Quantitative Analysis

QUANTITATIVE
ANALYSIS
STUDENT ID:
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QUANTITATIVE ANALYSIS
Introduction
The given data pertains to the data of 400 people who have been randomly selected from the
US state of California in the year 2012. The data provides information with regards to wages
that the people draw along with their occupation and gender. The objective of this report is to
present an analysis of the sample data of 50 observations that has been retrieved from the
sample of 400 observations provided using appropriate statistical tools and techniques.
Analysis
The requisite statistical analysis of the sample data is carried and relevant output along with
discussion is provided in this section.
TASK 1
The sample data of 50 observations has been obtained as per the procedure which is outlined
based on the student ID.
(a) Column chart and pie chart for variable SEX (0 = MALE), (1=FEMALE) is shown
below.
0 (Male) 1 (Female)
23
23.5
24
24.5
25
25.5
26
26.5
Column Chart: SEX
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QUANTITATIVE ANALYSIS
0 (Male)
48%1 (Female)
52%
Pie Chart: SEX
0 (Male)
1 (Female)
Based on the above graphs, it is evident that in the selected sample, females have a slight
edge over the males considering that more than 26 samples comprise of females while the
remaining 24 are males.
TASK 2
(a) Probability distribution for variable ‘Occupation category” is shown below.
It is evident from the above probability distribution table that 44% of the people included in
the sample tend to be occupied in “Other” category. Amongst the five defined categories of
occupation, the highest relative frequency is observed for clerical occupation category which
accounts for 22% of the sample. The lowest representation is for the sales category
employees which have only 4% representation in the selected sample of 50 observations
using the personal identification number.
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QUANTITATIVE ANALYSIS
Descriptive statistics for variable ‘Occupation category”
(b) Probability distribution for variable ‘Occupation category” can be derived based on the
following relative frequency distribution.
Occupational Category Frequency Relative Frequency
1 (Management) 7 =7/50= 0.14
2 (Sales) 2 =2/50=0.04
3 (Clerical) 11 =11/50=0.22
4 (Service) 8 =8/50=0.16
5(Professional) 0 0
6 (Other) 22 =22/50=0.44
Total 50 1
Hence, Probability distribution
X 1 2 3 4 5 6
P(X) 0.14 0.04 0.22 0.16 0 0.44
(c) Bar chart for probability distribution of occupation category has been drawn using Excel
and pasted below.
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