A Report on“Socio-Economic background of General

Investors”Course Name: Business Statistics

Course Code: F-107[

Lecturer

Department of …..Faculty of Business Studies

University of Dhaka

University of Dhaka

Date of Submission: 18 February, 2014

SUBMITTED BY

SUBMITTED TO

SL No. Name ID No.

1

2

3

4

5 =

6

7

8

9

Department of ……University of Dhaka

ACKNOWLEDGEMENT

Group Details

At the very beginning we acknowledge our gratitude to Almighty Allah to help us in preparing

the report on time. Then we like to acknowledge our gratitude to our classmates. Because they

helped us a lot. Without their direct co-operation it would not be possible to conceptualize and

carry out this sort of analytical work.

We also express our thanks to our dear course teacher Mohammed Abdullah Al Mamun for

assigning us a report dealing with the share market. The goal of this report is to identify the socio

economic background of the general investors through descriptive statistics. We would like to

thank the honorable teacher to provide us the opportunity to apply classroom learning in practice.

There are always some differences between theories and practical. This report bridges the gaps

between them. We also like to thanks the authors from whose books we take help for preparing

the report.

So lastly, we would again like to express our heartfelt thanks to our course teacher for providing

valuable guidelines related to this report.

All members of our Group

Letter of Transmittal

February 18, 2014

…………………………

LecturerDepartment of …………..University of Dhaka.

Dear Sir,

Subject: Submission of report on socio economic background of general investors

We are extremely gratified & enthusiastic to present a report on” socio economic background of general investors from the course named ‘Statistical techniques in business & economics, as part of our academic activities.

We have prepared this report based on the data gathered from interviewing share market investors of different brokerages houses. This was the first ever opportunity for us to gain proper understanding about the share market. Thank you for giving us the opportunity to learn the real life practice and increase the knowledge. As we are really new in this field any mistakes can be occurred by us. We deeply regret for any mistakes made in this term paper and we will always be available for any clarification required.

We would, therefore, feel much obliged if you are kind enough to consider our report enthusiastically and also consider our mistakes sympathetically.

Sincerely yours,

All members of our Group

The report began with a brief overview of different statistical tools like frequency distribution for qualitative and quantitative data, graphical techniques to represent data, measures of location, measures of dispersion, regression analysis etc. that are used to make decisions in business world. By using this techniques a business can maintain its operations systematically or in a organized way. The introductory part ended with the origin & scopes of the assigned subject. The main segment of the report started with an elaborate discussion of different securities and

EXECUTIVE

their share investors’ personal information like their name, age, marital status, their first share market involvement, their monthly income etc. As it was our assign subject to know the socio economic background of the general investors we apply different statistical tools based on the investors’ information. Using different techniques we find out much information about the investors such as whether there are more male or female investors, whether there are more married or unmarried people, whether there expenditure depends on share market income etc. Then we show the different graphical representation, regression analysis based on survey information. At last from this study we came to know many things. From our text book we only know about the theoretical concept of different statistical tools but when we implement our learning ideas in practical life we came to know the real uses of these tools in business.

Table of Contents

Chapter No. Chapter Title Page Number

Chapter 01 Introduction1.1 introduction1.2 objective of the report1.3 Methodology1.4 Limitations

Chapter 02 THEORITICAL BACKGROUND

Chapter 03 Statistical Analysis of the Socio-Economic Background of General Investors3.1 List of the brokerage house3.2 Age of the respondents

3.3 Gender of the respondents

3.4 Occupation of the respondents3.5Marital status of the respondents3.6 Monthly income of the respondents3.7 Member dependency on income3.8 First share involvement of the respondents3.9 Educational background of the respondents3.10 Expenditure dependency of the respondents

Chapter 04 conclusion

Chapter 05 AppendixChapter 06 References

CHAPTER 1: INTRODUCTION OF THE STUDY

Different Statistical techniques are very important in our everyday life especially in business world .For this reason statistics course is required .The main purpose of this course is to give an overview of the Descriptive statistics as well as presenting statistics in an understandable way .The main reason of the importance of statistics is to form the data in a informative way .Because we know that numerical information is everywhere .If we want to accumulative this in a informative way we have to use different statistical techniques .The second reason is that statistical techniques are used to make decisions that affect our daily lives that is ,they affect our personal welfare .

