Part A: Statistics for Economics Complete notes (50 Marks expected)
Q.1. What is economics?
Who is called father of economics and statistics?
Ans: Economics is the science which studies human behaviour as a
relationship between scare means and ends.
Adam smith is called father of economics.
Gottfried Achenwall is called father of statistics.
Q.2. Define the term
Statistics. What are its Characteristics? Mention its Functions and
Limitations.
Ans: Statistics: The word Statistics seems to have been derived
from the Latin word “status” or the Italian word Statista.
By Statistics we mean aggregates of facts
affected to a marked extent by multiplicity of causes, numerically expressed,
enumerated or estimated according to reasonable standards of accuracy,
collected in a systematic manner for a predetermined purpose and placed in
relation to each other.
Characteristics
of Statistics:
(i) Statistics are aggregates of facts. (ii)
Statistics must be numerically expressed.
(iii) Statistics should be capable of comparison and connected to each
other. (iv) Statistics should be collected in a systematic manner. (v)
Statistics should be collected for a definite purpose.
Importance
of Statistics: Statistics is widely used in many fields.
a] Importance to the Government
Ø Statistics is used in administration and efficient
Ø functioning of departments. It collects data to fulfill its
welfare objectives.
b] Importance of Statistics in Economics:
Ø Statistics helps in making economic laws like law of demand and
concept of elasticity.
Ø It helps in understanding and solving economic problem.
Ø It helps in studying market structure.
Ø It helps in finding mathematical relations between variables.
Limitations
of statistics are as follows:
(i) Statistics deals only with quantitative
characteristics. (ii) Statistics deals with aggregates not with individuals.
(iii) Statistical laws are not perfectly accurate. (iv) Statistical results are
only an average. (v) Statistics is only
one of the methods of studying a problem. Statistical tools do not provide the
best solution under all circumstances. (vi) Statistics can be misused.
Q.3. What are various
types of Statistical Data? Mention their merits and demerits.
Ans: Statistical data are of two types
(a) Primary data
(b) Secondary data.
Primary
Data: Data which are collected for the first time for a specific
purpose are known as Primary data. For example: Population census, National
income collected by government, Textile Bulletin (Monthly), Reserve bank of
India Bulletin (Monthly) etc.
Secondary
Data: Data which are collected by someone else, used in investigation
are knows as Secondary data. Data are primary to the collector, but secondary
to the user. For example: Statistical abstract of the Indian Union, Monthly
abstract of statistics, Monthly statistical digest, International Labour
Bulletin (Monthly).
Merits and
Demerits of Primary Data:
Merits:
(a) They are reliable and accurate. (b) It is more suitable if the field of enquiry
is small.
Demerits:
(a) It the field of enquiry is too wide, it is
not suitable. (b) Collection of primary data is costly and time consuming. (c)
Personal Bias may affect the data.
Merits and
Demerits of Secondary Data:
Merits:
(a) While using secondary data, time and
labour are saved. (b) It may also be collected from unpublished form.
Demerits:
(a) Degree of accuracy may not be acceptable.
(b) Secondary Data may or may not fit the need of the project. (c) Data may be
influenced by personal bias.
Q.4. Distinguish between
Primary data and Secondary data.
Ans: Difference between Primary Data and Secondary Data:
(a) Primary data are those which are collected
for the first time and thus original in character. While Secondary data are
those which are already collected by someone else.
(b) Primary data are in the form of
rawmaterial, whereas Secondary data are in the form of finished products.
(c) Data are primary in the hands of
institutions collecting it while they are secondary for all others.
Q.5. What are various
sources of Secondary Data? Mention the points which should be considered before
using secondary data.
Ans: Sources of Secondary Data:
(a) Official publication by the central and
state governments, district Boards. (b) Publication by research institutions,
Universities etc. (c) Economic Journals. (d) Commercial Journals. (e) Reports
of Committees, commissions.
Precautions
in the use of Secondary Data:
(i) Suitability: The investigator must check
before using secondary data that whether they are suitable for the present
purpose or not.
(ii) Adequacy: The investigator has to determine
whether they are adequate for the present purpose of investigators.
(iii) Dependability.
(iv) Units in which data are available.
Q.6. What are various
essential qualities of Secondary data? Explain some effective methods of
collecting primary data.
Ans: Qualities of Secondary Data:
(a) Data should be reliable (b) Data should be
suitable for the purpose of investigator. (c) Data should be adequate (d) Data
should be collected by trained investigator.
Methods of
collecting primary Data
(a)
Direct Personal Observation: Under this method, the investigator
collects the data personally from the persons concerned.
(b) Indirect Oral Investigation:  Under this
method, the investigator collects the data from third parties capable of
supplying the necessary information.
(c) Schedule and questionnaire: A list of
question regarding the enquiry is prepared and printed and send to the person
concerned.
(d) Local reports:  This method gives only
approximate results at a low cost.
Q.7. What are various
