BIOSTATISTICS | ZOOL-600-601 LECTURE 3
Instructor: Dr. Waheed Ali Panhwar | University of Sindh BS Zoology — Final Year
Population, Sample & Variables
1. Population
Official Definition:
In statistics, a population is the complete group of all individuals, objects, or measurements
that a researcher wants to study. It includes every single member of the group the research
question is concerned with — not just most of them, but all of them.
A statistical population does not have to be people. It can be animals, plants, blood samples,
temperature readings, or any group of things being studied. The population is entirely defined by the
research question — it changes as soon as the question changes.
Example: If your question is 'what is the average wing length of honeybees in Hyderabad district?' —
your population is every single honeybee in Hyderabad district. Not some. All of them.
Types of Population
Finite Population: Has a countable, definite number of members. Large but theoretically countable.
Examples: all students currently enrolled at University of Sindh; all crocodiles in Manchar Lake.
Infinite Population: So numerous or continuously changing that counting all members is practically
impossible. Very large finite populations are treated as infinite for research purposes. Examples: all
mosquitoes in Pakistan; all bacteria in a soil sample; all honeybees in a province.
Key Point: The population is defined by your research question, not by geography alone.
If your study is about migratory birds in Sindh during winter, your population is only those
birds during that season — not all birds in Pakistan, not Sindhi birds in summer. Define it
precisely at the start of every study.
Examples in Zoology
• All fish living in Keenjhar Lake (finite, but treated as infinite due to size)
• All migratory birds visiting Sindh during winter season
• All patients with a specific disease admitted to a hospital this year
• All honeybee colonies in a particular district
2. Sample
Official Definition:
A sample is a smaller, carefully selected subset of the population that is used to represent
the whole. The purpose of a sample is to allow a researcher to study a manageable group
and then draw conclusions that apply to the entire population.
The most important property a sample must have is representativeness — the sample must accurately
reflect the key characteristics of the entire population it comes from. A sample that does not represent
the population will produce biased, unreliable conclusions.
Key Point: Think of it like tasting soup. The chef does not drink the entire pot to check for
salt. One spoonful (the sample) represents the whole pot (the population). But if the chef
only tastes the top layer where cream has risen, the spoonful does not represent what is
below. The sample must reflect the whole.
Why Use Samples Instead of Studying the Full Population?
• Studying every individual is often practically impossible (billions of bees, millions of insects)
• It saves time — a sample can be studied in weeks while a full population study could take years
• It saves cost — fewer individuals to capture, measure, and process
Instructor: Dr. Waheed Ali Panhwar | University of Sindh BS Zoology — Final Year
Population, Sample & Variables
1. Population
Official Definition:
In statistics, a population is the complete group of all individuals, objects, or measurements
that a researcher wants to study. It includes every single member of the group the research
question is concerned with — not just most of them, but all of them.
A statistical population does not have to be people. It can be animals, plants, blood samples,
temperature readings, or any group of things being studied. The population is entirely defined by the
research question — it changes as soon as the question changes.
Example: If your question is 'what is the average wing length of honeybees in Hyderabad district?' —
your population is every single honeybee in Hyderabad district. Not some. All of them.
Types of Population
Finite Population: Has a countable, definite number of members. Large but theoretically countable.
Examples: all students currently enrolled at University of Sindh; all crocodiles in Manchar Lake.
Infinite Population: So numerous or continuously changing that counting all members is practically
impossible. Very large finite populations are treated as infinite for research purposes. Examples: all
mosquitoes in Pakistan; all bacteria in a soil sample; all honeybees in a province.
Key Point: The population is defined by your research question, not by geography alone.
If your study is about migratory birds in Sindh during winter, your population is only those
birds during that season — not all birds in Pakistan, not Sindhi birds in summer. Define it
precisely at the start of every study.
Examples in Zoology
• All fish living in Keenjhar Lake (finite, but treated as infinite due to size)
• All migratory birds visiting Sindh during winter season
• All patients with a specific disease admitted to a hospital this year
• All honeybee colonies in a particular district
2. Sample
Official Definition:
A sample is a smaller, carefully selected subset of the population that is used to represent
the whole. The purpose of a sample is to allow a researcher to study a manageable group
and then draw conclusions that apply to the entire population.
The most important property a sample must have is representativeness — the sample must accurately
reflect the key characteristics of the entire population it comes from. A sample that does not represent
the population will produce biased, unreliable conclusions.
Key Point: Think of it like tasting soup. The chef does not drink the entire pot to check for
salt. One spoonful (the sample) represents the whole pot (the population). But if the chef
only tastes the top layer where cream has risen, the spoonful does not represent what is
below. The sample must reflect the whole.
Why Use Samples Instead of Studying the Full Population?
• Studying every individual is often practically impossible (billions of bees, millions of insects)
• It saves time — a sample can be studied in weeks while a full population study could take years
• It saves cost — fewer individuals to capture, measure, and process
