The document provides details about a report on the socio-economic background of general investors in Bangladesh. It includes an introduction outlining the objectives and methodology of the report. It also describes the theoretical background on various statistical tools and techniques used in the analysis. The main body of the report presents statistical analysis on the socio-economic characteristics of investors such as their age, gender, income, and expenditure patterns. Graphs and regression analysis are used to analyze the survey data collected from brokerage houses. The conclusions provide insights about investors gleaned from applying statistical methods.

1. A Report on
Socio-Economic background of General Investors

2. 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

3. SL No. Name ID No.
1
2
3
4
5 =
6
7
8
9
Department of ……
University of Dhaka
Group Details

4. ACKNOWLEDGEMENT
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

5. Letter of Transmittal
February 18, 2014
…………………………
Lecturer
Department 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.
EXECUTIVE
SUMMARY

6. The main segment of the report started with an elaborate discussion of different securities and
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.

7. Table of Contents
Chapter No. Chapter Title Page
Number
Chapter 01 Introduction
1.1 introduction
1.2 objective of the report
1.3 Methodology
1.4 Limitations
Chapter 02 THEORITICAL BACKGROUND
Chapter 03 Statistical Analysis of the Socio-
Economic Background of General
Investors
3.1 List of the brokerage house
3.2 Age of the respondents
3.3 Gender of the respondents
3.4 Occupation of the respondents
3.5Marital status of the
respondents
3.6 Monthly income of the
respondents
3.7 Member dependency on
income
3.8 First share involvement of the
respondents
3.9 Educational background of the
respondents
3.10 Expenditure dependency of

8. the respondents
Chapter 04 conclusion
Chapter 05 Appendix
Chapter 06 References

9. 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.
1.1 Introduction:
1.2 Objective of the Report
1.3 Methodology

10. Secondary data sources:
 Collecting information about the brokerage houses from the
share market website.
 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.
1.4 Limitations of the Report

11. CHAPTER 2: THEORITICAL BACKGROUND
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:
• Singularsense:Statisticsin singularsense meansa subject or scientificdiscipline.
• 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.
Data
Information
Konwledge
2.1 Statistics
2.2 The Statistical Process
2.3 Types of Statistics

12. 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.
Statistical
Methods
Descriptive
Statistics
Inferential
Statistics
Data
Numerical
(Quantitative)
Categorical
(Qualitative)
Discrete Continuous
Data
Numerical
(Quantitative)
Categorical
(Qualitative)
Discrete Continuous
2.3.1 Descriptive Statistics
2.3.2 Inferential Statistics
2.4 Types of Data

13. Data can be further classified as being qualitative or quantitative.
 Labelsor names usedto identifyan attribute of eachelement
 Oftenreferredto as categorical data
 Use eitherthe nominal or ordinal scale ofmeasurement
 Appropriate statistical analyses are rather limited
In general, there are more alternatives for statistical analysis when the data are quantitative.
 Quantitativedataindicate how many or how much
 Discrete: ifmeasuring how many
Continuous: ifmeasuringhow much
 Quantitative data are always numeric.
 Ordinaryarithmeticoperationsare meaningful forquantitativedata.
Nominal level Data
Ordinal-level data
Interval-Level Data
Ratio-Level Data
2.4.1 Qualitative Data
2.4.1 Quantitative Data
2.5 Levels of Measurement

14. Nominal: Data are labels or names used to identify an attribute of the element. nonnumeric
label or numeric code may be used.
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- Selectnumber ofclasses
• Usuallybetween5and 20 inclusive
3- Compute class intervals (width)
4- Determine class boundaries(limits)
5- Compute class midpoints
6- Count observations& assignto classes
2.6 Describing Data
2.6.1 Frequency Distribution
2.6.1.1 Frequency DistributionTable Steps

