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INDEX

Sl.No PARTICULARS

1 INTRODUCTION

2 INTRO OF TELECOM INDUSTRY

3 DATA ANALYSIS AND PERCENTAGE ANALYSIS

4 SUGGESTION

5 CONCLUSION

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INTRODUCTION TO STATISTICAL TOOL

CORRELATION:

Correlation is computed into what is known as the correlation coefficient, which ranges between -1 and +1. Perfect positive correlation (a correlation co-efficient of +1) implies that as one security moves, either up or down, the other security will move in lockstep, in the same direction. Alternatively, perfect negative correlation means that if one security moves in either direction the security that is perfectly negatively correlated will move in the opposite direction. If the correlation is 0, the movements of the securities are said to have no correlation; they are completely random. Correlations are used in advanced portfolio management. In real life, perfectly correlated securities are rare; rather you will find securities with some degree of correlation.

'Correlation Coefficient'A measure that determines the degree to which two variable's movements is associated. The correlation coefficient is calculated as:

Correlation(r) = NΣXY - (ΣX)(ΣY) / Sqrt([NΣX2 - (ΣX)2][NΣY2 - (ΣY)2])

The correlation coefficient is calculated as: 

REGRESSION:

Regression analysis is a statistical technique for estimating the relationships among variables. It includes many techniques for modelling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables — that is, the average value of the dependent variable when the independent variables are fixed. Less commonly, the focus is on a quantile, or other location parameter of the conditional distribution of the dependent variable given the independent variables. In all cases, the estimation target is a function of the independent variables called the regression function. In regression analysis, it is also of interest to characterize the variation of the dependent variable around the regression function, which can be described by a probability distribution.

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Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables. However this can lead to illusions or false relationships, so caution is advisable. See correlation does not imply causation.

A large body of techniques for carrying out regression analysis has been developed. Familiar methods such as linear regression and ordinary least squares regression are parametric, in that the regression function is defined in terms of a finite number of unknown parameters that are estimated from the data. Nonparametric regression refers to techniques that allow the regression function to lie in a specified set of functions, which may be infinite-dimensional.

The performance of regression analysis methods in practice depends on the form of the data generating process, and how it relates to the regression approach being used. Since the true form of the data-generating process is generally not known, regression analysis often depends to some extent on making assumptions about this process. These assumptions are sometimes testable if a large amount of data is available. Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally. However, in many applications, especially with small effects or questions of causality based on observational data, regression methods give misleading results.

GRAPH ON REGRESSION ANALYSIS

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INTRODUCTION TO TELECOM INDUSTRY

TELECOM INDUSTRY

Indian telecom industry underwent a high pace of market liberalization and growth since 1990s and now has become the world's most competitive and one of the fastest growing telecom markets. The Industry has grown over twenty times in just ten years, from under 37 million subscribers in the year 2001 to over 846 million subscribers in the year 2011 India has the world's second-largest mobile phone user base with over 929.37 million users as of May 2012. It has the world's third-largest Internet user-base with over 137 million as of June 2012.

The total revenue of the Indian telecom sector grew by 7% to 283,207 crore (US$53.53 billion) for 2010–11 financial year, while revenues from telecom equipment segment stood at 117,039 crore (US$22.12 billion).

TOP MARKET PLAYERS IN INDIAN CELLULAR MARKET

Telecommunication has supported the socio-economic development of India and has played a significant role to narrow down the rural-urban digital divide to some extent. It also has helped to increase the transparency of governance with the introduction of e-governance in India. The government has pragmatically used modern telecommunication facilities to deliver mass education programmes for the rural folk of India.

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ANALYSIS

1. GENDER:

Sl.No Particulars Frequency Percentage1 Male 20 50%2 Female 20 50%

Male Female0

5

10

15

20

25

20 20

Gender Details

Table 1 – Gender

INFERENCE:

From the above table and graph we can understand that 50% of the respondents are Male and 50% of the respondents are Female. So the both respondents are equal.

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2. ANNUAL INCOME:

Sl.No Particulars Frequency Percentage1 Less than 2 lakhs 5 12.5%2 2 lakhs to 5 lakhs 15 37.5%3 5 lakhs to 10 lakhs 10 25%4 Above 10 lakhs 9 22.5%

less than 2 lakh 2 lakh to 5 lakh 5 lakh to 10 lakh more than 10 lakh0

5

10

15

20

25

30

35

40

12.5

37.5

2522.5

Annual Income Detail

Table 2 – Annual Income

INFERENCE:

From the above table and graph, The customer’s income level is varying across four major income groups, with 12.5% of population with less than 2 lakhs annual income, 37.5% ranging between 2 to 5 Lakhs, 25% of population have income more than 5 lakhs and about 22.5% of customer have more than 10 lakhs income.