stages involved in statistical investigation? Explain them briefly.
Ans: Various stages in statistical investigation: There are five
stages in a statistical investigation which are given below:
(i) Collection of Data.
(ii) Organisation of Data: Organising of data
involves three steps which are (a) Editing of data (b) Classification of data
according to some common characteristics and (c) Tabulation.
(iii) Presentation of Data.
(iv) Analysis: After collection, organisation
and presentation, data are analysed.
(v) Interpretation: The last stage is
interpretation which is a difficult task and requires a high degree of skill.
Q.8. What is
Questionnaire? What are its essential characteristics?
Ans: Questionnaire: A Questionnaire is simply a list of questions
in a printed sheet relating to survey which the investigators asks to the
informants and the answers of the informants are noted down against the
respective questions on the sheet.
Characteristics of an ideal Questionnaire:
(i) The Schedule of question must not be lengthy.
(ii) It should be clear and simple.
(iii) Questions should be arranged in a
logical sequence.
(iv) The Units of information should be Cleary
shown in the sheet.
Q.9. Define the term
population and sample. What is sample and census survey? Distinguish between
them.
Ans: Population and Sample
Population: Statistics is taken in relation to
a large data. Single and unconnected data is not statistics. In the field of a
statistical enquiry there may be persons, items or any other similar units. The
aggregate of all such units under consideration is called “Universe or
Population”.
Sample: If a part is selected out of the
universe then the selected part or portion is known as sample. Sample is only a
part of the universe.
Sample
survey and Census Survey:
Sample survey: It is a survey under which only
a part taken out of the universe is investigated. It is not essential to
investigate every individual item of the Universe.
Census survey and complete enumeration: Under
Census survey detail information regarding every individual person or item of a
given universe is collected.
Difference
between Census and Sample survey:
The following are the differences between
Census and Sample method of investigation:
(a) Under Census method, each and every
individual item is investigated whereas under sample survey only a part of
universe is investigated.
(b) There is no chance of sampling error in
census survey whereas sampling error cannot be avoided under sample survey.
(c) Census survey is more time consuming and
costly as compared to sample survey.
(d) Census survey is an old method and it less
systematic than the sample survey.
Q.10. Mention the Merits
and Demerits of Census and Sample Survey.
Ans: Merits and Demerits of Census:
Merits:
(a) Since all the individuals of the universe
are investigated, highest degree of accuracy is obtained.
(b) It
is more suitable if the field of enquiry is small.
Demerits:
(a) It the field of enquiry is too wide, it is
not suitable.
(b) Collection of data is costly and time
consuming.
Merits and
Demerits of sample survey:
Merits:
(a) Time and labour are saved. (b) It may also
be collected from unpublished form. (c) If secondary Data are available, they
are much quicker to obtain than primary data.
Demerits:
(a) Degree of accuracy may not be acceptable.
(b) Data may or may not fit the need of the project. (c) Data may be influenced
by personal bias of investigator.
Q.11. What are various types of diagrams and graphs? Distinguish
between diagrams and graphs. What are the uses and limitations of diagrams and
graphs?
Ans: Types of diagrams and Graphs:
a) Simple Bar Chart b) Multiple
Bar Chart or Cluster Chart c) Staked Bar Chart or SubDivided Bar Chart or
Component Bar Chart d) Simple Component Bar Chart e) Percentage Component Bar
Chart f) SubDivided Rectangular Bar Chart g) Pie Chart
Types of
Diagrams/Charts:
a)
Histogram b) Frequency Curve and Polygon c) Lorenz Curve d) Histogram
Difference
Between Diagrams And Graphs
a) A graph needs a graph paper but a diagram can be drawn on a plain
paper.
b) As diagrams are attractive to look at, they are used for. Graphs on the
other hand are more useful to statisticians and research workers for the purpose of further analysis.
c) For representing frequency distribution, diagrams are rarely used
when compared with graphs. For example, for the time series graphs are more appropriate than diagrams.
Uses of
Diagrams and Graphs:
Diagrams and graphs are extremely useful due
to the following reasons:
(i) Information presented though
diagrams and graphs can be understood easily just in a bird’s eye view.
(ii) Diagrams and graphs produce a
greater lasting impression on the mind of the readers.
(iv) They facilitate ready comparison
of data over time and space.
However, graphic and diagrammatic
presentations have some limitations:
(i) Unlike a table a diagram or a graph does not show the exact value
of a variable.
(ii) Further, a limited set of facts can be presented through such
devices like diagram and graph.
Q.12. What do you mean by index numbers? What are
its features?
Ans: Index number is an
indicator of changes in prices and quantities. It is a specialized average
designed to measure the change in a group of related variables over a period of
time. It is also an indicator of inflationary or deflationary tendencies.
Following are the various feature of index number:
1. Measures of relative changes:  Index
number measure relative or percentage changes in the variable over time.
2.
Quantitative expression:  Index numbers offer a precise measurement of the
quantitative change in the concerned variable over time.
3.