The objectives of the report are given below:

To know the uses of different statistical techniques and tools

To know the real practice of these tools

To know the socio economic background of share market investors

When we prepare this report we collect information from both the primary data sources and the secondary data sources .

Primary data sources: Visiting the different brokerage houses and collecting the

required data from the investors. Secondary data sources:

Collecting information about the brokerage houses from the share market website.

1.1 Introduction:

1.2 Objective of the Report

1.3 Methodology

Gathering necessary information from our text book. Applying our own ideas.

The limitations of our study are mentioned bellow:

As we are really new in this field and it is our first report in our life; we

felt lack of experience in every stage of our work. And there was not

enough time for this project. But we tried our level best to overcome

this

On the other hand when we visited the brokerage houses we saw

that the investors were involved with their share transactions as a

result they could not fully concentrated on our survey. It was tough to

make conversation with them.

Some essential data could not be gathered because of confidentiality

concerns.

Another limitation was that the data gathered could not be verified

for accuracy.

CHAPTER 2: THEORITICAL BACKGROUND

1.4 Limitations of the Report

2.1 Statistics

Scientific methods for collecting, organizing, summarizing, presenting and analyzing data as well as drawing valid conclusions and making reasonable decisions on the basis of such analysis.

Statistics Defined:

• Singular sense: Statistics in singular sense means a subject or scientific discipline.

• Plural sense: Statistics in plural sense means statistical data. This data must carry answers to questions like what? Where? When?

• So, Statistics can be defined as a body of methods for obtaining and analyzing numerical data in order to make better decisions in an uncertain world.

DataInformationKonwledgeStatisticalMethods

DescriptiveStatistics

InferentialStatistics

2.2 The Statistical Process

2.3 Types of Statistics

2.3.1 Descriptive Statistics

Descriptive statistics are the tabular, graphical, and numerical methods used to summarize data.

The methods used to estimate a property of a population on the basis of a sample.

Population: The entire sat of individuals or objects of interest or the measurements obtained from all individuals or objects of interest.

Sample: A portion, or a part, of the population of interest.

Data can be further classified as being qualitative or quantitative.

2.3.2 Inferential Statistics

2.4 Types of Data

2.4.1 Qualitative Data

Labels or names used to identify an attribute of each element Often referred to as categorical data Use either the nominal or ordinal scale of measurement Appropriate statistical analyses are rather limited

In general, there are more alternatives for statistical analysis when the data are quantitative.

Quantitative data indicate how many or how much

Discrete: if measuring how many Continuous: if measuring how much

Quantitative data are always numeric. Ordinary arithmetic operations are meaningful for quantitative data.

Nominal: Data are labels or names used to identify an attribute of the element. nonnumeric label or numeric code may be used.

2.4.1 Quantitative Data

2.5 Levels of Measurement

Ordinal: The data have the properties of ordinal data, and the interval between observations

is expressed in terms of a fixed unit of measure.

Interval: It includes all the characteristics of ordinal level but values is a constant size.

Ratio: The data have all the properties of interval data and the ratio of two values is meaningful Variables such as distance, height, weight, and time use the ratio scale

Techniques used to describe a set of data are called Describing data.

A frequency distribution is a tabular summary of data showing the frequency (or number) of items in each of several non-overlapping classes. The objective is to provide insights about the data that cannot be quickly obtained by looking only at the original data.

