This is a PowerPoint prepared to teach the students of BA Economics about methods of data collection. This will help students prepare for their presentations during their tenure of study. You can easily attain good command if you read all the basics in this presentation.

1. The Art of Gathering
Data
Exploring the benefits of both census and survey data and examining how
different sampling methods can produce more accurate results.
by Dr.Palak Jain

2. Population Census
Definition & Purpose
The entire population is counted to
provide accurate demographic and
socio-economic data. Used by
governments and large organizations
to make important decisions.
Applications
Population censuses are used for
public policy, research design,
business planning, and infrastructure
development in areas like health,
education, and transportation.
Real-World Examples
The U.S. Census Bureau conducts a population census every 10 years to determine
congressional representation for each state and allocate federal funding.

3. Population Census
Real-World Examples
The U.S. Census Bureau conducts a population census every 10 years to
determine congressional representation for each state and allocate federal
funding.
India's census is one of the world's most extensive population counts,
years. The process involves meticulous planning, execution, and analysis,
methods to gather comprehensive data about its vast population.

4. Impact on Policy Planning, Resource
Allocation, and Socioeconomic
Development:
1. Policy Formulation
2. Resource Allocation
3. Socioeconomic Development
4. Urban Planning
5. Economic Insights

5. India's Census Methodology:
1. Enumeration Process
2. Use of Technology
3. Inclusivity
4. Comprehensive Data Collection
5. Government Collaboration

6. Sampling is an essential part of research and industries when it comes to
collecting data. In this presentation, we'll explore various sampling
techniques and their real-life examples.
"Unlocking Insights:
Navigating Sampling
Techniques for Real-World
Data Collection"

7. Sample Survey
1 Definition & Purpose
A randomly selected group of individuals is surveyed to collect data that
represent the larger population. Used to determine opinions, attitudes, beliefs,
health trends, and buying habits.
2 Advantages
More cost-effective and less time-consuming than a population census.
Provides more detailed information that can inform targeted marketing and
public opinion research.
3 Limitations
Sample surveys can be biased and produce unrepresentative results. They
may not accurately capture the views of underrepresented groups in the
population.

8. Simple Random Sampling
How It Works
All members of a population
are assigned a number.
Random numbers are
generated to select a sample
from the population without
bias.
Pros and Cons
Provides an equal chance for
each member of the population
to be selected. Can be difficult
to execute correctly and may
not be feasible for large
populations.
Real-World Examples
Simple random sampling can
be used to select a small group
of people to survey in order to
estimate public opinion on a
particular issue.

9. Systematic Sampling
Definition and
Explanation
Systematic sampling
involves selecting a
starting point and then
selecting every kth
member from the
population.
Application and
Procedure
For example, in a
production line, you might
select every 10th item for
quality testing. To do this,
you would start with the
first item, select every
10th, and continue until
you reached a defined
sample size.
Advantages and
Limitations
The advantage of
systematic sampling is that
it is relatively easy to
implement and can be
more efficient than other
methods. However, it may
introduce bias if there is a
pattern in the population's
characteristics.

10. Case Study: Systematic Sampling in
Research or Industry
1 Research Study
In a study on consumer spending, systematic sampling was used
to select a sample of households from a list of all households in the
United States. This study found that there was a significant
relationship between income and spending on discretionary items.
2 Industry Application
In a production line, systematic sampling was used to monitor the
quality of products coming off the line. Through this process, the
company was able to identify and correct issues before they
became widespread, reducing waste and increasing efficiency.

11. Stratified Sampling
1 How It Works
The population is divided
into groups based on
characteristics like age,
gender, or income. A
sample is taken from
each group in proportion
to its size in the
population.
2 Pros and Cons
Provides more accurate
data for specific
subgroups within a
population. It can be
complex to set up, and
sampling error can still
occur if groups aren't
representative.
3 Real-World
Examples
Stratified sampling can
be used to survey
people in different age
groups to understand
the impact of a new
healthcare policy on
different demographics.

12. Cluster Sampling
How It Works
The population is divided into smaller, more manageable clusters based on geography or other
characteristics. A sample is taken from a few of these clusters, and all individuals within those
clusters are surveyed.
Pros and Cons
More cost-effective and less time-consuming than other sampling methods for large, dispersed
populations. It can be difficult to ensure clusters are representative of the larger population.
Real-World Examples
Cluster sampling can be used to survey people in different neighborhoods about their transportation
habits or to evaluate the impact of a new infrastructure project.

13. Multi-Stage Sampling
How It Works
Similar to cluster sampling,
but more than one sampling
technique is used to select
different groups from within
each cluster. Can be used for
complex research designs or
for geographically dispersed
populations.
Pros and Cons
Provides more accurate and
nuanced results for
complicated studies. It can be
difficult to execute and
requires more resources than
simpler sampling methods.
Real-World Examples
A social science researcher
using multi-stage sampling to
understand cultural trends
among different ethnic groups
in a large city.

14. Conclusion
The Importance of
Accurate Data
Data is essential for making
informed decisions in business,
public policy, and social justice.
Accurate data leads to better
outcomes for everyone.
The Future of Data
Collection
New technologies like machine
learning and artificial
intelligence are changing the
way we collect and analyze
data. It's important to stay
informed and adapt to new
methods.
Happy Researching!
Gathering data can be a
daunting task, but it's also an
exciting opportunity to learn
something new about the world
and make a positive impact.