15. The relative frequencyof aclass isthe fractionor Proportionof the total numberof data items
Belongingtothe class.
 A bar graph isa graphical device forpresentingqualitativedata.
 On one axis(usuallythe horizontal axis),we specifythe labelsthatare usedfor each of the
classes.
 The bars are separatedtoemphasize the factthateach classis a separate category.
The pie chart is a commonlyusedgraphical device forpresenting relative frequencydistributionsfor
qualitative data.
Anothercommongraphical presentationof quantitative dataisa histogram.
 The variable of interestisplacedonthe horizontal axis.
 A rectangle isdrawnabove eachclassinterval with itsheight correspondingtothe interval’s
frequency, relative frequency,orpercent frequency
 Unlike abar graph,a histogramhas no natural separation between rectangles of adjacent
classes
2.6.2 Relative Frequency Distribution
2.6.3 Bar Graph
2.6.4 Pie Chart
2.6.5 Histogram

16. showsthe number of items with values less than or equal to the upper limit of each class.
 Measuresof Location : Mean, Median,Mode,percentiles,Quarterlies
 Measuresof Variability:
The meanof a data setisthe average of all the data values.Aswe said,the sample mean isthe
pointestimatorof the populationmean m.
Propertiesofthe ArithmeticMean:
1- Everyset of interval-levelandratio-level datahasa mean.
2- All the valuesare includedincomputingthe mean.
3- A setof data has a unique mean.
4- The meanisaffectedbyunusuallylarge orsmall datavalues.
5- The arithmeticmeanisthe onlymeasure of central tendencywhere the sumof thedeviationsof
each valuefromthe mean is zero.
GeometricMean:
 It isa kindof average of a setof numbersthat isdifferentfromthe arithmeticaverage.
 The geometricmeaniswell definedonlyforsetsof positive real numbers(nonegative or
zerovalue).
 Thisis calculatedbymultiplyingall the numbers(call the numberof numbersn),andtaking
the nth root of the total.
 A commonexample of where the geometricmeanisthe correct choice iswhenaveraging
growthrates.
2.6.6 Cumulative Frequency Distribution
2.7 Numerical Measures
2.7.1 Mean

17. Formula:
GM = ((X1)(X2)(X3)........(XN))1/N
where
X = Individual growthfactor
N = Sample size (Numberof
The medianof a data setisthe value inthe middlewhenthe dataitemsare arrangedinascendingorder.
 Wheneveradata sethas extreme values,the median isthe preferredmeasure of central
location
 The medianisthe measure of locationmostoftenreportedforannual income andproperty
value data
 A fewextremelylarge incomesorpropertyvalues caninflate the mean
2
1
PointMediangPositionin


n
Median = L + (n/2 – p.c.f)/f * h
Where:
L = The lower class boundary of median class
h = The size of median class i.e. difference between upper and lower class boundaries of median
class
f = The frequency of median class
p.c.f = Previous cumulative frequency of the median class
n/2 = Total no. of observations divided by 2...OR...summation of F divided by 2
2.7.2 Median
2.7.2.1 Median Grouped Data

18. The mode of a data setis the value thatoccurs with greatest frequency.
 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 class
fm = The Frequency of the modal class
f1 = The previous frequency of the modal class
f2 = The next frequency of the modal class
h = 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 valuesthatdividesthe datasetinto four equal parts are called quartiles
 Percentiles: A percentile providesinformationabouthow the data are spread over the
interval from the smallest value to the largest value.
2.8 Mode
2.8.1 Mode Grouped Data
2.9 Numerical Measures

19. The pth 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
The degree towhichnumerical datatendto spreadabout 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 deviationof adata setisthe positive
square root of the varianceItismeasuredinthe same unitsasthe data, making
it more easilyinterpretedthanthe variance.Mostcommonlyusedmeasure of variationin
Businessapplication
 Measure of relative dispersion
 Alwaysa%
 CV is the standarddeviationexpressedaspercentof the mean
 Usedto compare twoor more groups
 Weakness:CV isundefinedif the meaniszeroorif data are negative.
 Thus,CV isusedonlyforvariableswhose valuesare X>=0
2.10 Measures of Variability
2.10.1 Standard Deviation
2.10.2 Coefficientof Variation