1- Determine range

2- Select number of classes

• Usually between 5 and 20 inclusive

3- Compute class intervals (width)

4- Determine class boundaries (limits)

5- Compute class midpoints

6- Count observations & assign to classes

2.6 Describing Data

2.6.1 Frequency Distribution

2.6.1.1 Frequency Distribution Table Steps

2.6.2 Relative Frequency Distribution

The relative frequency of a class is the fraction or Proportion of the total number of data items Belonging to the class.

A bar graph is a graphical device for presenting qualitative data. On one axis (usually the horizontal axis), we specify the labels that are used for each of the

classes. The bars are separated to emphasize the fact that each class is a separate category.

The pie chart is a commonly used graphical device for presenting relative frequency distributions for qualitative data.

Another common graphical presentation of quantitative data is a histogram.

The variable of interest is placed on the horizontal axis.

A rectangle is drawn above each class interval with its height corresponding to the interval’s frequency, relative frequency, or percent frequency

Unlike a bar graph, a histogram has no natural separation between rectangles of adjacent classes

2.6.3 Bar Graph

2.6.4 Pie Chart

2.6.5 Histogram

2.6.6 Cumulative Frequency Distribution

shows the number of items with values less than or equal to the upper limit of each class.

Measures of Location : Mean, Median, Mode, percentiles, Quarterlies

Measures of Variability:

The mean of a data set is the average of all the data values.As we said, the sample mean is the point estimator of the population mean m.

Properties of the Arithmetic Mean:

1- Every set of interval-level and ratio-level data has a mean.

2- All the values are included in computing the mean.

3- A set of data has a unique mean.

4- The mean is affected by unusually large or small data values.

5- The arithmetic mean is the only measure of central tendency where the sum of the deviations of each value from the mean is zero.

Geometric Mean:

It is a kind of average of a set of numbers that is different from the arithmetic average. The geometric mean is well defined only for sets of positive real numbers (no negative or

zero value). This is calculated by multiplying all the numbers (call the number of numbers n), and taking

the nth root of the total. A common example of where the geometric mean is the correct choice is when averaging

growth rates.Formula:

GM = ((X1)(X2)(X3)........(XN))1/Nwhere X = Individual growth factor

2.7 Numerical Measures

2.7.1 Mean

N = Sample size (Number of

The median of a data set is the value in the middlewhen the data items are arranged in ascending order.

Whenever a data set has extreme values, the median is the preferred measure of central location

The median is the measure of location most often reported for annual income and property value data

A few extremely large incomes or property values can inflate the mean

Positioning Median Point= n+1

2

Median = L + (n/2 – p.c.f)/f * h

Where:L = The lower class boundary of median classh = The size of median class i.e. difference between upper and lower class boundaries of median classf = The frequency of median classp.c.f = Previous cumulative frequency of the median classn/2 = Total no. of observations divided by 2...OR...summation of F divided by 2

The mode of a data set is the value that occurs with greatest frequency.

2.7.2 Median

2.7.2.1 Median Grouped Data

2.8 Mode

The greatest frequency can occur at two or more different values

If the data have exactly two modes, the data are Bimodal

If the data have more than two modes, the data are multimodal

Mode = L + [(fm-f1) / (fm-f1)+(fm-f2)] x h

where:L = The lower class boundary of modal classfm = The Frequency of the modal classf1 = The previous frequency of the modal classf2 = The next frequency of the modal classh = The size of modal class i.e. difference between upper and lower class boundaries of modal class.Modal class is a class with the maximum frequency

Median is the value of the data set arranged either in ascending or descending order. By extending the idea of Median we can think of values which divides the data set into four or hundred equal parts. Hence we can get

Quartiles: The values that divides the data set into four equal parts are called quartiles

Percentiles: A percentile provides information about how the data are spread over the interval from the smallest value to the largest value.

The p th percentile of a data set is a value such that at least p percent of the items take on this value or less and at least (100 - p) percent of the items take on this value or more

2.8.1 Mode Grouped Data

2.9 Numerical Measures

2.10 Measures of Variability

The degree to which numerical data tend to spread about an average value is called the dispersion or variation of the data. It is often desirable to consider measures of variability (dispersion), as well as measures of location.