Average:  Index number show changes in terms of average.
Q.13. Mention few uses of index numbers. Or why
index number is called economic barometer? What are its limitations?
Ans: Advantages of index number
1. Measurement of change in the price level or
the value of money. 2. Index number helps to ascertain the living standards of
people. 3. Price index numbers serve as a useful guide to the business
community in planning. 4. Index of exports and imports provides useful
information regarding foreign trade.
Limitation of index number
1. Not completely true:  Index number not
fully true. 2. International comparison
is not possible 3. Limited use:  Index numbers are prepared with certain
specific objective.
Q.14. what are the problems in the constructions of
index numbers?
Ans: Following are the main
Problems in the construction of index number
1. Purpose of index number. 2. Selection of
base year. 3. Selection of goods and services. 4. Selection of
price 5. Choice of average (simple or geometric average). 6) Selection of
appropriate weights. 7) Selection of appropriate formula (Fisher’s or
Laspeyre’s).
Q.15.Define cost of living index number. What are
the uses of cost of living index number?
Ans:  Cost of living index number (CLI): Cost of living index
numbers generally represent the average change in prices over a period of time,
paid by a consumer for a fixed set of goods and services.
Uses of cost of living index:
1. CLI numbers are used for adjustment of
dearness allowance to maintain the same standard of living. 2. It is used in
fixing various economic policies. 3. Its helps in measuring purchasing power of
money. 4. Real wages can be obtained
with the help of CLI numbers.
Q.16. Which is the most ideal
formula for constructing index no. and Why?
Ans: 
Fisher’s index is regarded as ideal index because:
i)
It considers both base year and current year’s
price and quantity.
ii)
It satisfies both time reversal and factor
reversal test.
iii)
It is based on Geometric mean which is
theoretically considered to be the best average of constructing index number.
iv)
It is free from bias as it considers both
current year and base year price and qty.
Q.17. Define Correlation
analysis. What are its various kinds?
Ans:  Definition:  Correlation is the degree of the relationship
between two or more variables. It does not explain the cause behind the
relationship.
Kinds of correlation may be studied on the
basis of:
(a) Linear correlation:  Correlation is said
to be linear when one variable move with the other variable in fixed proportion
(b) Nonlinear correlation:  Correlation is
said to be nonlinear when one variable move with the other variable in changing
proportion.
(c) Simple correlation:  When only two
variables are studied it is a simple correlation.
(d) Partial correlation:  When more than two
variables are studied keeping other variables constant, it is called partial
correlation.
(e) Multiple correlations:  When at least
three variables are studied and their relationships are simultaneously worked
out, it is a case of multiple correlations
Q.18.What are the uses
and limitations of Correlation?
Ans:  Following are the main advantages of correlation:
1. It gives a precise quantitative value
indicating the degree of relationship existing between the two variables. 2. It measures the direction as well as
relationship between the two variables.
3. The effect of correlation is to reduce the range of uncertainty in
predictions.
Following are the main limitations of
correlation:
1. Extreme items affect the value of the
coefficient of correlation. 2. Its
computational method is difficult as compared to other methods. 3. It assumes the linear relationship between
the two variables, whether such relationship exist or not.
Q.19. What are the
different degrees of Correlation?
Ans: The different degrees of correlation are:
i)
Perfect Correlation:  It two variables vary
in same proportion, and then the correlation is said to be perfect correlation.
ii)
Positive Correlation:  If increase (or
decrease) in one variable corresponds to an increase (or decrease) in the
other, the correlation is said to be positive correlation.
iii) Negative
Correlation:  If increase (or decrease) in one variable corresponds to a
decrease (or increase) in the other, the correlation is said to be positive
correlation.
iv)
Zero or No Correlation:  If change in one
variable does not other, than there is no or zero correlation.
Q.20. Explain Karl
Pearson’s coefficient of correlation and spearmen’s rank correlation.
Ans: Karl Pearson’s Coefficient of
correlation: The Correlation
coefficient (r), also called as the linear correlation coefficient measures the
strength and direction of a linear relationship between two variables. The
value of r lies between 1 to +1.
Spearman’s rank Coefficient of
correlation:  This is a qualitative method of measuring correlation
coefficient. Qualities such as beauty, honesty, ability, etc. cannot be
measured in quantitative terms. So, ranks are used to determine the correlation
coefficient.
Q.21.What are the
desirable properties of a good average and good measure of dispersion.
Ans:  The following
are the important properties which a good average should satisfy:
a) It should be easy
to understand. b) It should be simple to compute. c) It should be based on all
the items. d) It should not be affected by extreme values. e) It should be
rigidly defined. f) It should be capable
of further algebraic treatment.
Q.22.Define
Arithmetic Mean (A.M). What are its properties? Explain its merits and
demerits.
Ans:  Arithmetic
Mean:  It is a value obtained by adding together all the items and by dividing