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3. USAGE OF CELL PHONE:

Sl.No Particulars Frequency Percentage1 12 months 13 32.5%2 24 months 17 42.5%

3 36 months 10 25%

1 year 2years 3 years0

2

4

6

8

10

12

14

16

18

13

17

10

Cell Phone Usage

Table 3 – Usage of cell phone

INFERENCE:

From the above table and graph, the customer cell phone usage curve varies broadly among three percentage groups with person using cell phone for maximum of 36 months by 25 % customers, 24 months by 42.5 % customers and minimum of 12 months by 32.5 %. Since mobile is a gadget customers use it for one year in minimum

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4. CELLULAR OPERATOR:

Sl.No Particulars Frequency Percentage1 Vodafone 10 25%2 BSNL 7 17.5%3 Airtel 10 25%4 Aircel 8 20%5 Others 4 10%

Vodafone BSNL Airtel Aircel Others0

2

4

6

8

10

12

10

7

10

8

4

Favorite Operator

Table 4 – Cellular Phone

INFERENCE:

The above table and graph gives the list of cellular phone operators with their market shares. Vodafone making a 10% of the total market followed by Airtel with 10%, Aircel with 8% and 7% by BSNL and 4 % are Others small operators.

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5. MOBILE CONNECTION:

Sl.No Particulars Frequency Percentage1 Pre-paid 21 52.5%2 Post-paid 19 47.5%

Pre-paid Post-paid18

18.5

19

19.5

20

20.5

21

21.5

21

19

Connection type

Table 5 - Mobile Connection

INFERENCE:

From the above graph, 21% of the cell phone user population prefer pre-paid connection and 19 % are post-paid connection.

6. PURPOSE OF USING PHONE:

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Sl.No Particulars Frequency Percentage1 Family and Friends 22 55%2 Business 13 32.5%3 Emergency 4 10%4 Others 1 2.5%

Family and Friends Business Emergency Others0

5

10

15

20

2522

13

4

1

Purpose of usage

Table 6 – Purpose of Using Phone

INFERENCE:

From the above table, we can infer that the study shows the basic purpose for which the cellular phones are used amongst the various customers, the persons use to keep in touch with friends and family are up to 55% and people using for business are 22.25%, only for emergency purpose accounts to just 10% and 2.5% of customers use it for other purpose.

7. MONTHLY EXPENDITURE:

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Sl.No Expenditure Frequency Percentage1 Less than Rs. 500 15 37.5%2 Rs 500 to 1000 15 37.5%3 Rs 1000 to 2000 8 20%4 Greater than Rs. 2000 2 5%

Less than Rs. 500 Rs 500 to 1000 Rs 1000 to 2000 Greater than Rs. 2000

0

2

4

6

8

10

12

14

16 15 15

8

2

Monthly Expenditure

Table 7 – Monthly Expenditure

INFERENCE:

The above given table, the monthly expenditure for cell phone among the respondents, those customers who spend less than Rs. 500 and customers with expenditure ranging from 500 to 1000 accounts for 37.5 % and those customer who spend more than Rs. 1000 to 2000 accounts about 20 % and customers above Rs.2000 are only 5%

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8. MOBILE RECHARGES:

Sl.No Particulars Frequency Percentage1 Self 17 42.5%2 Parents 15 37.5%3 Company 7 17.5%4 Others 1 2.5%

Self Parents Company Others0

2

4

6

8

10

12

14

16

18 17

15

7

1

Mobile charges

Table 8 – Mobile Charges

INFERENCE:

The given above table, we can conclude that the source of mobile charges are paid, by themselves by 42.5 % by parents 37.5%, for those who company pays their mobile bill is by 17.5% and others by 2.5%.

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9. VALUE ADDED SERVICE USED:

A) SMS – Short Mail Service

Sl.No Particulars Frequency Percentage1 Not Aware 3 7.5%2 Never Used 10 25%3 Recently Used 20 50%4 Occasionally Used 7 17.5%

Not Aware Never Used Recently Used Occasionally Used0

5

10

15

20

25

3

10

20

7

SMS

Table 8 a) – Short Service Message

INFERENCE:

The given above table, Profiling the customer based on their SMS usage are 7.5% were Not aware, 25% never used, 50%have recently used and 17.5% of the them have used this service occasionally.