The standard deviation of a data set is the positive

square root of the varianceIt is measured in the same units as the data, making

it more easily interpreted than the variance.Most commonly used measure of variation in

Business application

Measure of relative dispersion

Always a %

CV is the standard deviation expressed as percent of the mean

Used to compare two or more groups

Weakness: CV is undefined if the mean is zero or if data are negative.

Thus, CV is used only for variables whose values are X>=0

Sometimes two or more variables are related in such a way that movement in one variable is accompanied by the movements in other variables.

2.10.1 Standard Deviation

2.10.2 Coefficient of Variation

2.11 Correlation

For example there exists a relationship between family income and the amount spent on luxury items, increase in the quantity of rainfall and the production of crops, increase in govt. expenditure and the living standard, flow of FDI and GDP growth etc.

The statistical tool used to measure this relationship between two or more variables is called correlation. Correlation is an analysis of the co-variation of two or more variables.

Independent variable: is a variable that can be controlled or manipulated or used to see the impact on dependent variable.

Dependent variable: is a variable that cannot be controlled or manipulated. Its values are predicted from the independent variable

The independent and dependent can be plotted on a graph called a scatter plot. By convention, the independent variable is plotted on the horizontal x-axis. The dependent

variable is plotted on the vertical y-axis

The correlation coefficient (r) computed from the sample data measures the strength (Strong/moderate/low) and direction (positive/negative) of a relationship between two variables.

Formula for coefficient of Correlation

CHAPTER 3: Statistical Analysis of the Socio- Economic Background of General Investors

2.11.1 Independent and Dependent Variable

de

2.11.2 Scatter Plot

2.11.3 Coefficient of Correlation

r=∑i=1

n

( X i−X )(Y i−Y )

√∑i=1

n

( X i−X )2 √∑i=1

n

(Y i−Y )2

In this section we will list the securities in which we visited. We have visited nine securities. The list of these brokerage houses is given below:

1. BDBL securities2. ICB Securities Trading Company Limited3. Shakil Rizvi Stock Limited4. Ahmed Iqbal Hasan Securities Ltd5. Ibrahim Securities Limited6. DBL Securities7. Anwar Securities Limited8. Lanka Bangla Securities9.

Now we will present frequency distribution, show the graphical presentation such as pie chart, bar chart, histogram, frequency polygon, cumulative frequency polygon. We will also analyze the data using statistical tools and along with this we will present interpretation of the analysis.

We were given questionnaire containing eleven questions about investors of share market. We will now apply statistical tools on each question.

In our survey we found that most of our respondents are of 30-40 age. We will now present pie chart and bar chart on the information gathered from the investors

The Frequency Table of the Age of the respondentsClass Limit FrequencyBelow 20 220-30 4530-40 6640-50 45Above 50 22total 180

3.1 List of the Brokerage House:

3.2 Age of the respondents

1% 13%

18%

13%6%

50%

Pie Chart of the Age of the Respondents

below 2020-3030-4040-50above 50total

below 20 20-30 30-40 40-50 above 50 total0

20406080

100120140160180200

Bar Chart of the Age of the Respondents

freq

uenc

y

Interpretation: In frequency table the most frequency lied between 30-40 classes. Almost 50% respondents’ age is between 30%-40%.

In our survey we found that almost all the investor in the brokerage house are male. For your consideration we present our findings through pie chart and bar chart below:

3.3 Gender of the Respondents

Gender FrequencyMale 168Female 12Total 180

93%

7%

Pie Chart of the Gender of the Respondents

Male Female

Male Female0

20406080

100120140160180

Bar Chart of the Gender of the Respondents

Series1

Occupation is an important element of socioeconomic condition. In our survey we categorized the general investors in 5 groups. Where we found that maximum are businesspersons. We used the bar chart and the pie chart to demonstrate percentage of each category:

Frequency tableOccupation FrequencyFinancial service 30Government service 09Business 85Academician 10Other service 46Total 180

