Convenience sample
Here
the researcher chooses the sample as per his / her convenience.
It
those unit of population will be selected which are in the easy reach of
researcher.
Snow ball sampling (chain referral sampling)
In
snow ball sampling initially a small sample = chosen
It
is much smaller than what is requited
Then
selected sample unit help to further selection of more unit.
This
new unit further help to another unit selection
This
process in continues until sample greatest than required size.
Dimensional sampling
In
dimensional sampling researcher specifics, all dimensions of variables.
And then choose the sample such way that all
dimensions are represented in sample.
The
sample size of study depending upon the 1purposing of study 2size and nature of the population understudy
3 purpose of study 4time and researcher available for research.
Data collection
Next
step: collect data.

Hypothesis ne verify cheyyunna data collect
cheyyuka.
Collected by 1 originally by the
researcher. Or 2 it can be extracted from the data already available.

Data can be primary or secondary depending upon
it’s source.
Primary data
Is
that which collected by the researcher specifically as per the requirement of
the study.
Data
is collected for a fresh study.
Data
collected by a researcher through.
1Vsurvey
2 questionnaires
3
interviews
4 observation etc
Will
be considered as primary data.

Researcher can record data by observing the
sample unit.

For this the researcher can either be a part of
the group under study or simply can observe the outside.

Observation can also made in natural setting or
in a controlled environment.

Interview can be arranged over telephone /
videocall / in personal depending upon the availability of fund and time and
depth of study.

Data can also collect through survey from: from
can be filled by sending through 1 email 2 visiting respondent personally 3
online tools can be used like google from online polis or using website for
survey.

Questionaries are used to also respondent about
their choice views and opinion.
This can be ended (question with multiple choice responds)
This can be close ended (question whit descriptive answer)

Or combined

Data published already cannot be consider as
primary data.
Secondary data

It is already available and not collected
originally by the researcher for the indent study.

It can be collected from published or unpublished
source.

Published source include:
1 historical document
2 public records
3 statistics
4 reports of ministries or journal
5 book / magazine
6 newspaper / publication
Unpublished
source secondary data:
1 diary
2 letters
3 unpublished
biographies

The selection of method for data collection
depend up on the nature of study.
(like for historical studies only secondary data can be used)
Data analysis and hypothesis

The next step is to draw conclusion from the data
collected.
So as to answer the research questions and to easily the
established hypothesis.

For this the raw data collected needs to be
processed and It can be analysed manually or with the help of software of data
management such as Microsoft excel and access and statistical analyse tools
like spss / R language / stata & so on.
Commonly used data analysis tricks
Frequency:
it helps to know about the extent of preference.
Eg: (2550) idayilulla aalukalkk
ethra social media account und unn ariyanam.

This is a simple a count of people who be longa
to this age group and social media accounts.

For data with options like yes or no

Use 1 for yes or no

Then count 1^{st} so get news (who
studies)
Percentage:

It
is used to calculate proportion out of total.
Eg:
what is the proportion of people in the age group of 2550 who has social media
account.
Answer:  can be answered by dividing the number of people in the age group
having social media account with total population of this age group. The X100
%
can be also used to find growth rate and declined rate.
Mean:
 mean is used to find average number of responses.
It
can be used to find:
1 average
income
2 average
marks
3 average
age / speed view
There
are different measures like mean / median / mode.
Median:
 is used o fins idle value of available data.
Mode:
 is used to find value which repeated maximum number of time.
Eg: “such as most preferred dish at restaurant”
Standard deviation

It is measure of spread of data, around the
average.

It signifies how diverse of data is.

It is useful measure for comparing different set
of data. As comparing only one the basis of 1^{st} average will not
give complete image.
o Eg: 2 ///
company A, B income of A= 1180 / 1200 /1220 & income of 1110 / 1150 / 2340.
Now age of both company = 1200.
o But there is a
hope difference in salary.

The difference can be realised with standard
deviation.
Correlation

correlation analysis is used to study the
relation between variables.

It can show the nature of relationship it is
whether. If is positive / negative.

Positive correlation means: if there is an
increase or decrease in the other variable.

Positive correlation means increase in one decrease
In other variable.
Spurious correlation: data verifies
the relationship between variable but the relationship= not realistic.
Regression

Regression analysis is used to study the
causeandeffect relationship between dependant & independent variable.

Trend in the data can be recorded using such an
analysis to make prediction for future.

Regression analysis also tell the degree of
explained variation.

Eg: the impact of different factor like healthy /
numbers of rooms / design of the house / road network / neighbourhood on the
price of a house is known then price of hours in future can be predicted.
The
next step is to present the data is findings this can be presented in the form
of text / table / graphs /charter.

Explanation can be provided in text.

Tables are used to express data.

Tables can be constructed for time series data /
cross sectional data / and panel data.

Data can be expressed in tables in absolute from
or in percentage.

Graphs are an effective way to show trend &
variation.

Pictorial representation can be line chart /
colonography slacked bar chart / box plot / histogram / pie chart / doughnut
chart / scatter plot / population pyramid area chart / radar chart / suable
chart / surface chart / Nandigram.
Look chart on txt good who study //// 2.17
Hypothesis testing

the next step is to verify the hypothesis.

Null hypothesis is subject to verification.
There can be 2 type
conclusion possible.
1 reject null hypothesis
2 unable to reject null hypothesis

Different test like 1 ttest, Ftest, chisquare
test, etc. can be used to test hypothesis.

The value of statistic is not be calculated &
compared with calculated value of statistics.
If the complect value lies
with in the range of tabulated value. We are unable to reject null hypothesis.

The level of significance considered for
tabulated value is generally 5% to 1%
For RA Part 07 Notes  Click Here
Research Aptitude Notes Part 09 Click Here
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