the total by the number of items. It is also called average. It is the most
popular and widely used measure for representing the entire data by one
value.
Properties of
arithmetic mean:
1.
The sum of deviations of the items from the
arithmetic mean is always zero i.e.
∑(X–X) =0.
2.
The Sum of the squared deviations of the
items from A.M. is minimum that is less than the sum of the squared deviations
of the items from any other values.
Merits of A.M.:
Ø It is simple to
understand and easy to calculate.
Ø It is affected by the
value of every item in the series.
Ø It is capable of
further algebraic treatment.
Demerits of A.M.:
Ø It is affected by
extreme items i.e., very small and very large items.
Ø It can hardly be
located by inspection.
Q.23.Define
Geometric Mean (G.M). Mention its merits and demerits. What are its Uses?
Ans: G.M.:It is defined as nth root of the
product of n items or values. i.e., G.M. = ^{n}√ (x1. x2. x3 ……xn)
Merits of G.M.:
Ø
It is not
affected by the extreme items in the series.
Ø
It is rigidly
defined and its value is a precise figure.
Ø
It is capable
of further algebraic treatment.
Demerits of G.M.:
Ø It is difficult to understand and to
compute.
Ø It cannot be computed when one of the values is 0 or negative.
Q.24.Define Harmonic
Mean (H.M). Mention its merits and demerits. What are its Uses?
Ans:  H.M.: It is defined
as the reciprocal of the arithmetic mean of the reciprocal of the individual
observations.
Merits of H.M.:
Ø
Like AM and
GM, it is also based on all observations.
Ø
It is capable
of further algebraic treatment.
Demerits of H.M.:
Ø It is difficult to understand and to
compute.
Ø It cannot be computed when one of the values is 0 or negative.
Q.25.Define Median. Mention its merits and demerits.
Ans: Median: Median
may be defined as the size (actual or estimated) to that item which falls in
the middle of a series arranged either in the ascending order or the descending
order of their magnitude. It lies in the centre of a series and divides the
series into two equal parts. Median is also known as an average of position.
Merits of Median:
Ø It is simple to
understand and easy to calculate, particularly is individual and discrete
series.
Ø It is not affected by
the extreme items in the series.
Ø It can be determined graphically.
Demerits of Median:
Ø It does not consider all variables because it is a positional
average.
Ø The value of median is affected more by sampling fluctuations
Ø It is not capable of further algebraic treatment. Like mean, combined median cannot be calculated.
Q.26.Define Mode.
Mention its merits and demerits.
Ans:  Mode:  Mode is that value a dataset, which is repeated most often in the database. In other words, mode is the value, which is predominant in the series or is at the position of greatest density. Mode may or may not exist in a series, or if it exists, it may not be unique, or its position may be somewhat uncertain.
Ans:  Mode:  Mode is that value a dataset, which is repeated most often in the database. In other words, mode is the value, which is predominant in the series or is at the position of greatest density. Mode may or may not exist in a series, or if it exists, it may not be unique, or its position may be somewhat uncertain.
Merits of Mode:
Ø Mode is the most representative value of distribution, it is
useful to calculate model wage.
Ø
It is not
affected by the extreme items in the series.
Ø
It can be
determined graphically.
Demerits of Mode:
Ø
It is not
based on all observations.
Ø Mode cannot be calculated when frequency distribution is
illdefined
Ø
It is not
capable of further algebraic treatment. Like mean, combined mode cannot be calculated.
Q.27.
What
is the relationship between mean, median and mode? Give the formula.
Ans:  In a
normal distribution Mean = Median = Mode.
In an asymmetrical distribution median is always in the middle but mean
and mode will interchange their positions or values. Mode = 3 Median  2 Mean.
Q.28. What is Dispersion? What are its various
types? Distinguish between absolute and relative measures of dispersion.
Ans:  Dispersion: Dispersion
is the measure of variation of items. It measures the extent to which the items
vary from central value. It is also known as average of the second order. It
includes range, mean deviation, quartile deviation, and standard deviation.
Measure of
dispersion may be broadly classified into two types:
A) Absolute
measures of dispersion: It is classified into
a) Range
b) Mean Deviation c) Standard
Deviation d) Quartile Deviation
B)
Relative measures of dispersion: It is classified into
a) Coefficient of Range b) Coefficient of Mean Deviation c) Coefficient
of Variation d) Coefficient of
Quartile Deviation.
Q.29.Define Standard
Deviation (S.D).Mention its merits and demerits.
Ans:  S.D:  The
standard deviation, commonly denoted by ‘σ’ (Sigma) is the most widely used
measure of dispersion. It is the square root of the second moment of dispersion
and is calculated from the arithmetic mean. In short, it may be defined as the
rootmeansquare deviation from the mean.
Merits of SD:
Ø It is based on each
and every item of the data and it is rigidly defined.
Ø It is capable of
further algebraic treatment. Combined SD of two or more groups can be
calculated.
Ø It is less affected
by fluctuations of sampling than most other measures of dispersion.
Ø SD is most
prominently used in further statistical work.
Demerits of SD:
Ø It is not easy to
calculate and to understand.
Ø It gives more weight
to extreme items and less to those which are nearer to mean.
Q.30. Difference between Schedule and Questionnaire.
Sl.No