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B) VOICE MAIL

Sl.No Particulars Frequency Percentage1 Not Aware 2 5%2 Never Used 20 50%3 Recently Used 11 27.5%4 Occasionally Used 7 17.5%

Not Aware Never Used Recently Used Occasionally Used0

5

10

15

20

25

2

20

11

7

Voice-mail

Table 8 b) Voice Mail

INFERENCE:

The given above table, surveying the customer based on their voice-mail usage a 5% are Not aware ,50%, never used , 27.5% have used recently and 17.5% of the them have occasionally used this service.

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C) RING TONE

Sl.No Particulars Frequency Percentage1 Not Aware 2 5%2 Never Used 5 12.5%3 Recently Used 25 62.5%4 Occasionally Used 8 20%

0

5

10

15

20

25

30

2

5

25

8

Ring tone

Table 8 c) Ring Tone

INFERENCE:

The given above table, we can understand the customer using ring tone download usage are 5 % Not aware 28.33% ,12.5 %never used and 62.5% of the them have used the service recently and 20 % have occasionally used .

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D) GPRS SERVICE

Sl.No Particulars Frequency Percentage1 Not Aware 1 2.5%2 Never Used 9 22.5%3 Recently Used 12 30%4 Occasionally Used 18 45%

Not Aware Never Used Recently Used Occasionally Used0

2

4

6

8

10

12

14

16

18

20

1

9

12

18

GPRS service

Table 8 d) - GPRS Service

INFERENCE:

The given above table, the customer using on their GPRS Service usage are 2.5% are Not aware 22.5% have never used it and 21.67% and 30% of the them have used this service recently and 45 % have used it occasionally.

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E) STD & ISD

Sl.No Particulars Frequency Percentage1 Not Aware 1 2.5%2 Never Used 15 37.5%3 Recently Used 10 25%4 Occasionally Used 14 35%

Not Aware Never Used Recently Used Occasionally Used0

2

4

6

8

10

12

14

16

1

15

10

14

STD/ISD

Table 8 e) – STD & ISD

INFERENCE:

The given above table, surveying the customer about their STD/ISD usage, 2.5% are Not aware, 37.5% have never used, 25 % have recently used and 20% have occasionally used. .

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F) MMS

Sl.No Particulars Frequency Percentage1 Not Aware 3 7.5%2 Never Used 17 42.5%3 Recently Used 10 25%4 Occasionally Used 10 25%

Not Aware Never Used Recently Used Occasionally Used0

2

4

6

8

10

12

14

16

18

3

17

10 10

MMS

Table 8 f) - MMS

INFERENCE:

The given above table, the customer based on their MMS usage are 7.5 % are Not aware, 42.5% have never used 25% have used it recently and occasionally used this service.

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G) RADIO

Sl.No Particulars Frequency Percentage1 Not Aware 4 10%2 Never Used 10 25%3 Recently Used 12 30%4 Occasionally Used 14 35%

Not Aware Never Used Recently Used Occasionally Used0

2

4

6

8

10

12

14

16

4

10

12

14

Radio

Table 8 g) - Radio

INFERENCE:

The given above table, the customer survey based on their Radio usage are 10% are Not aware, 25% have never used, 30% have recently used and 35% of them are using it occasionally.

H) INTERNET

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Sl.No Particulars Frequency Percentage1 Not Aware 5 12.5%2 Never Used 8 20%3 Recently Used 12 30%4 Occasionally Used 15 37.5%

Not Aware Never Used Recently Used Occasionally Used0

2

4

6

8

10

12

14

16

6

8

12

15

Internet

Table 8 h) - Internet

INFERENCE:

The given above table, we can infer that the customer survey based on their Internet usage are 12.5% were Not aware 25% have never used 22.5% have recently used and 47.5 % have used occasionally.

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10. COST OF SERVICE:

Yes No0

5

10

15

20

2522

18

Cost of Service

Table 10 – Cost of service

INFERENCE:

The above given table, the customers those who are willing to use the services if the mobile company reduces the cost is reduced accounts to 55% and those don’t bother to use the service even if the cost is reduced account to 45%.11. PURPOSE OF USING INTERNET:

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Sl.No Particulars Frequency Percentage1 Yes 22 55 %2 No 18 45 %

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Sl.No Particulars Frequency Percentage1 Movies 10 25%2 News 7 17.5%3 Stocks 10 25%4 Weather 3 7.5%5 Sports 10 25%

Movies News Stock Weather Sports0

2

4

6

8

10

12

10

7

10

3

10

Internet usage

Table 11 – PURPOSE OF USING INTERNET

INFERENCE:

Different purpose for the usage of internet are for watching movies which is of 25% ,those looking for news accounts to 17.5% , those who use for stock 25% for weather 7.5% and those who update about sports are 25%

CORRELATION ANALYSIS

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Correlation is the statistical tool used in this Analysis. Five interpretations are done to show the correlation between them.

