Quantitative methods

IMPERIAL INSTITUTE OF HIGHER EDUCATION

Table of Content Table of Content .................................................................................................................... 1 1.0 Introduction .................................................................................................................... 2 2.0 Problem Background ..................................................................................................... 4 2.1 Research Description ................................................................................................. 4 2.2 Problem Description .................................................................................................. 5 3.0 Project Description......................................................................................................... 6 3.1 Issue ........................................................................................................................... 6 3.2 Objective .................................................................................................................... 7 4.0 Research Data Representation ....................................................................................... 7 5.0 Theory of Analysis ......................................................................................................... 9 5.1 Used Analysis Technique ........................................................................................ 10 6.0 Analysis........................................................................................................................ 13 7.0 Findings and Recommendations .................................................................................. 16 8.0 Reference ..................................................................................................................... 17

Quantitative Methods

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1.0 Introduction 1.1 Assignment Objectives  Understand what is Descriptive Statics and other methods are.  Identify the best method for the given data.  Explain the outcomes of the data.  Usage of the SPSS software.  Present an inclusive justification with use of figures and illustrations to support all the decisions made in calculations.

1.2 Organization Background

The main objective of this report is to analyze data from a research done in 2009. There are two main companies involved in this documentation.

1. Dialog

2. Nielsen

Nielsen Lanka is the Sri Lankan branch of AC Nielsen which operates over 100 countries in the world. Nielsen offers an incorporated collection of market information gathered from a wide range of sources, sophisticated information management gears, refined analytical systems and methodologies, and devoted specialized client service to help Nielsen consumers discover the best paths to growth.

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Main services offered by Nielsen are  Measure market performance  Market Dynamics analysis  Analyze market and sales issues and solve them  Diagnose company growth opportunities

Dialog Telekom PLC is considered as Sri Lanka’s largest telecommunication service provider. Dialog is a subsidiary company of “Axiata Group Berhad”. In addition to mobile telecommunication dialog operates many other multi-sensory connectivity services such as Dialog satellite TV, Broadband, auditory and many more.

Dialog GSM has invested over 500 million U.S Dollars for the development of telecommunication infrastructure in Sri Lanka, and has provided over 1000 job opportunities for the Sri Lankan youth.

The picture shows the coverage area of dialog network over Sri Lanka.

The Yellow color represents the “3G 2100” coverage in Sri Lanka and Pink color shows the “GSM 900/1800” coverage in Sri Lanka

Figure 1: Dialog Coverage in Sri Lanka [Source: Internet]

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2.0 Problem Background In this project there are mainly 2 companies involved. Apparently they are Nielsen Lanka and dialog Telekom.

Nielsen Lanka conducted a market research on Dialog in 2009. And the project was called RIDE. The project was conducted for 2 months by using questioners and used more than 400 different categories of clients. 30 employees of Nielsen Lanka were involved in this project and finally the results were analyzed and presented to the dialog Telekom Corporation.

2.1 Research Description Dialog is introducing new technology in Sri Lanka where the user gets the capability to watch television in the vehicle while travelling. This system uses satellite technology.

Dialog Telekom fix the full system to the vehicle and it has the capability of watching 13 channels, and also capability of watching DVD while travelling.

Therefore the user gets the opportunity to be always updated about the world and always be entertained by various programs.

If the specific vehicle already has a Television set fixed, the subscription for the satellite television will be given for a special price.

If the vehicle does not have one dialog technical team will fix the television and will be given subscription. Proposing price will be 70,000 Rs.

Given Channels are;

KidsCo

Neo Cricket

Sun TV

Neo Sports

CiTi Hitz

Learn TV

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H Tv

Buddhist

Islam Channel

God

Aarti Tv

Channel C

VH1

2.2 Problem Description The main objective of this research is to do a market research on the introducing product.

Main Objectives of the Research Price analysis - (understand the ideal price for this product.)

Customer base analysis - The whole research is divided in to four main categories. The division is done according to the value of the vehicle. They are, value of the vehicle; Less than 1 million 1.0 million < x < 2.0 million 2.0 million < x < 4.0 million 4.0 million + Customer category analysis â&#x20AC;&#x201C; This mainly focus on age of the customer and status. (e.g.

Businessman, manager, Doctor.. etc. ) Customer background â&#x20AC;&#x201C; Number of family members, Education of the customer, Education of the family members, what is the most preferred entertainment method, favorites.

The research was done with vehicle owners and they are picked randomly. In each category one hundred (100) car owners were interviewed. Overall four hundred and fifty (450) vehicle owners were interviewed but only 400 were taken in to calculation and analysis process.

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3.0 Project Description The Goal of this project is to analyze the data from the research conducted. The main research conducted to analyze many areas, which given in above paragraph.

In this specific project sample data set is used which is taken from the research. The data were cleaved from the project as explained below

400 data sets were taken in to consideration in the research under 4 categories. Therefore in each category there were 100 data sets.