Questionnaire

Schedule

1.

Data collection
is cheap and economical.

Data collection
is more expensive.

2.

It is not clear
that who replies.

Identity of
respondent is not known.

3.

No personal
contact is possible in case of questionnaire.

Direct personal
contact is established

4.

Wider and more representative
distribution of sample is possible.

There remains
the difficulty in sending enumerators over a relatively wider area.

5.

This is not
possible when collecting data through questionnaire.

Along with
schedule observation method can also be used.

Q.31. What are various parts of the table?
Ans: In general,
a statistical table consists of the following eight parts. They are as follows:
(i) Table Number: Each table must be given
a number.
(ii) Title of the Table: Every table should
have a suitable title.
(iii) Caption: Caption refers to the headings
of the columns.
(iv) Stub: Stub refers to the headings of
rows.
(v) Body: It contains a number of cells.
Cells are formed due to the intersection of rows and column.
(vi) Head Note: The headnote contains the
unit of measurement of data.
(vii) Foot Note: A foot note is given at the
bottom of a table.
(viii)Source Note: The source note shows the
source of the data presented in the table.
Q.32.What do you mean by
Sampling? What are its various types? Mention its features, advantages and
disadvantages.
Ans: Meaning of Sampling and Its Types
Sampling refers to the statistical process of
selecting and studying the characteristics of a relatively small number of
items from a relatively large population of such items, to draw statistically
valid inferences about the characteristics about the entire population.
Some of the most common types of random
sampling methods are
(1) simple random sampling,
(2) systematic sampling,
(3) stratified sampling, and
(4) cluster sampling.
Simple random sampling ensures that each
possible sample has an equal probability of being selected, and each item in
the entire population has an equal chance of being included in the sample.
In systematic sampling the items are selected
from the population at a uniform interval defined in terms of time, order or
space.
In stratified sample the entire population is
divided in relatively homogeneous group.
In cluster sampling the population is divided
into groups or clusters, a sample of these clusters may be drawn.
Characteristics of the sampling technique (Essentials of a Good sampling)
1. Representative: The sample
should truly represent the characteristics of the verse.
2. Adequacy: The size
of the sample should be adequate.
3. Homogeneity: There should be homogeneity in the
nature of all the units selected.
4. Independent ability.
Advantages of sampling
1. Very accurate.
2. Economical in nature.
3. Very reliable.
Disadvantages of sampling
1. Inadequacy of the samples.
2. Chances for bias.
3. Problems of accuracy.
Q.33. What are various types of Statistical errors?
Ans: Types of Statistical errors: 1] Sampling
errors 2] Nonsampling errors
Sampling Error: It is the difference between
sample value and actual value of a characteristic of a population.
Nonsampling errors: Errors that accurate the
stage of collecting data.
Practical
Problems: Consult your teacher
1. One Question from mean, median or mode
2. One Question from MD, SD or variance (Objective)
3. Index number
4. Correlation
5. Preparation of Frequency Distribution table
6. Diagram – Bar diagram
7. Graph – Ogive, histogram and frequency polygon
Q. Calculate
Mean, Median, Mode, Q1, Q3, QD, D9 and P60 from the below mentioned data:
a)
4, 4, 3, 3, 4, 5, 7, 8, 7, 8, 15, 20, 10, 3.
b)
1, 2, 3, 4, 5, 6
Q. Find
the weighted AM of 1, 2, 3, and 4 with corresponding weights 4, 3, 2, and 1
respectively.
Q. Calculate Mean, Median, Mode, Q1, Q3, QD, D9 and P60 from the
following data:
X

