frequency Class Interval Midpoint CF
RF
F
LL
UL
(X)
CF
RF
1
80
86
83
1
0.02
12
87
93
90
13
0.20
18
94
100
97
31
0.30
11
101
107
104
42
0.18
12
108
114
111
54
0.20
4
115
121
118
58
0.07
2
122
130
126
60
0.03
60
Class Interval
80 - 86
87 - 93
94 - 100
101 - 107
108 - 114
115 -121
122 - 130
Frequency
1
12
18
11
12
4
2
FREQUENCY POLYGON
20
18
16
14
12
10
8
6
4
2
0
80 - 86
87 - 93
94 - 100 101 - 107 108 - 114 115 -121 122 - 130
Frequency
Histogram
20
18
16
14
12
10
8
6
4
2
0
80 - 86
87 - 93 94 - 100 101 - 107108 - 114 115 -121 122 - 130
Class Interval
QUESTION 3
a)
Mean
total X/n
47.3
Average 57.80714
58.6
78
61.2
80.3
49.9
67.4
65.8
47.7
23.9
Median
It is the value in the canter of an arrange data based on ascending order
23.9 59.65
44.4
47.3
47.7
49.9
58.6
59.3
60
61.2
65.5
65.8
67.4
78
80.3
b)
Variance(data-mean)^2
1149.7
179.75
110.4
102.15
62.523
0.6286
2.2286
4.8086
11.511
59.18
63.886
92.023
407.75
505.93
Total 2752.5
Std Deviation
variance/n-1
211.73
14.551
44.4
65.5
60
59.3
QUESTION 4
a)
b)
c)
d)
e)
a
b
c
d
e
f (column)
f (row)
6
7
19
10
9
62
62
0.693548387
0.103448276 0.145161
0.085848075
0.655172414
PART B:
QUESTION 1
a)
Large Sample n > 30
Null Hypothesis: There is no significant adults women spend less than 11 hours per week on online shopping
Alternative Hypothesis: There is a significant adults women spend less than 11 hours per week on online shopping
9.090909
b)
Null Hypothesis: There is no significant adults women spend less than 11 hours per week on online shopping
Alternative Hypothesis: There is a significant adults women spend less than 11 hours per week on online shopping
QUESTION 2
a.
Sales Staff
A
B
C
D
E
F
G
H
I
Ads Exp
31
40
44
29
32
50
61
48
52
Sales
30
36
39
28
29
44
54
42
46
y
b)
Sales Staff
A
B
C
D
E
F
G
H
I
Total
x
Ads Exp
31
40
44
29
32
50
61
48
52
387
Sales
30
36
39
28
29
44
54
42
46
348
900
1296
1521
784
841
1936
2916
1764
2116
14074
961
1600
1936
841
1024
2500
3721
2304
2704
17591
930
1440
1716
812
928
2200
3294
2016
2392
15728
c)
Scatter Diagram
60
y = 0,8042x + 4,0856
R² = 0,9942
50
54
40
Ads
36
30
39
46
4244
29
2830
20
10
0
0
10
20
30
40
50
60
70
Sales
d)
Y
29.82
e. According to Ozer (2015) correlation is a statistical metric that expresses how closely two
variables change at the same rate when they are linearly connected. It's a typical way of
describing simple interactions without making a cause-and-effect claim. Although
correlation is a strong tool, it has certain limits because it cannot account for the presence
or effect of factors other than the two being investigated. Correlation does not, however,
reveal cause and effect. Curvilinear relationships are similarly difficult to characterise using
correlation. Furthermore, correlation does not imply causation, as a change in one variable
does not always result in a change in another. (Rodgers and Nicewander, 2016).
QUESTION 3
A time series is a set of well-defined data items observed over time through repeated
measurements. Alibaba, for example, would have a time series if they measured the value of
their retail sales each month of the year. This is due to the fact that sales income is well defined
and recorded at regular periods (Statista, 2016). Data that is collected seldom or only once is
not considered a time series. The trend, which is long-term direction, the seasonal, which are
systematic, calendar-related movements, and the irregular, which are unsystematic, short-term
fluctuations, may all be dissected from an observed time series.