20.  Sometimestwoormore variablesare relatedinsucha waythat movementinone variable is
accompaniedbythe movementsinothervariables.
 For example there existsarelationshipbetweenfamilyincome andthe amountspentonluxury
items,increase inthe quantityof rainfallandthe productionof crops,increase ingovt.
expenditure andthe livingstandard,flow of FDIandGDP growthetc.
 The statistical tool usedtomeasure thisrelationshipbetweentwoormore variablesiscalled
correlation.Correlationisananalysisof the co-variationof twoormore variables.
 Independentvariable:isavariable thatcan be controlledormanipulatedorusedtosee the
impacton dependent variable.
 Dependentvariable:isavariable thatcannotbe controlledormanipulated. Itsvaluesare
predictedfromthe independentvariable
 The independentanddependentcanbe plottedona graph calleda scatterplot.
 By convention,the independentvariable isplottedonthe horizontal x-axis. The dependent
variable isplottedonthe vertical y-axis
 The correlationcoefficient (r) computedfromthe sample datameasuresthe strength
(Strong/moderate/low) anddirection(positive/negative)of arelationshipbetweentwo
variables.
 Formulaforcoefficientof Correlation







n
i
i
n
i
i
n
i
ii
YYXX
YYXX
r
1
2
1
2
1
)()(
))((
2.11 Correlation
2.11.1 Independent and Dependent Variable
de
d
2.11.2 Scatter Plot
2.11.3 Coefficientof Correlation

21. CHAPTER 3: Statistical Analysis of the Socio-
Economic Background of General Investors
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 securities
2. ICB Securities Trading Company Limited
3. Shakil Rizvi Stock Limited
4. Ahmed Iqbal Hasan Securities Ltd
5. Ibrahim Securities Limited
6. DBL Securities
7. Anwar Securities Limited
8. Lanka Bangla Securities
9.
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 respondents
Class Limit Frequency
Below 20 2
20-30 45
30-40 66
40-50 45
Above 50 22
total 180
3.1 List of the Brokerage House:
3.2 Age of the respondents

22. 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:
1% 12%
18%
13%
6%
50%
Pie Chart of the Age of the
Respondents
below 20
20-30
30-40
40-50
above 50
total
below 20 20-30 30-40 40-50 above 50 total
Series1 2 45 66 45 22 180
0
20
40
60
80
100
120
140
160
180
200
frequency
Bar Chart of the Age of the
Respondents
3.3 Gender of the Respondents

23. Gender Frequency
Male 168
Female 12
Total 180
93%
7%
Pie Chart of the Gender of the
Respondents
Male Female
0
50
100
150
200
Male Female
Bar Chart of the Gender of the
Respondents
Series1

24. 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 table
Occupation Frequency
Financial service 30
Government service 09
Business 85
Academician 10
Other service 46
Total 180
30
9
85
10
46
Pie Chart of the Occupation of
the Respodents
Financial Services
Government Services
Business
Academician
Other Services
3.4 Occupation of the Respondents

25.  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 Frequency
Married
Unmarried
129
51
0
20
40
60
80
100
Bar Chart of the Occupation of
the Respondents
Series2
Series1
3.5 Marital Status

26. Total 180
 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.
129
51
Marital status
married
unmarried
129
51
0
20
40
60
80
100
120
140
married unmarried
Bar Chart of the Marital Status of
the Respondents
frequency

27. Monthlyincome isan importantfactorregardingsocio-economicconditionof 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
MonthlyIncome Frequency Cumulative Frequency
below10,000 25 25
10000-30,000 69 94
30,000-50,000 44 138
50,000-70,000 28 166
70,000-90,000 4 170
above 90,000 10 180
0
10
20
30
40
50
60
70
80
Bar Chart of the Monthly Income
of the Respondents
frequency
3.6 Monthly Income of the Respondents

28.  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
ssaCC ycqeuqerF yassF qsatalqR
ycqeuqerF
suiusatalqR
ycqeuqerF
ssaCCR
taiopaet
1-3 06 IIIIIRIIIIIRIIIIIRIIIIIR
IIIIIRIIIIIRIIIIIRIIIIIR
IIIIIRIIIIIRIIIIIRIIIIIR
6.33 06 2
3-5 06 IIIIIRIIIIIRIIIIIRIIIIIR
IIIIIRIIIIIRIIIIIRIIIIIR
IIIIIRIIIIIRIIIIIRIIIIIR
IIIIIRIIIIIRIIIIIRIIIIIR
6.44 146 4
5-7 46 IIIIIRIIIIIRIIIIIRIIIIR
IIIIIRIIIIIRIIIIIRIIIII
6.22 106 0
14%
38%24%
16%
2% 6%
Pie Chart of the Monthly Income
of the Respondents
Below 10000
10000-30000
30000-50000
50000-70000
70000-90000
Above 90000
3.7 Members Dependent on Respondent’s
Income