It is explained as below

No

Vehicle Value

Number of Data sets

1

Less than 1.0 Million

100

2

More than 1.0 Million & Less than 2.0 Million

100

3

More than 2.0 Million & Less than 4.0 Million

100

4

More than 4.0 Million

100 400 - Total

For this project the research data from category 3 is used. Sample set which is used for this analysis is 100.

3.1 Issue Even though there were many objectives in the research in this analysis we only consider â&#x20AC;&#x153;Price Analysisâ&#x20AC;?. By the results we got from the research of category 3 in above table, the analysis is done in this project.

The main issue involved is, in almost all the interviewees did not prefer the price tagged by Dialog for this particular product. Therefore new price has to be tagged for the product.

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3.2 Objective Since the proposed price of 70,000 does not approved by most of the interviewees (Customers), a new price has to be decided. If the pricing is not done correctly product will fail with the competitors and grasping the market will be almost impossible.

Therefore the ultimate Goal of this is to find a new price which is acceptable by the customer as well as Dialog Telekom. In the sense, it is to find the best possible price for the customer.

4.0 Research Data Representation The table below shows the list of prices which are suggested by interviewees who owns vehicles that value more than 2.0 million and less than 4.0 million. And most of the interviewees participated for these were aged between 26 and 40.

Figure 2: Research Data [Source: Nielsen Research Records]

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For better understanding of the raw data, the above can be given in classes. To calculate number of classes following equation can be used.

1 + (3 Log (100)) = 7 Below shows the table which is derived from above equation. The below table is more understandable for humans than just raw data.

Proposed Value in Rupees

Frequency (f)

2500 – 12500

7

12500 – 22500

23

22500 – 32500

24

32500 – 42500

19

42500 – 52500

16

52500 – 62500

7

62500 – 72500

4 ∑ (f) =

100

The above graph shows the raw data in understandable manor. The histogram bar graph can be drawn for the above table.

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5.0 Theory of Analysis Raw data is analyzed using mathematical methods to get information necessary. In this MBA program there are Three (3) main types of analysis techniques which we could use for the analysis of above data.

Those 3 types as shown below

Descriptive Statistics – “Descriptive statistics are typically distinguished from inferential statistics. With descriptive statistics you are simply describing what is or what the data shows.”

(William. M.K. Trochim, 2006)

Correlation and Regression Analysis “Correlation analysis is the process of finding how well (or badly) the line fits the observations, such that if all the observations lie exactly on the line of best fit, the correlation is considered to be 1 or unity.”

“Regression analysis is the mathematical process of using observations to find the line of best fit through the data in order to make estimates and predictions about the behavior of the variables.”

(Whitemore, 2000)

Time Series Analysis – “A simple analytical procedure which is a predictive technique involving the extrapolation of past values of an item of financial information into the current audit period.”

(Dayarayan, 2005)

From the above three types, only one can be used for the data of the Nielsen research.

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5.1 Used Analysis Technique To carry out the analysis of the prices of the Dialog Telekom car TV set, the technique of “Descriptive Statistics” is used.

5.1.1 Justification

Correlation and Regression Analysis For the above set of data correlation and regression analysis techniques cannot be used. The reason is given below Correlation and regression method is used to identify the relationship between two parties.

In the sense if there are two parties called “X” and “Y” correlation and regression technique is used to identify the nature of the relationship (Positive, Negative) and the strength of the relationship.

In this case of analysis there are no parties divided or a relation between each data.

Therefore this technique cannot be used in this specific project.

Time Series Analysis For the above set of data time series analysis technique cannot be used. The reason is given below.

There are two main goals of the time series analysis. They are classifying the nature of occurrence by observing and forecasting future occurrence. For this kind of analysis a record of long time investigation is necessary. But in this specific research it is only one month and moreover the goal of the project itself is different.

Descriptive Statistics Descriptive Statistics is used in this project. The reason is given below The main aim of the research is to find the best price for the customers as well as for the Dialog. Therefore by using the descriptive statistics we can get the best value and much more additional data which is directly related to the aim of the research.

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5.1.2 Descriptive Statistics

This is the main method used in this specific project. In this we are mainly discussing about few types of information which is derived.

Mean Median Mode Standard Deviation Variance Minimum Maximum Skewness Kurtosis

Sample Mean The equation of the sample mean is given below

Standard Deviation The equation is of the standard deviation is given below

Median The Equation of the median is given below

Skewness The Equation of the skewness is given below

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Kurtosis The Equation of the kurtosis is given below.

NOTE: Mean is statistically average value Median is the value in the exact middle when all the values are ordered Mode is the most frequent appearing value from set of values Standard Deviation is the dispersion or the spread of values Skewness is the measure of the lop-sidedness of “probability distribution”.

Kurtosis is the measure of peakedness of probability distribution.

Above demonstrates the meanings of each factor and the equations which are used to derive the each value.

But in this specific project we do not use manual approach. We use software called “SPSS” which is specially made for the analysis of the values and for statistics purposes.

For this project SPSS version 13.0 is used. And the software itself does all the calculation and demonstration of data.

