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7/27/2019 SectionB Group2 Apparel Analysis Final
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Apparel Industry
by
Aman Anshu(13PGP061)
Minu Pandey(13PGP091)
Puneet Manot(13PGP102)
Bhavana
Ziradkar(13PGP118)
Indian Institute of Management Raipur Page 1
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Introduction
The apparel and textile industry occupies a unique and important
place in India. One of the earliest industries to come into existence in the
country, the sector accounts for 14% of the total Industrial production,
conduces to about 30% of the total exports and is the second largestemployment creator after agriculture.
The Indian textiles industry that already has an overwhelming
presence in the economic life of the country has been given a further
boost with the scrapping of quotas in global trade of textiles and clothing.
In the post quota period, the size of industry has expanded from US$ 37
billion in 2004-05 to US$ 49 billion in 2006-07. During this period, while
the domestic market has grown from US$ 23 billion to US$ 30 billion,
exports have increased from around US$ 14 billion to US$ 19 billion.As a matter of fact, the apparel and textile is the largest foreign
exchange earning sector in the country. Being the 2nd highest employer of
raw labour it gives a direct employment provider to over 35 million people
and with continuing growth momentum, the role of this sector in Indian
economy is bound to increase.
Objective
1. Collection of sample data of readymade garments producing
companies.
2. Descriptive analysis of the data
3. Preparation of contingency tables for producers as per their Net
Profit Margin and consumers according to segment classification.
4. Using stratified random sampling technique to obtain a sample from
which inferences can be made.
Brief Summary of Data used
The sources of our data are:
www.Crisilresearch.com
www.wazir.in (Annexure)
We obtained the Net profit margin of 11 companies (for 5 years each),
dealing with the manufacture of readymade garments from CrisilResearch. The companies are:
Indian Institute of Management Raipur Page 2
http://www.crisilresearch.com/http://www.wazir.in/http://www.crisilresearch.com/http://www.wazir.in/7/27/2019 SectionB Group2 Apparel Analysis Final
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S.N. Name of Company
1 Arvind Ltd.
2 Bhandari Hosiery Exports Ltd.
3 Celebrity Fashions Ltd.
4 Gokaldas Exports Ltd.
5 Kewal Kiran Clothing Ltd.
6 Page Industries Ltd.
7 Provogue(India) Ltd.
8 Raymond Ltd.
9 Samtex Fashions Ltd.
10 Virat Industries Ltd.
11 Zodiac Clothing Ltd.
We obtained the contingency table for the consumption of garments
according to the following three categories Mens Wear, Womens Wear
and Kids Wear - based on two types of products Branded and Un-branded
from a report published by Wazir Advisors a statistics for the year 2011.
Descriptive Summary Population
The population size N = 5*11=55
Population data.xlsx
Attachment 2: Population data
Descriptives
Statistic Std. ErrorMean 3.9271 1.04266
95% Confidence Interval forMean
LowerBound
1.8367
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UpperBound
6.0175
Std. Deviation 7.73256
Skewness -.467 .322
(Skewness)/(Std. Error of Skewness) = -1.45109 (which is greater than -2 and
less than 2).
Hence we can apply Empirical Rule to obtain ranges of data and density of
data.
Range of Data Empirical Rule
Density
Density (calculated from
Population)Min Maximum
-3.81 11.66 90% 67%
-11.54 19.40 95% 95%-19.27 27.12 99% 98%
Inference: 95% chances that a selected period has a net profit margin in
between -11.84 and 19.40
The histogram plot for the population data:
Using Tests of Normality Kolmogorov-Smirnov Test
Net Profit Margin
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig..101 55 .200* .980 55 .472Ho: The Population is Normal (p> )
H1: The Population is not normal (p< )
Here, significant value p= 0.2 Level of significance = 0.05 (95%
confidence level) As p > : Null Hypothesis (Ho) that population
is normally distributed is accepted.
