## Assignment Cover Sheet Qualification Module Number and Title

Assignment Cover
Sheet

Qualification

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Module Number
and Title

Higher
National Diploma in Computing & Software Engineering

Analytics

Student Name
& No.

Assessor

Vivek
Sureshkumar & CL/HNDCOM/73/50

Mr.Chanuka

Hand out date

Submission Date

29-01-2018

Assessment
type
Coursework

Duration/Length
of
Assessment
Type
3
weeks

Weighting of
Assessment

100
%

Learner
declaration

I, Vivek Sureshkumar certify
that the work submitted for this assignment is my own and research sources
are fully acknowledged.

Marks Awarded

First assessor

IV marks

Signature of the assessor

Date

Acknowledgment

I take this
opportunity to thank my BA lecturer Mr.Chanuka who taught us this lesson
Business Analytics and who provided us with this assignment which helped us to
analyze and remember the tasks and study well. I also thank my fellow mates who
helped me to finish this assignment by lending a helping hand in sorting out my
doubts. I also thank my lecturer for his support and guidance throughout the
completion of this assignment.

He is really
cool person to explain things clearly to everyone even sometimes if doubt is
cleared he seems to be the same as in the beginning class, he’s having so energetic
to express the important points as well to clear doubts. so I’m again thanking again
to my lecturer.

Introduction

having a lot of theories but when it comes do everything & practice in R
studio it’ll more clear as well as more interesting.

In this modern world everything interconnects
with business so we must have a better knowledge to use & apply everywhere.
Through this subject we are learning about R-studio which is having special
graphs, pie charts, histograms, curves, special analysis including mean, mode,
median, etc… so using these charts & graphs we can apply everything into
a software, then as a company per month, per week, per year likewise we can analyze
easily.

1 : Provide an explanation about company expectation of the analysis and
benefits generated. 6
2 : Explain tools, techniques and methodologies going to use for data analysis
purpose of three products. 7
3: Find out minimum, maximum, mean, median, mode of sales revenue of each
product during three months. 9
DATA
SET MX.. 9
DATA
SET NX.. 11
Data
Set OX.. 12
4 : Find out summary statistics of each product within three months. 13
NebMX:
Summary. 13
NebNX
: Summary. 13
NebOX:
Summary. 14
5: Graphically represent product sales quantity data and product sales revenue
data during three months using statistical charts. 15
Barplot-NebulaMX.. 16
Barplot-NebulaNX.. 16
Barplot-NebulaOX.. 17
6: Conduct central tendency analysis for each product and find out standard
deviation of product sales quantity based on region. Represent finding
graphically using bell curves. 18
CMT
Nebula MX-Colombo. 18
Mean
& sd. 18
Histogram.. 18
Curve. 18
CMT
Nebula MX-Kandy. 19
Mean
& sd. 19
Histogram.. 19
Curve. 19
CMT
Nebula MX-Kurunegala. 20
Mean
& sd. 20
Histogram.. 20
Curve. 20
CMT
Nebula NX-Colombo. 21
Mean
& sd. 21
Histogram.. 21
Curve. 21
CMT
Nebula NX-Kandy. 22
Mean
& sd. 22
Histogram.. 22
Curve. 23
CMT
Nebula NX-Kurunegala. 23
Mean
& sd. 23
Histogram.. 23
Curve. 24
CMT
Nebula OX-Colombo. 24
Mean
& sd. 24
Histogram.. 25
Curve. 25
CMT
Nebula OX-Kandy. 25
Mean
& sd. 25
Histogram.. 26
Curve. 26
CMT
Nebula OX-Kurunegala. 26
Mean
& sd. 26
Histogram.. 27
Curve. 27

company expectation of the analysis and benefits generated.

CMT plc is one of the leading
electronic device manufacturer in Srilanka, their designing part and
technologies are unique as well as in very attractive standard so they having a
good placement in consumer market. In 2015 they introduced three tablet products
named CMT Nebula Mx, CMT Nebula Nx, CMT Nebula Ox. All three products having
different features and prices which is targeted for various type customers.

Company planned to do a survey
for first three months in 2015 & covers the areas Colombo, kandy & Kurunegala.
These are the major cities to analyze about the selling level, opportunities,
strengths , weakness, threats as well as to fulfill the customer’s requirement
and is capable for getting more profit also to collect valuable data, comments this
survey will help.

This survey is used to enhance
the revenue & profit targets of the company. Also via this survey

Ø  Will
help to figure out the issues in products so can fixed it soon & finalize
it.

Ø  Also
can analyze the relationship between customers and employees.

Ø  Company
can get experience to have good relationship with customers to sell best
products.

Task 2 : Explain tools, techniques and
methodologies going to use for data analysis purpose of three products.

R-Studio

It is a
cross-platform integrated development environment for the R statistical
language. RStudio supports version control and codebase organization in the
form of projects. It allows you to seamlessly document what you are doing while
you are doing it .RStudio enable rapid navigation to files and functions and
also it makes easier to start new or saved projects. It can run on most
desktops and also on a server and can access over the web.