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6.0 Analysis The below table and figures shows the output which is derived from the software

Figure 3: SPSS output [Source: SPSS software]

All the below explanations are directly connected with the graph above and the research data.

N (Valid) â&#x20AC;&#x201C; N can be described as the number of values. In the research data there are 100 values. And it is represented here as valid N. Since there are no missing numbers or empty fields in the calculation, Missing = 0

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Mean Value – The mean value is the average value from all the values. It is derived by adding all the values and dividing the result by one hundred (100) which is the total number of values.

Median – The median is value which is in the middle of the dataset when the data set is ordered from smallest value to the biggest value. In this data set it is 30600.

Mode – the mode is the most appeared value. According to the research it is 25000. That means most of the interviewees like to purchase the TV set for 25000 Rs. Standard Deviation – This shows how much difference or variance is there from the mean (average) value. When the data is close to the mean the standard deviation is very low and if the data is spread the standard deviation is high. In this case standard deviation is calculated as 15601.

Skewness – skewness in this is 0.331 which is a positive value. That means this is positively skewed. That means in probability distribution graph the tail extends to the right.

Figure 4: Distribution Curve

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Kurtosis – this express the peakedness of the curve. In this specific case it gives -.753 which is a minus value. Therefore it has flatter/ less peakedness than the normal distribution curve.

Range – Range is derived by subtracting minimum value from the maximum value. And the result got from that is 65000 Minimum – This is the minimum value of the data set.

Maximum – This is the maximum value of the data set.

Sum – Sum is not important factor in this research. However it is the total of all the values given in the dataset.

Percentiles 25 - There are 100 values in the dataset. And this is the 25th value when all the values are ordered from minimum value to the maximum. In other words this is the ¼ th value of the total number of values.

Percentiles 50 – this is the 50th value. And this is equal to the median. Therefore we can state that 50th percentile is equal to the median of the dataset.

Percentiles 75 – this is the 75th value. In other words this is the ¾ th value from the whole dataset.

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7.0 Findings and Recommendations In the previous chapter we discussed about the results demonstrated using the SPSS software. In this chapter more discussion will take place about the usefulness of the above information for the research of the project and the results. Additionally recommendations will be given about the research results.

In the above analysis the mean, median, mode values are 32330, 30600, and 25000 respectively. All the three values are very important in this project to decide the price for this category of customers.

Even though median and mode get higher value best suitable value is 25000 which is mode. That is because most occurring value is 25000. Therefore most selling value for the TV is 25000.

But since the cost of production for the dialog may be very high and if the price is decided for 25000 there could be no profit at all. in a case like that Dialog always have the option of going for the mean, median or somewhat closer value which is higher than the Mode.

The kurtosis takes a negative value therefore we can understand that values are more distributed. That means the values are not concentrated around the mode value. This is somewhat good news for the Dialog because they has the ability to move a bit towards high price area without making huge gap in the â&#x20AC;&#x153;yâ&#x20AC;? axis in the graph.

In the percentiles, Percentile (25) =18400, Percentile (50) = 30400, and Percentile (75) = 44375. By that we can say that between percentile (25) and percentile (50) there is a huge gap, but between percentile (50) and percentile (75) there is only a small gap. Therefore we can say that in 50 â&#x20AC;&#x201C; 75, value difference between each other is comparatively low.

Therefore when deciding the price they always can concentrate to that area as well.

By all the details given above as well as considering all the production costs the selling price can be found.

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8.0 Reference

William M.K, 2005. Descriptive Statistics [online]. Available from: <http://www.socialresearchmethods.net/kb/statdesc.php>. [Accessed 05/06/10].

Jay Hill, 2005. Descriptive Statistics [online].Available from: <http://mste.illinois.edu/hill/dstat/dstat.html>. [Accessed 05/06/10]. annonymous ,2001. Descriptive Statistics [online].Available from: <http://onlinestatbook.com/chapter1/descriptive.html>.[Accessed 06/06/10].

Whitemore, 2000. Correlation and Regression [online].Available from: <http://managersnet.org/regression.html>. [Accessed 06/06/10].

Britannica Encyclopedia, 2001. Correlation and Regression [online]. Available from: <http://abyss.uoregon.edu/~js/glossary/correlation.html>. [Accessed 06/06/10]. dayarayan,

2001.

Correlation

and

Regression

[online].

Available

from:

<http://www.dayarayan.info/english-Glossary .php>. [Accessed 06/06/10].

Osmar R, 2003. Definitions of terms [online].Available from: <http://webdocs.cs.ualberta.ca/~zaiane/courses/cmput690/glossary.html>. [Accessed 06/06/10].

Charles W, 1998. Time Series Analysis [online].Available from: <http://books.google.lk/books?id=8FppWLEFHU8C>. [Accessed 06/06/10].

Australian Bureau of Statistics, 2008. Time Series Analysis [online].Available from: <http://www.abs.gov.au/websitedbs/d3310114.nsf/4a256353001af3ed4b2562bb00121564/ b81ecff00cd36415ca256ce10017de2f!OpenDocument> [Accessed 07/06/10].

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