29. RRRRRRRRRRRRRRRR
RacpuoqiRuata :ncat iqtarRiqae
(X=)Eyi
RRRRRRRRRRRRRe
RRRRRRR= 60*2+80*4+40*6
RRRRRRRRRRRRRRRRR106
RRRRRRRRR= 3.78R
Ietqcocqtatape:R y qRalqcakqRiqihqcCRiqoqeiqerFRpeRqar RCtprg psiqcRaCR 4RoqcCpe
RRRRRR
RRRRRRRRRRRRRRRRRRRRRRR
0
2
4
6
Category 1 Category 2 Category 3 Category 4
Series 1, 4.5
Series 2, 2.8
Series 3, 5
AxisTitle
Chart Title
58%23%
10%
9%
Pie Chart
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr

30. RacpuoqiRiata :ntaeiacqiRuqlaatape
ssaCC ycqeuqerF ssaCCR
taiopaet
t-)X( (t-
(x))2
y)t-
)x((2
1-3 06 2
-1.78 3.11 111.4
3-5 06 4
6.22 6.65 4.66
5-7 46 0
2.22 4.13 117.2
n=1.40
Total numberof observations=180
K=8
Classinterval=4
Class Midpoint(M) Frequency(f) C.f. M-x (M-x) f(M-x)
1984-1988 1986 2 2 -21 441 882
1988-1992 1990 3 5 -17 289 867
1992-1996 1994 6 11 -13 169 1014
1996-2000 1998 13 24 -9 81 1053
2000-2004 2002 14 38 -5 25 350
2004-2008 2006 34 72 -1 1 34
3.8 First Involvement in Share market

31. 2008-2012 2010 92 164 3 9 828
2012-2016 2014 16 180 7 49 784
Total 180 5812
1984-1988
12%
1988-1992
12%
1992-1996
12%
1996-2000
12%
2000-2004
13%
2004-2008
13%
2008-2012
13%
2012-2016
13%
First Involvement in Share
market
99%
99%
99%
99%
100%
100%
100%
1 2 3 4 5
Frequency Polygon of First
Involovement on Share
Market
Midpoint(M) Frequency(f)

32. Mean(x) = ∑fn
N
361256
=
180
=2007
∑f_fc
2
Median = L + *Im
Fm
90 - 72
=2008 + * 4
92
=2008 + 0.78
=2008.78
=2009
Standard deviation = √∑fi(xi-x̄)²/n-1

33. =√ (5012/171)
=√32.4013
=5.698
3 (Mean –median )
S.K = ----------------------------------
S.D
3 (2007 – 2009 )
=-----------------------------
5.698
= - 1.054
Interpretation:
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 backgroundisa vital factorregardingthe investors’socio-economiccondition.Inoursurvey
we foundthat mostof the investorsare graduatedorpost- graduated.We usedpie chart to show the
multiple educational basesof general investors.
3.9 Educational Background

34. Educational Qualification Frequency
Below SSC 3
SSC 18
HSC 27
Graduation 52
Post Graduation 80
2%
10%
15%
29%
44%
Educational Qualification
Below SSC
SSC
HSC
Graduation
Post Graduation
0
50
100
150
200
3 18 27
80
52
180
Bar chart of Educational
Background
Frequency
3.10 Expenditure Dependency on Share
Market Income

35. We include thisinoursurveytofind outhow manymembersdependontheirshare marketinvestment.
We present the data on a bar chart for your convenience.
Expenditure Dependency Frequency
Yes 64
No 116
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”.
Yes No
Frequency 64 116
0
50
100
150
AxisTitle
Bar Chart of Expenditure
DEpendency on Share
Market
64
116
Pie Chart of Expenditure
DEpendency on Share Market
Yes
No

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

37. CHAPTER 4: Conclusion

38. CHAPTER 5: Appendix
A 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

39.  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

40. Chapter 6: Reference
 Data collected from the assigned securities.
 Information is taken from our text book.
 Data collected from internet.