309

85

10

46

Pie Chart of the Occupation of the Respodents

Financial ServicesGovernment ServicesBusinessAcademicianOther Services

3.4 Occupation of the Respondents

Occupati

on

Finan

cial Se

rvices

Governmen

t Serv

ices

Business

Academ

ician

Other Ser

vices

020406080

Bar Chart of the Occupation of the Respondents

Series2Series1

From the frequency table it can be concluded that the lowest frequency is 09 and the highest frequency is 85. The total number of frequency is 180. The highest frequency is in the class named business and the lowest frequency is in the class named Government service.

From the pie chart it can be concluded that about 47% investors were businesspersons, about 17% investors were engaged in financial services, about 5% investors were engaged in government services, about 6% investors were academician and about 26% were engaged in other services

Marital status is an element of socio-economic condition. After surveying we found that most of the investors are married. For your convenience we present a frequency table and based on table we draw pie chart and bar chart below.

Marital status FrequencyMarried

Unmarried

129

51

3.5 Marital Status

Total 180

129

51

Marital status

married

unmarried

married unmarried0

20

40

60

80

100

120

140 129

51

Bar Chart of the Marital Status of the Respondents

frequency

From the frequency table it can be concluded that the lowest frequency is 51 and the highest frequency is 129. The total number of frequency is 180. The highest frequency is in the class named married and the lowest frequency is in the class named unmarried.

From the pie chart it can be concluded that about 72% investors were married and about 28% investors were unmarried.

3.6 Monthly Income of the Respondents

Monthly income is an important factor regarding socio-economic condition of the investor. We find out mean, median and mode to find out the central tendency of income and we also find out standard deviation and variance to analyze dispersion. We also present the data on a bar chart and frequency polygon.

Frequency Distribution

Monthly Income Frequency Cumulative Frequencybelow 10,000 25 2510000-30,000 69 9430,000-50,000 44 13850,000-70,000 28 16670,000-90,000 4 170above 90,000 10 180

Below 10000

10000-30000

30000-50000

50000-70000

70000-90000

Above 90000

01020304050607080

Bar Chart of the Monthly Income of the Respondents

frequency

14%

38%24%

16%

2%6%

Pie Chart of the Monthly Income of the Respondents

Below 1000010000-3000030000-5000050000-7000070000-90000Above 90000

From the frequency distribution it can be concluded that the lowest income is (10000) and the highest income is above 90000. The total number of frequency is 180. The class interval is 20000.

In the bar chart the most frequency lied between 10000 to 30000.That means most of the investors monthly income is between 10000 to 30000

Class Frequency Tally Relative frequency Cumulative frequency

Class Midpoint

1-3 60 IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII

0.33 60 2

3-5 80 IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII IIIII

0.44 140 4

5-7 40 IIIII IIIII IIIII IIII IIIII IIIII IIIII IIIII

0.22 180 6

3.7 Members Dependent on Respondent’s Income

Category 1 Category 2 Category 3 Category 4012345

Series 1 4.5

Series 2 2.8

Series 3 5Chart Title

Axis Title

59%23%

10%9%

Pie Chart1st Qtr2nd Qtr3rd Qtr4th Qtr

Grouped Data:Arithmetic mean

(X)=Efm n

=60*2+80*4+40*6

180

=3.78

Interpretation: The average members dependency on each stockholder is 4 person

Grouped data:Standared Deviation

Class Frequency Class Midpoint M-(X) (M-(x))2 F(M-(x))21-3 60 2 -1.78 3.19 191.43-5 80 4 0.22 0.05 4.005-7 40 6 2.22 4.93 197.2

S=1.48

Total number of observations=180

K=8

Class interval=4

Class Midpoint(M) Frequency(f) C.f. M-x (M-x) f(M-x)1984-1988 1986 2 2 -21 441 8821988-1992 1990 3 5 -17 289 8671992-1996 1994 6 11 -13 169 10141996-2000 1998 13 24 -9 81 10532000-2004 2002 14 38 -5 25 3502004-2008 2006 34 72 -1 1 342008-2012 2010 92 164 3 9 8282012-2016 2014 16 180 7 49 784Total 180 5812