Probability Contingency Table for Net Profit
MarginThe mean of the population of yearly Net Profit Margins is 3.9271%
Using this we create a contingency table for mutually exclusive and collectively
exhaustive criteria
a) NPM>5 b) NPM
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Count Contingency Table
NPM>Mean
NPMMean
NPMMean
MarginalProbabilit JointProbabil Conditional RevisedProbability
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y ityProbability
Arvind Ltd. 0.09091 0.05455 0.00496 0.10714Bhandari HosieryExports Ltd. 0.09091 0.00000 0.00000 0.00000
Celebrity Fashions Ltd. 0.09091 0.00000 0.00000 0.00000Gokaldas Exports Ltd. 0.09091 0.01818 0.00165 0.03571Kewal Kiran ClothingLtd. 0.09091 0.09091 0.00826 0.17857Page Industries Ltd. 0.09091 0.09091 0.00826 0.17857Provogue(India) Ltd. 0.09091 0.09091 0.00826 0.17857Raymond Ltd. 0.09091 0.00000 0.00000 0.00000Samtex Fashions Ltd. 0.09091 0.00000 0.00000 0.00000Virat Industries Ltd. 0.09091 0.09091 0.00826 0.17857Zodiac Clothing Ltd. 0.09091 0.07273 0.00661 0.14286
Total 0.04628 1.00000
NPM
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Virat Industries Ltd. 0.09091 0.00000 0.00000 0.00000Zodiac Clothing Ltd. 0.09091 0.01818 0.00165 0.03704
Total 0.04463 1.00000
The Contingency calculation can be found in the attached excel sheet:
contingency tablewith pie.xlsx
Sampling Technique
Population consisted of all the companies of the textile and apparel
industry.
The parameter taken into consideration was the net profit of all these
companies.
We could identify data of each company as strata. Random samples
were taken from each stratum.
Stratified Random Sampling has been used for normalization of the
data with net profit of the samples as statistics.
Stratified randomsample.xlsx
Attachment 1: Stratified random sample
Descriptive Summary Sample
The sample size selected is n =3*11=33
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DescriptiveSample NPM
Statistic Std. Error
Mean 4.3021 1.39947
95% Confidence Interval for
Mean
Lower Bound 1.4515
Upper Bound 7.1527
Std. Deviation 8.03932
Skewness -.648 .409
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
SampleNPM .106 33 .200* .970 33 .489
Here, significant value p= 0.2
Level of significance Alpha (a) = 0.05 (95% confidence level)As p > Alpha (a) - Null Hypothesis (Ho) that population is normally
distributed is accepted.
Hence t-sample test and Z tests can be carried out for the sample. From the data it can be assumed that:
o Case 1 H0: the net profit margin (population mean
()) 5
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H1: the net profit margin (population mean
()) < 5
o Case 2 H0: the net profit margin (population mean ())
3.92
H1: the net profit margin (population mean ()) ,
Hence we may accept Ho
Asthe probability does not lie within the rejection ratio, Ho is accepted.
Hence, with 95% confidence, we can say the net profit margin will be greater
than 5%
Case 2:
Tabulated value of z is 1.6449
Zstat= (x - )/ (^/ n)x=4.3021= 3.9271
^ =s= 8.03932
n= 33
Zstat= (4.3021 3.9271)/(8.03932/ 33)= (0.375)/ (8.03932/5.744)
= (0.375)/ (1.399)=.26804Also from the one sample t-test
One-Sample Test
Test Value = 3.9271
t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the
Difference
Lower Upper
SampleNPM .268 32 .790 .37502 -2.4756 3.2256
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We observe that p value is greater than the value of,
Therefore, |cal z| ,
Hence we may accept Ho
Asthe probability does not lie within the rejection ratio, Ho is accepted.
Hence, with 95% confidence, we can say the net profit margin will be greater
than 3.92%.
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Regression Analysis
We have done the regression for 10 brands. However the Regression analysis for
Provogue Industry has only been shown below. Same procedure has been
followed for the rest of the 9 brands.
REGRESSION CALCULATION FOR PROVOGUE INDUSTRIES
MODEL:
Assumptions:
a.) Linearity: We assume that the factors are linear.
b.) Independence of errors: Durbin Value=2.47 which is slightly more than 2.
Therefore the errors are slightly negatively co-related. However, It is
accepted.c.) Normality of errors: The PP graph shows that the errors are normal.
d.) Equal variance: Homoscedasticity found. Therefore accepted.
