ElecCom Customer Data Analysis

This assignment tasks students with analyzing customer data for ElecCom using descriptive statistical methods. Students are asked to classify variables, create frequency distributions (pivot tables & charts), calculate proportions, and interpret trends in spending habits based on age, experience, and membership status. The analysis aims to understand how these factors influence customer purchasing behavior.

MCD2080 Business Statistics Assignment
Descriptive Statistics
Student id & name
[Pick the date]

Question 1
It is apparent that Gender is a categorical variable since the underlying variable is expressed by a
non-numerical value. Further, the Gender variable is nominal as there is no overlapping and also
numerical significance is lacking for this variable.
The Age variable is numerical considering that the underlying values are captured by a numerical
value. Further, the variable is of continuous nature as all possible ages including fractional ages
are also included in the interval under consideration.
The Spend variable is numerical considering that the underlying values are captured by a
numerical value. Further, the variable is of discrete nature as all the data values are integers only
and no value is fractional or decimal.
Question 2
(a) Pivot table to present that frequency distribution of the customers of ElecCom is
highlighted below:
Table 1
(b) Column chart to present that frequency distribution with respect to the age and
experience of the customer is shown below:

(c) It is apparent that both the given age distribution are non-normal considering that skew is
present in both of these. From the pivot table, it is apparent that for the new customers
less than 10% of the customers have a age over 56 while there is a disproportionate
amount of customers lying in the age group of 30 or younger. In relation to the old
customers also, the minimum proportion is witnessed for the age group constituting 56 or
older. However, for this particular segment, the largest market share is occupied by the
age group 31-55 years. Hence,, both have outliers on the positive side in the form of
customers have a very high age.
(d) It is apparent that the percentage representation of new customers is higher in the age
group of 30 or less when compared to the old customers. However, for the other two age
groups i.e. 31-55 and 56 or old, it is the old customers who tend to have a greater %
representation in comparison with new customers.
Question 3
(a) Frequency distribution of the table 1 in the form of percentage of grand total is shown
below:

(b) Frequency distribution of the table 1 in the form of percentage of row total is shown
below:
(c) Frequency distribution of the table 1 in the form of percentage of column total is shown
below:
Question 4
The below highlighted table is the indication of the respective proportion as per the pivot tables.
S. No. Question Proportion
a) Age group which has greatest of new customers 30 or younger (0.62)
b) Proportion of customers who are old customers and
aged between 31-55
172/800 = 0.215
c) Number of old customers who are aged 30 or younger 151
d) Proportion of the old customers who are aged 56 or
older
0.1456 or 14.56%
e) Proportion of customers who are new customers 422/800 = 0.5275

Question 5
(a) Pivot table for mean spend of customers in relation with age and experience of the
customers is shown below:
(b) Column chart for mean spend of customers in relation with age and experience of the
customers is shown below:
(c) The general trend is towards an increase in mean spend as the age rises. However, there is
a significant difference with regards to the new and the old customers. This is because for
the new customers, the mean spend is highest for 31.55 age group while lowest for 56 or
older age group. However, for the old customers, the mean spend is highest for 56 or
older while lowest for 30 or younger age group.
Question 6
There seems to be an inverse relationship between membership status and average spending.
This is observed for all the income groups barring the low income group where the membership

group tends to have a higher average spending level in comparison with non-membership group.
For instance, for a customer lying in the medium income group, $ 465 is the average non-
member spend while $ 449 is the average member spend Further, it makes sense for the company
to focus on the high income group customers as a suitable cohort since the average spending for
customers lying in this group tends to be the highest.
Question 7
The requisite table is indicated below.
Question 8
a) The requisite table is indicated below.
b) The requisite table is indicated below.

Question 9
a) The requisite histogram is as indicated below.
b) The requisite histogram is as indicated below.

Question 10
It is apparent that the distribution for the new customer spend is non-normal since a tail towards
the right is present which is indicative of the positive skew. This is apparent as there are certain
customers which have spending in the range of $ 1,520 to $ 1,670. Further on account of present
of skew, the shape is not symmetric and does not assume a bell curved shape.
Question 11
a) Yes the results do support the claim that old customers on an average tend to spend more.
This is apparent from the comparison of average which is $ 435 for the old customers while $
308 for the new customers. Similar observation for median is also observed.
b) The value of $ 435 implies that an old customer on an average spent $ 435 last year on
purchases. Also, the median value of $ 386 implies that 50% of the old customers would have
an average spending lower than or equal to $ 386.
c) The best reporting measure while reporting average spend would be median since mean
would be distorted owing to distortion produced by outliers on the positive side.
Question 12
a) The various variation variables are compared above.
IOR – Higher for old customers ($ 444) as compared to new customers ($ 322)
Standard Deviation - Higher for old customers ($ 343) as compared to new customers ($ 270)
Range - Higher for old customers ($ 1689) as compared to new customers ($ 1589)
Coefficient of Variation - Higher for old customers (0.91) as compared to new customers
(0.64)

b) The middle 50% values for the old customer spend tend to lie between $ 156 to $ 600. The
difference between the maximum spend and minimum spend by the old customers last year
amounts to $ 1,689. Further, the standard deviation from mean in case of old customer
amounts to $ 343.
c) Since right skew is present, hence IQR is the best suited measure for measuring variability.
Also, on the basis of the various variability indicators, it is apparent that the higher variability
of Spend is observed for old customers in comparison to the new customers.