3.8 First Involvement in Share market

1984-198812%

1988-199212%

1992-199612%

1996-200012%

2000-200413%

2004-200813%

2008-201213%

2012-201613%

First Involvement in Share market

1 2 3 4 50%

20%40%60%80%

100%

Frequency Polygon of First Involovement on

Share Market

Midpoint(M) Frequency(f)

Mean(x) = ∑fn N

361256=

180

=2007

∑f_fc 2

Median = L + *ImFm

90 - 72=2008 + * 4

92

=2008 + 0.78

=2008.78

=2009

Standard deviation = √∑fi(xi- )²/n-1x

=√ (5812/179)

=√32.4693

=5.698

3 (Mean –median )S.K = ----------------------------------

S.D

3 (2007 – 2009 ) =-----------------------------

5.698

= - 1.054Interpretation:Most of the investors invested in share market between 2000-2014. Almost 13% investors invested in these years. The mean is 2007. The median is 2009. The dispersion of the data from mean is .05%. there is negative skewness between the variables.

Educational background is a vital factor regarding the investors’ socio-economic condition. In our survey we found that most of the investors are graduated or post- graduated. We used pie chart to show the multiple educational bases of general investors.

Educational Qualification FrequencyBelow SSC 3SSC 18HSC 27Graduation 52Post Graduation 80

3.9 Educational Background

2%10%

15%

29%

44%

Educational Qualifi-cation

Below SSCSSCHSCGraduationPost Graduation

Below SS

C SSC HSC

Graduati

on

Post Grad

uation

Total

04080

120160

3 18 2780 52

180

Bar chart of Educational Background

Frequency

We include this in our survey to find out how many members depend on their share market investment. We present the data on a bar chart for your convenience.

Expenditure Dependency FrequencyYes 64No 116

3.10 Expenditure Dependency on Share Market Income

Yes No0

20406080

100120140

Bar Chart of Expen-diture DEpendency on Share Market

Axis Title

64

116

Pie Chart of Expenditure DEpendency on Share

MarketYesNo

Interpretation: From the frequency table it can be concluded that the lowest frequency is 64 and the

highest frequency is 116. The total number of frequency is 180. The highest frequency is in the class named “no” and the lowest frequency is in the class named “yes”.

From the pie chart it can be concluded that about 36% investors depend on share market and about 64% investors don’t depend

CHAPTER 4: Conclusion

CHAPTER 5: AppendixA Survey on Socio-Economic Background of General Investors.

This survey is one of the partial requirement of the Business Statistics course in the Department of Finance, University of Dhaka. The main purpose of this course is to give an overview of the descriptive statistics as well as presenting the statistics in an understandable way. The intention of this survey is to identify the socio-economic background of the general investors through descriptive statistics. Your response will help them to prepare their term paper. The information that is provided by you will be used only for academic purpose.

Mr. Mohammed Abdullah Al Mamun Lecturer Department Of Finance University of Dhaka

Survey Questionnaire

1. Name :

2. Age:

Below 20 20-30 30-40 40-50 Above 60

3. Contact Number:4. Gender :

Male Female

5. Main Occupation : Financial Service Government Service Business Academician Other Service

6. Marital Status :

Married Unmarried

7. Monthly Income (In Taka): Below 10000 10000-30000 30000-50000 50000-70000 70000-90000 Above 90000

8. Members dependent on your income : 1 2 3 4 5 6 Above 6

9. First involvement in share market (in year):

10. Educational Background: Below S.S.C S.S.C H.S.C Graduation Post Graduation

11. Expenditure dependency on Share market Income? Yes No

Chapter 6: Reference

Data collected from the assigned securities. Information is taken from our text book. Data collected from internet.