1. SMS & VOICE-MAIL:

Particulars Not Aware Never Used Recently Used Occasional Used

SMS 3 10 20 7Voice-Mail 2 20 11 7

Not Aware Never Used Recently Used Occasional0

5

10

15

20

25

3

10

20

7

2

20

11

7

SMS Voice-Mail

Table 12 – Correlation between SMS & Voice Mail

The Correlation value isr= (0.4523)

INFERENCE: Since, correlation value is positive, so there is a weak positive correlation between SMS & Voice-Mail.

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2. INTERNET & GPRS SYSTEM:

particulars Not Aware Never Used Recently Used Occasional UsedInternet 6 10 9 15GPRS System

1 9 12 18

Not Aware Never Used Recently Used Occasional0

2

4

6

8

10

12

14

16

18

20

6

109

15

1

9

12

18

Internet GPRS System

Table 13 – Correlation between Internet & GPRS

The Correlation value isr= (0.9323)

INFERENCE: Since, correlation value is positive, so there is a very strong positive correlation between Internet & GPRS System.

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3. STD/ISD & GPRS System:

Particulars Not Aware Never Used Recently Used Occasional UsedSTD/ISD 1 15 10 14GPRS System

1 9 12 18

Not Aware Never Used Recently Used Occasional0

2

4

6

8

10

12

14

16

18

20

1

15

10

14

1

9

12

18

STD/ISD GPRS System

The Correlation value isr= (0.7984)

INFERENCE:

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Since, correlation value is positive, so there is a strong positive correlation between STD/ISD & GPRS System.4. RADIO & INTERNET

Particulars Not Aware Never Used Recently Used Occasional UsedRadio 4 10 12 14Internet 6 10 9 15

Not Aware Never Used Recently Used Occasional0

2

4

6

8

10

12

14

16

6

109

15

4

10

12

14

Internet Radio

The Correlation value isr= (0.866)

INFERENCE:

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Since, correlation value is positive, so there is a strong positive correlation between Internet & Radio.

5. MMS & SMS:

Particulars Not Aware Never Used Recently Used Occasional UsedMMS 3 17 10 10SMS` 3 10 20 7

Not Aware Never Used Recently Used Occasional0

5

10

15

20

25

3

17

10 10

3

10

20

7

MMS SMS

The Correlation value isr= (0.3937)

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INFERENCE:Since, correlation value is positive, so there is a weak positive correlation between MMS & SMS.

SUGGESTION:

Different Cellular Operators use different schemes of SMS, Voicemail, GPRS/3G,MMS, Radio, Roaming, STD/ISD, Ringtone download. Customers of various operators have different charges for different value added services and depending upon the customer’s income, they use that particular service. If the charges of this value added service is reduced, more number of customers will start using all these services.

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CONCLUSION:

Thus, few variables are highly dependent on other variables each as they have been projected by the strong positive correlation using correlation as a tool and it will have a huge and easy scope for market segmenting and targeting.

MOBILE STATISTICS

1) Name :

2) Gender :

3) Annual house hold income :a) <2 lakhs b ) 2-5 lakhs c) 5-10 lakhs c ) above 10 lakhs

4) Usage pattern :

5) How long have you been using your cell phone?

------------ Years ----------- months

6) Your cellular network operator a) Vodafone b) Reliance c) Airtel d) BSNL e) others

7) Type of connection :a) Prepaid b) Post-paid

8) What do you use the cell phone for:a) Business b) Keeping in touch with family and friends c) Emergency

d) Others (please specify)

9) Monthly expenditure on your mobile connectiona) Less than Rs. 500 b) Rs.500 – 1000 C) Rs. 1000- 2000 d) Rs.2000 and above

10) Mobile charges are paid by a) Self b) company c) parents

11) Value Added Service

Services Not Aware Never Used Recently Used Frequently Used

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SMSVoice MailRingtones & DownloadsNews & Cricket UpdateGPRSSTD or ISDMMSRadioRoaming3G

12) Reasons for not using some of above service:

a) Not aware b ) Too Expensive c) complicated d) No utility or No time e) Other Reasons

13) Would you use the above service more frequently if they were free?

a) Yes b ) No

14) Kindly Tick info services that you would be interested in

a) Movies b) Sports c) Stocks d) News e) Weather

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