Research Methodology

AIT
FTFT
For 3nd Fashion Design Students

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Research Defined per Fashion Design
• Research is integral part of any design process that begins to
investigate all the elements explored during design process
from conceptualization to the product development.
• It involves initial hunt for ideas, market and client study,
fabric and resources, production and execution, finding out
vendors prior to design till the stage it gets final feedback
from the experts and the users.

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Data Collection in Quantitative Research
Methodology

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Research problem

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Hypothesis Testing
• Population  all possible values
• Sample  a portion of the population
• Statistical inference  generalizing from a sample to
a population with calculated degree of certainty
• Two forms of statistical inference
• Hypothesis testing
• Estimation
• Parameter  a characteristic of population, e.g., population
mean µ
• Statistic  calculated from data in the sample, e.g., sample
mean (x )

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Introduction
The primary objective of statistical analysis is to use
data from a sample to make inferences about the
population from which the sample was drawn.

The mean and

µ, σ variance of
students in the
entire country?

Sample

Mean and variance

x,S of GATE scores of
all students of IIT-
KGP

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 A hypothesis should possess the following
features:

•It should explain what you expect to happen

•It should be clear
•It should be understandable
•It should be testable
•It should be measurable
•It should contain a dependent variable
•It should contain an independent variable

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 Testing of Hypothesis
Testing of Hypothesis:
In hypothesis testing, we decide whether to accept or
reject a particular value of a set, of particular values of a
parameter or those of several parameters. It is seen that,
although the exact value of a parameter may be unknown,
there is often same idea about the true value. The data
collected from samples helps us in rejecting or accepting our
hypothesis. In other words, in dealing with problems of
hypothesis testing, we try to arrive at a right decision about a
pre-stated hypothesis.

Definition:
A test of a statistical hypothesis is a two action
decision problem after the experimental sample values have
been obtained, the two–actions being the acceptance or 19
rejection of the hypothesis.
Statistical Hypothesis:

If the hypothesis is stated in terms of population parameters (such as

mean and variance), the hypothesis is called statistical hypothesis.

Example: To determine whether the wages of men and women are

equal.
A product in the market is of standard quality.
Whether a particular medicine is effective to cure a disease.

Parametric Hypothesis:

A statistical hypothesis which refers only the value of unknown

parameters of probability Distribution whose form is known is
called a parametric hypothesis.

Example: if (
X ~ N ,  2 ) then
 = 1 ,   1 ,   1 is a parametric hypothesis 20
 Null Hypothesis: H0

❖ The null hypothesis (denoted by H0) is a

statement that the value of a population
parameter (such as proportion, mean, or
standard deviation) is equal to some claimed
value.

❖ We test the null hypothesis directly.

❖ Either reject H0 or fail to reject H0.

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Example:
Ho : µ=5

The above statement is null hypothesis stating that the

population mean is equal to 5.

Another example can be taken to explain this. Suppose a

doctor has to compare the decease in blood pressure
when drugs A & B are used. Suppose A & B follow
distribution with mean µA and µB ,then

Ho : µA = µB
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Alternative Hypothesis: H1
❖ The alternative hypothesis (denoted by H1 or
Ha or HA) is the statement that the parameter
has a value that somehow differs from the
Null Hypothesis.

❖ The symbolic form of the alternative

hypothesis must use one of these symbols: ,
<, >.
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Types of Alternative Hypothesis

We have two kinds of alternative hypothesis:-

(a) One sided alternative hypothesis

(b) Two sided alternative hypothesis

The test related to (a) is called as ‘one – tailed’

test and those related to (b) are called as ‘two
tailed’ tests.
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 Ho : µ = µ0

Then

H1 : µ < µ0 or H1 : µ > µ0

One sided alternative hypothesis

H1 : µ ≠ µ0

Two sided alternative hypothesis

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Note about Forming Your
Own Claims (Hypotheses)

If you are conducting a study and want to use

a hypothesis test to support your claim, the
claim must be worded so that it becomes the
alternative hypothesis.

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Hypothesis Testing Steps
A. Null and alternative hypotheses
B. Test statistic
C. P-value and interpretation
D. Significance level (optional)

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§9.1 Null and Alternative Hypotheses
• Convert the research question to null and alternative
hypotheses
• The null hypothesis (H0) is a claim of “no difference in
the population”
• The alternative hypothesis (Ha) claims “H0 is false”
• Collect data and seek evidence against H0 as a way of
bolstering Ha (deduction)

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Illustrative Example: “Body Weight”
• The problem: In the 1970s, 20–29 year old men in the
U.S. had a mean μ body weight of 170 pounds.
Standard deviation σ was 40 pounds. We test whether
mean body weight in the population now differs.
• Null hypothesis H0: μ = 170 (“no difference”)
• The alternative hypothesis can be either Ha: μ > 170
(one-sided test) or
Ha: μ ≠ 170 (two-sided test)

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§9.2 Test Statistic
This is an example of a one-sample test of a
mean when σ is known. Use this statistic to
test the problem:
x − 0
z stat =
SE x
where  0  population mean assuming H 0 is true

and SE x =
n

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Illustrative Example: z statistic
• For the illustrative example, μ0 = 170
• We know σ = 40
• Take an SRS of n = 64. Therefore

 40
SE x = = =5
n 64
• If we found a sample mean of 173, then

x −  0 173 − 170
zstat = = = 0.60
SE x 5

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Illustrative Example: z statistic
If we found a sample mean of 185, then

x −  0 185 − 170
zstat = = = 3.00
SE x 5

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Reasoning Behinµ zstat

x ~ N (170,5)
Sampling distribution of xbar
under H0: µ = 170 for n = 64 
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Research design
• Research design: meaning of research design, different research
designs,
• basic principles of experimental design

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Development of Hypothesis
• A hypothesis could be a specific, testable prediction. It describes in
concrete terms what you expect can happen during a bound
circumstance.
• the aim of a hypothesis is to search out the solution to a matter.

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State of the art/Literature Review
• The literature review encompasses all existing literature on a given
subject, while the state-of-art refers to the latest evidence available,
in the sense of what is newest on this subject.
• Literature review has to be written by all students who engage in
research. It’s an important part of your thesis. It’s about the work
researchers in your field have done before you. State-of-the-art is
often written by senior academic members and is usually
commissioned by a journal publisher. It’s about how research in a
particular field has developed and in which direction it is going.

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Sampling

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Probability Sampling

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Data Analysis

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