Microsoft
Excel

It’s a
spreadsheet program that allows user to quickly log, sort, summerise and
analyze data. In the modern era, many businesses and firms collect data from
multiple sources. It provides a grid interface to organize any type of
information. Excel allows users to build a variety of great charts including
pie charts, clustered   column charts and
graphs.

It allows
conditional formatting, which means that users can use different shades,
bolding and italics to help differentiate between their data. Excel is one of
best product of Microsoft which is releasing with Office package and most of
the companies in world really must need to work with excel. In excel data can
be imported and exported from a variety of files. Excel is very useful tool for
scientific and statistical analysis with large data sets. In other words can
say as a company without a excel sheet is nothing (mostly).

R

It incorporates
all of the standard statistical tests, models and analyses, as well as
providing a comprehensive language for managing and manipulating data. This
programming language R reflects well on a very competent community. R is free
open source software allowing anyone to use and importantly, to modify it. The
graphical capabilities of R are outstanding, providing fully programmable
graphics language. R prefers data arranged with variables in columns and
observational units in rows.

It commands provide an exact record of how
an analysis was done. Those commands can be edited, rerun, commented, and
shared.

R-commander

R-commander is
easy to use. It is a graphical user interface that provides a powerful and
comprehensive system for analyzing data when used. It is simple and multiple
linear regression. R-commander utilizes many other R packages and can perform
most standard statistical analyses.

Hypothesis

Is a testing
that is the formal procedures that statisticians use to test whether a
hypothesis can be accepted or not. Typical examples of parameters are the mean
and the variance.

There are two
types of statistical hypotheses:-

·
Null Hypothesis

The
null hypothesis states that there is no association between the predictor and
outcome variables in the population. The null hypothesis is the formal basis
for testing statistical significance.

·
Alternative hypothesis:-

This
is denoted by H1 or Ha, it is the hypothesis that sample
observation are influenced by some non-random cause.

One
and two tailed alternative hypothesis.

A
one tailed hypothesis specifies the direction of the association between the
predicator and outcome variable. And a two tailed hypothesis states only that
an association exists it doesn’t specify the direction.

Task 3: Find out minimum, maximum, mean,
median, mode of sales revenue of each product during three months.

DATA SET MX

Median

Median
is the middle value in the list of numbers. According to the CMT products of MX
data set the median sale vale is calculated and considering the every
information of MX item it is discovered that the middle value is “31250000”.
It’s not the highest or the lowest number but the middle value in all the
entries.

Mean

The mean is the average you’re used to, where
you add up all the numbers and then divide by the numbers of numbers. So mean
is to find out the average of the dataset.

Mean= sum of MX sales revenue data

Number of MX data

Maximum value

Maximum value is
to see the highest value of all the products in the MX column data sheet.

Minimum value

It is to find the
lowest value of all the MX data column. And the minimum value of the product MX
is 5e+06

Mode value

It is the most
used value and according to the M data set “32500000” is used in the data sheet
of MX product.

DATA SET NX

Mean value

Mean= sum of MX
sales revenue data

Number
of NX data

So the NX mean
value is – “40888889”

Median value

There are 18
entries in the column of NX and the median is the 9th entry in it.
It is the middle value 2.4e+07

Maximum value

The maximum value
of the NX product is “1e+08”.

Minimum value

And the minimum
value is the lowest value of the sales revenue NX product which is “4e+06”.

Mode value

The most
frequently used mode value is in the NX product is “42666667”.

Data Set OX

Median value

According to the
OX product data set the median for each month is “6e+07”

Mean value

Mean= Sum of OX
sales revenue data

Number of OX data

So the mean is
“9.3e+07”

So according to
the value of sales revenue of NEBULA OX is “40888889”

Mode value

The mode value is
most likely to be “3e+07”

Minimum value

The minimum value
of NEBULA OX is “3e+07”

Maximum value

The maximum value
of NEBULA OX is “1.8e+08”

Task 4 : Find out summary statistics of each
product within three months.

NebMX: Summary

NebNX : Summary

NebOX: Summary

Task 5: Graphically represent product sales
quantity data and product sales revenue data during three months using
statistical charts.

Barplot-NebulaMX

Barplot-NebulaNX

Barplot-NebulaOX

Task 6: Conduct central tendency analysis
for each product and find out standard deviation of product sales quantity
based on region. Represent finding graphically using bell curves.

CMT Nebula MX-Colombo

Mean & sd

Histogram

Curve

CMT Nebula MX-Kandy

Mean & sd

Histogram

Curve

CMT Nebula MX-Kurunegala

Mean & sd

Histogram

Curve

CMT Nebula NX-Colombo

Mean & sd

Histogram

Curve

CMT Nebula NX-Kandy

Mean & sd

Histogram

Curve

CMT Nebula NX-Kurunegala

Mean & sd

Histogram

Curve

CMT Nebula OX-Colombo

Mean & sd

Histogram

Curve

CMT Nebula OX-Kandy

Mean & sd

Histogram

Curve

CMT Nebula OX-Kurunegala

Mean & sd

Histogram

Curve

Task 7: Using statistical hypothetical testing prove, whether there
is a statistically identifiable relationship exist with Product Quality and the
Product Revenue

x

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