7. Probability and Non-probability samples 8. Simple Random Sampling 9. Systemat

Question

7. Probability and Non-probability samples 8. Simple Random Sampling 9. Systematic Sampling 10. Cluster Sampling, Stratified Sampling 11. Sources of data Primary and Secondary - give examples 12. Qualitative data - Nominal and Ordinal 13. Quantitative data - Discrete and Continuous, ratio and interval 14. How to calculate the mean, median, mode, variance, sample standard deviation coefficient of variation (CV), first quartile, second quartile (same as the median), third quartile, interquartile range (IR). 15. Five Number Summary, Box Plot, Shape of data (right skewness, left skewness, and 16. Contingency Tables -know how to set up the table, calculate the row and column 17. Using frequency distribution table to calculate percentage distribution, cumulative symmetric. percentages, like the examples given in the class. percentage distribution and using it to answer cumulative percentage questions. Know how to draw a cumulative percentage polygon (Ogive) and using it for interpolation.

Explanation / Answer

Probability sampling is the sampling in which each unit in the population has some probability of selection. Random sampling is an example of Probability sampling.

Non Probability sampling is the sampling in which each unit is have not had a probability of selection.

Convenience sampling is an example of it.

Simple Random Sampling: each unit in the population have the equal probability of selection . for random sampling you have to create frame before sampling.

Systematic Sampling: Systematic random sampling is the random sampling method that requires selecting samples based on a system of intervals in a numbered population.  

Cluster Sampling is a method where the target population is divided into multiple clusters. Some of these clusters are selected randomly for sampling or a second stage or multiple stage sampling is carried out to form the target sample.

Stratified Sampling is a probability sampling method, also called random quota sampling, where a large population is divided into unique, homogeneous strata and further, members from these strata are randomly selected to form a sample.

Primary data: Primary data is obtained from a direct effort from the survey.

Secondary data: Secondary data was collected by someone other than the user. primary data is used for secondary data when the user is different from the data collector.

thanks :)

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