CHANDIGARH UNIVERSITY

DEPARTMENT OF COMMERCE
Bachelor of Commerce
COMMERCE APTITUDE (CMT-658)
BY Dr. A. Shanker Prakash [E10381]

PROBABILITY VS NON PROBABILITY DISCOVER . LEARN . EMPOWER

COMMERCE
APTITUDE
Course Objectives & Outcome Will be covered in this
CO Number Title Level lecture

CO1 What is probability sampling? Remember

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 PROBABILITY
SAMPLING
This means that everyone in
the population has a chance
of being sampled, and you
can determine what the
probability of people being
sampled is.

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 PROBABILITY SAMPLING
• This means that everyone in the population has a chance of being
sampled, and you can determine what the probability of people being
sampled is.
• Probability sampling includes Simple Random Sampling, 
Systematic Sampling, Stratified Sampling, Probability Proportional to
Size Sampling, and Cluster or Multistage Sampling. And have these
elements in common
• Everyone has a known (calculated) chance of being sampled
•  There is random selection 4
 NON PROBABILITY SAMPLING
This means that you have excluded some of the population in your
sample, and that exact number can not be calculated – meaning there are
limits on how much you can determine about the population from the
sample. Nonprobability sampling methods include convenience
sampling, quota sampling, and purposive sampling – or judgment
sampling, and snowball sampling.

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 Probability Sampling Methods- Simple
Random Sampling

Random sampling, in its simplest and purest form, means that each

member of the population has an equal (and known) chance at being

selected. In a large population, this becomes prohibitive for cost and

technical reasons, so the actual pool of respondents becomes biased.

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Probability Sampling Methods- Systematic
Sampling

This method is often preferable to simple random sampling, as you

select members of the population systematically – that is, every Nth

record. As long as there is no ordering of the list, the sampling method

is just as good as random – only much simpler to manage.

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 Probability Sampling Methods- Stratified
Sampling

This is a more commonly used technique, and the population is divided

into subsets with a common trait, or “strata”, and then random

sampling is performed to reduce sampling bias. The key is to ensure

that the sample size is large enough to represent the population.

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 Non Probability Sampling Methods-
Convenience Sampling
One of the most cost-effective sampling methods, researchers choose
this method as they can recruit the sample from the population that is
close at hand, or convenient to them. It is up to the researcher to ensure
that a large enough sample is chosen that can closely represent the
population being studied. An extension of this is judgment sampling,
where the research selects a representative sample based on their
judgment.

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Non Probability Sampling Methods- Quota
Sampling
Very similar to stratified sampling, where the researcher defines the
segments or “stratums” and their representative proportion in the
population – quota sampling differs in that respondents are typically
filled by convenience or judgment sampling, vs random.

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 Non Probability Sampling Methods-
SNOWBALL SAMPLING
Snowball Sampling- There is another method of acquiring respondents
called snowball sampling, where initial subjects refer others to take the
survey

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 SUMMARY
Data collection is the process of gathering and measuring information
 on targeted variables in an established system, which then enables one
to answer relevant questions and evaluate outcomes. Data collection is
a research component in all study fields, including physical and 
social sciences, humanities, and business. While methods vary by
discipline, the emphasis on ensuring accurate and honest collection
remains the same. The goal for all data collection is to capture quality
evidence that allows analysis to lead to the formulation of convincing
and credible answers to the questions that have been posed.

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Assessment Pattern

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 APPLICATIONS
After going through this presentation, 
• Students will get an insight into meaning of probability sampling.
• They will also come to comprehend the nature of nonprobability
sampling.
• Students will be mindful of types of probability sampling.
• Students can understand the types of nonprobability sampling.

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 REFERENCES
WEBSITES
• https://ori.hhs.gov/education/products/n_illinois_u/datamanagement/dctopic.html
• https://www.jotform.com/data-collection-methods/
• https://www.formpl.us/blog/data-collection-method.
• https://www.questionpro.com/blog/data-collection/
• https://en.wikipedia.org/wiki/Data_collection
BOOKS
• UGC NET TRUE MAN
• UGC NET ARIHANT
VIDEO LINKS
https://www.youtube.com/watch?v=XEdXKrljNRU
https://www.youtube.com/watch?v=csh2g8Cx1Hs

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THANK YOU

For queries
Email: shanker.e10381@cumail.in