10

20

30

40

50

F

5

6

10

5

4

Q. Find
Mean, Median, Mode, D5, Q1, Q3, QD and P40
Class
:

15 – 25

25 – 35

35 – 45

45 – 55

55 – 65

65 – 75

Frequency
:

4

11

19

14

0

2

Q. Find Mean,
Median, Mode, D5, Q1 and P40
Marks

Below 10

10 – 20

20 – 30

30 – 40

40 – 50

50 – 60

60  70

Above 70

No.
of Students :

5

25

40

70

90

40

20

10

Q. Find
Range, SD, mean deviation about median, Q1 and Q3 of the following data: Wt (kg):
3, 4, 8, 10, And 12
Q. From
the following data, find Range, QD, MD about Mean and Median, standard
deviation and CV.
X:

10

11

12

13

14

15

16

Y:

2

7

11

15

10

4

1

Q. Find
the mean, QD, S.D., coefficient of SD and coefficient of variation:
Age

20 – 25

25 – 30

30 – 35

35 – 40

40 – 45

45 – 50

50 – 55

55 – 60

No.
of Persons

50

70

100

180

150

120

70

60

Q.
Calculate Rank correlation from the data given below:
X:

39

62

62

90

82

75

75

98

36

78

Y:

47

53

58

58

62

68

60

91

51

84

Q. Calculate Rank correlation:
Rank 1

2

3

4

5

1

9

7

8

4

Rank 2

1

3

5

2

4

6

9

7

8

Q. Calculate the correlation coefficient by Pearson’s formula of
the following data:
X

6

2

10

4

8

Y

9

11

?

8

7

Q. Find the simple aggregative index number and simple average of
price relatives (AM) for the data given below:
Commodity

A

B

C

D

E

Base Price
Current Price

40
50

22
25

31
29

10
12

75
100

Q. Find the index number by using (i) Unweighted (ii) Weighted
aggregative method (AM Method) from the following data:
Commodities

Base Price (2005)

Current Price (2010)

Weight

Rice
Dal
Fish
Potato
Oil

36
30
130
40
100

54
50
155
35
110

10
3
2
4
5

Q. From the given data calculate the following:
Commodity

1990

1993


Price

Quantity

Price

Quantity


A
B
C
D

6
2
4
10

50
100
60
3

10
2
6
12

56
120
60
24

1. Laspeyre’s Price Index and Laspeyre’s
Quantity Index
2. Paasche’s Price index and Paasche’s
Quantity index
3. Fisher’s price index and Fisher’s Quantity
index
Q. Calculate CLI (Weighted) and unweighted index number:
Expenditure

Food

Rent

Clothes

Petrol

Medicine

Others

% of Exp.
Prices in 1975
Prices in 1976

35%
50
40

10%
40
40

20%
30
40

15%
30
35

15%
10
20

5%
10
15

Q. Construct the general index number from the following data:
Group

A

B

C

D

E

Group Index
Weight

152
48

110
5

130
10

100
12

80
15