Since the equation follows all the assumptions, therefore, we go forward with the
calculations.
The calculations are done at 95% confidence level, Therefore =0.05
Calculations:
We assume the equation as: PRO NPM = 0 + (1 Pro_Emp) + (2Pro_Sell)+ errors
From the model Summary, we see that adjusted R2=.942, which indicated
that these two factors add to 94% of the value of the Pro NPM.
From the Annova table, we test the validity of the model.
H0: All Bi=0, ie: model is invalid
H1: At least 1 Bi is not equal to 0, Model is valid.
Here from the Annova table, we see the significance (p) = 0.058> =0.05
Therefore, H0 accepted and so the model is Invalid.
Significance of Independent Variables:
o H0: B1=0, Pro_Emp is not a significant value
H1: B1not equal to 0, Pro_Emp is a significant value
(p) = 0.207> , Therefore H0 accepted, hence ProEmp is not a
significant factor.
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o H0: B2=0, Pro_Sell is not a significant value
H1: B1 not equal to 0, Pro_Sell is a significant value
(p) = 0.465> , Therefore H0 accepted, hence ProSell is not a
significant factor
However, we proceed with the further calculations to show the mandated
process.
Collinearity Statistics:
We see the VIF value >10 or 20
Therefore, It is a matter of concern and hence collinear.
Getting the Value of the Coefficients from the Co-efficients table, we get
the final equation as: PRO NPM = 18.250 + (-0.592* Pro_Emp) + (0.238*Pro_Sell)
This equation tells that:
a) If there is a 1 unit change in Pro Emp and all the other factors
remaining constant, average estimated Pro NPM reduces by -0.592.
b) If there is a change of 1 unit in Pro Sell and all the other factors
remaining constant, average estimated Pro NPM increases by 0.238.
c) Also, If Pro Sell and Pro Emp are 0, still, Pro NPM is 18.25, and
therefore there are other factors also that add to the profit/loss.
The Regression data for rest of the brands is consolidated in the excel sheet
attached below.
Regression forApparel Industry.xlsx
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Annexure:
Probability Contingency Table for Garment
Categories
The data available segregates the consumption of Branded and
Unbranded garments in different exhaustive categories of Mens Wear,Womens Wear and Kids Wear. The probabilities evaluated from the data
are of the form (marginal):
o Money Spent on Branded garments
o Money spent on Un-branded garments
o Money spent on Mens garments
o
Money spent on Womens garments
o Money spent on Kids garments
The Contingency table so formed is:
Event Set (in Billion US
Dollars) Contingency Table
Catego
ry
Brand
ed
Un-
Branded
Tot
al
Catego
ry
Brand
ed
Un-
Branded
Tot
alMen 5 11 16 Men 0.125 0.275 0.4
Women 4 10 14 Women 0.1 0.250.35
Kidswear 1 9 10
Kidswear 0.025 0.225
0.25
Total 10 30 40 Total 0.25 0.75 1
The conditional probabilities for different pre-conditions are presented below:
Branded Category MarginalProbabilit Joint conditional RevisedProbability
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yMen 0.4 0.125 0.05 0.547945205
Women 0.35 0.1 0.035 0.383561644Kidswe
ar 0.25 0.025 0.00625 0.068493151
Total 0.09125
UnBranded
Category
MarginalProbability Joint conditional
RevisedProbability
Men 0.4 0.275 0.11 0.433497537Women 0.35 0.25 0.0875 0.344827586Kidswe
ar 0.25 0.225 0.05625 0.221674877Total 0.25375
MensWear
Marginal Joint
Conditional Revised Probability
Branded 0.25 0.125 0.03125 0.131578947Un-
Branded 0.75 0.275 0.20625 0.8684210530.2375
Womens Wear
Marginal Joint Conditional Revised Probability
Branded 0.25 0.1 0.025 0.117647059Un-
Branded 0.75 0.25 0.1875 0.882352941
0.2125
KidsWear
Marginal Joint Conditional Revised Probability
Branded 0.25 0.025 0.00625 0.035714286Un-
Branded 0.75 0.225 0.16875 0.9642857140.175
Indian Institute of Management Raipur Page 15