There are four components of a typical times series such as trend component, cyclical
component, seasonal component, and irregular component. According to Alibaba Group
(2010) The trend of Alibaba Group is a long-term pattern of a time series. Depending on
whether the time series exhibits a growing or declining long-term pattern, their trend can be
positive or negative. A time series is stationary in the mean if it does not display an increasing
or decreasing tendency. Furthermore, Alibaba Group's cyclical component exhibits an up and
down movement around a certain trend, which is known as a cyclical pattern (Siu, 2015). The
length of a cycle is determined by the sort of business or industry being studied.
Furthermore, Alibaba Group's seasonality happens when a time series demonstrates
consistent swings over the course of a month, a year, or a quarter (Alibaba Group, 2015). Their
retail sales, for example, are at their highest in December. Furthermore, the fourth component
is irregular, with this component being unexpected because every time series contains an
unpredictable component, making it a random variable. Their goal in prediction is to "model"
all of the components to the point that the random component is the only one that remains
unexplained (Statista, 2016).
Furthermore, Alibaba Group's seasonality happens when a time series demonstrates
consistent swings over the course of a month, a year, or a quarter (Alibaba Group, 2015). Their
retail sales, for example, are at their highest in December. Furthermore, the fourth component
is irregular, with this component being unexpected because every time series contains an
unpredictable component, making it a random variable. Their goal in prediction is to "model"
all of the components to the point that the random component is the only one that remains
unexplained (Statista, 2016). Furthermore, Alibaba Group's seasonality happens when a time
series demonstrates consistent swings over the course of a month, a year, or a quarter (Alibaba
Group, 2015). Their retail sales, for example, are at their highest in December. Furthermore,
the fourth component is irregular, with this component being unexpected because every time
series contains an unpredictable component, making it a random variable. Their goal in
prediction is to "model" all of the components to the point that the random component is the
only one that remains unexplained (Statista, 2016).
References
Alibaba Group (2010) Alibaba.com to Acquire Export Service Provider Shenzhen OneTouch.
Available
at:
http://www.alibabagroup.com/en/news/press_pdf/p101115.pdf
(Accessed: 29th October 2021).
Alibaba Group (2015). Alibaba Group and Ant Financial Announce Local Services JV.
Available at: http://www.alibabagroup.com/en/news/article?news=p15062 (Accessed: 29th
October 2021).
Boslaugh, S. (2017) ‘Secondary analysis for public health: A practical guide’, New York, NY:
Cambridge. doi: 10.1017/CBO9780511618802.
Bryman, A. and E. Bell (2013) Business Research Methods, Oxford University Press, Oxford,
New York.
Chakraborty, S., and Chakravarty, D. (2012) ‘Discrete gamma distributions: properties and
parameter estimation’, Communication in Statistics-Theory and Methods, 40(18), pp. 3301–
3324.
Etter, J., F. and Perneger, T., V., (2010) ‘Snowball sampling by mail: application to a survey
of smokers in the general population’, International Journal of Epidemiology, 29 (1), pp. 43 45.
Harris, H (2011) ‘Content Analysis of Secondary Data: A Study of Courage in Managerial
Decision Making’, Journal of Business Ethics, 34(3/4), pp. 191–207.
Heaton, J. (2018) ‘Secondary analysis of qualitative data: An overview’, Historical Social
Research, 33(3), pp. 33-45.
Ozer D. J., (2015) ‘Correlation and the Coefficient of Determination’, Psychological Bulletin,
97, pp. 307-315.
Rodgers J. L., and Nicewander W. A., (2016) ‘Thirteen Ways to Look at the Correlation
Coefficient’, The American Statistician, 42, pp. 59-66.
Siu, T. (2015) Alibaba agrees to $266 million acquisition deal with South China Morning
Post.
Available
at:
http://www.reuters.com/article/us-scmp-group-alibaba-
idUSKBN0TX01S20151214 (Accessed: 29th October 2021).
Statista (2016) Annual revenue of Alibaba Group from 2010 to 2016 (in million yuan).
Available
at:
http://www.statista.com/statistics/225614/net-revenue-of-alibaba/(Accessed:
29th October 2021).
Thompson,
C.H.
(2015)
Postal
questionnaires.
Available
at:
https://sociologytwynham.com/2015/03/19/postal-questionnaires/ (Accessed: 29th October
2021).