The document outlines key concepts of sampling and sampling distributions relevant to a Bio-statistics course for Pharm-D students. It defines terms such as sample, statistic, population, and parameter, and distinguishes between probability and non-probability sampling methods. Additionally, it includes descriptions of different sampling techniques, such as simple random sampling and stratified random sampling.

1. Program: Pharm-D 4th
Semester: II (2019-20)
Course: Bio-Statistics
Course code: PHAR-03428
Class Teacher: DR. LIAQUAT AHMAD
email: liaquatahmad@uvas.edu.pk
Lecture # 31-33

2. Sampling and Sampling
Distributions

3. • Sample : A part of the whole selected with the
belief that it will represent the characteristics of
the whole.
• Sampling is a statistical technique which is used
to collect information on the basis of the
characteristics of a population.
• Statistic: Any numerical value calculated from
sample data is called statistic.
• Population: The whole or totality from which a
sample is selected/ drawn is called a population.
• Parameter: Any numerical value calculated from
population data is called parameter.

4. Probability and Non-Probability
Sampling

5. Sampling with and without
Replacement

6. Sampling and non-sampling Errors

8. Simple random sample
A sample is defined to be a simple random
sample (SRS) if it is selected in such a manner
that i) each unit in the population has an equal
probability of being included in the sample and
ii) each possible sample of the same size has an
equal probability of being the sample selected.

9. Stratified Random Sampling

10. Systematic Random Sample

11. Sampling Distribution of the Mean

13. Example

19. Sampling Distribution of Proportion

20. Example

21. Practice