Statistics for Economics
Chapter 3
Chapter 3
Organisation of
Data
1 . The class midpoint is
equal to:
(a)
The average of the upper class limit and the lower class limit.
(b)
The product of upper class limit and the lower class limit.
(c)
The ratio of the upper class limit and the lower class limit.
(d)
None of the above.
Answer : The option (a) is correct.
The class midpoint is equal to the average of the
upper class limit and the lower class limit. It is known by adding the values
of upper and lower limits and dividing the total by 2.
2. The frequency
distribution of two variables is known as
(a)
Univariate Distribution
(b)
Bivariate Distribution
(c)
Multivariate Distribution
(d)
None of the above
Answer : The option (b) is correct.
The frequency distribution of two variables is known
as Bivariate Frequency Distribution. In other words, Bivariate Frequency
Distribution shows the series of statistical data having frequencies of two
variables such as the data on income and expenditure of the households.
3. Statistical
calculations in classified data are based on
(a)
the actual values of observations
(b)
the upper class limits
(c)
the lower class limits
(d)
the class midpoints
Answer :
The option (d) is
correct.
The calculations in classified data or continuous
series are based on the class midpoints. The items in a continuous series
cannot be exactly measured. Consequently, the class midpoints are calculated.
4. under Exclusive method,
(a)
the upper class limit of a class is excluded in the class
interval
(b)
the upper class limit of a class is included in the class
interval
(c)
the lower class limit of a class is excluded in the class interval
(d)
the lower class limit of a class is included in the class
interval
Answer :The option (a) is
correct.
A series in which upper limit of one class becomes
the lower limit of the succeeding class interval is called exclusive series. In
such series, the frequencies of the lower limit are included in that particular
class whereas the frequencies of the upper limit are excluded.
5. Range is the
(a)
difference between the largest and the smallest observations
(b)
difference between the smallest and the largest observations
(c)
average of the largest and the smallest observations
(d)
ratio of the largest to the smallest observation
Answer : The option (a) is correct.
Range is defined as the
difference between the largest and the smallest observations.
Algebraically,
R = H - L
Where,
R denotes range
H is the highest value
L is the lowest value
6. Can there be any
advantage in classifying things? Explain with an example from your daily life.
Answer : Yes, there are many advantages of classifying things. The
following are the advantages associated with classification:
1.
Saves Time and Energy- Classification of things not only saves our time but
also our energy which would otherwise be utilised in searching from entire lot of things.
3.
Easy Classification- Classification
facilitates comparisons and helps in drawing fast conclusions or inferences.
Ex: In a post office letters are classified first
according to the states, then according to the cities and streets. This process
of classification helps the postman to deliver posts quickly, efficiently.
7. What is a variable? Distinguish between a
discrete and a continuous variable.
Answer : A variable refers to that
quantity which keeps on changing and which can be measured by some unit. For
example, if we measure the height of students of a class, then height is
regarded as a variable. A variable can be either discrete or continuous.
1. A variable that takes only whole number as
its value is called discrete variable.
Ex. Number of students in a class.
A variable that can take any value within a reasonable limit is
called continuous variable. Ex: age,
height etc.
2. Discrete variables
change from one value to another while continuous variable assume a range of
values or increase in fractions.
8. Explain the 'exclusive'
and 'inclusive' methods used in classification of data.
Answer : Exclusive Method- This method is used for those series in which the upper limit of
one class becomes the lower limit of the next class. It is called exclusive series because the frequencies of
the upper limit of a class interval are not included in that particular class.
In such type of series, the upper limit of one class becomes the lower limit of
the next class, for example, 0-10, 10-20, 20-30 and so on. If two students have scored 10 then it wont be included under 0-10 but would be included under 10-20. This method is
most appropriate for data of continuous variables.
Inclusive Method- Under this method of classification of data, the classes are
formed in such a manner that the upper limit of a class interval does not repeat itself as the lower limit of the
next class interval. In such a series, both the upper limit and the lower limit
are included in the particular class interval, for example, 1-5, 6-10, 11-15
and so on. The interval 1-5 includes both the limits i.e. 1 and 5.
9. Use the data in Table 3.2 that relate to
monthly household expenditure (in Rs) on food of 50 households and obtain the
range of monthly household expenditure on food.
Range = Highest Value - Lowest Value
Highest Value = 5090
Lowest Value = 1007
So, Range = 5090 - 1007 = 4083
10. What is 'loss of
information' in classified data?
Answer. The classification or
grouping of raw data into classes makes it more concise and understandable. But
simultaneously there is loss of information.
The calculations involved in the classified data or the
continuous series are based on the class midpoints and individual observation
loses its importance during the statistical calculations.
Further, the statistical calculations are based on the values of
the class marks, ignoring the exact observations of the data leading to the
problem of loss of information.
11. Do you agree that classified data is better
than raw data?
Answer :
The classified data has following advantages over the raw data.
1.
Comprehensive-Raw data are large and
entangled, whereas classified data are comprehensive and easily manageable.
2.
Quick Information- It is troublesome to pick up information from
unclassified data. Information can be easily collected from the classified data.
3.
Conclusions - Classification
facilitates comparisons and helps in drawing fast conclusions or inferences.
4.
Saves Time and Energy- Classified data not only save our time but also our
energy, which would otherwise be utilised in searching from entire lot of things.
12. Distinguish between Univariate and Bivariate frequency
distribution.
Answer : The word “uni”
means one . A series of statistical data
showing the frequency of only one variable is called Univariate Frequency
distribution. Ex: income of people,
marks scored by students etc.
The word” Bi” means two.
A series of statistical data showing the frequency of two variables
simultaneously is called Bivariate frequency distribution. Ex: Sales and advertisement expenditure,
Height and weight of individuals etc.
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