Sampling Techniques
MAUREEN L. M.
INTERMEDIATE MICROECONOMICS
SAMPLING TECHNIQUES
INTRODUCTION
A sample is a unit or subset of selection from a larger population that is used in studying to draw conclusions regarding the whole population. A sample is usually selected from the population because it is not easy to study the entire population at once and the cost of doing so may be very high. The sample should be the best representation of the whole population to enable accurate outcomes and accurate decisions made from the findings. Before sampling, the population should be clearly defined to ensure that the correct sample is selected for accuracy.
Sampling, therefore, is the process used in statistics in which a predetermined number of observations will be taken from a large population. It is the selection of units from a population of interest so that by studying it, we may generalize the findings back to the population from which the sample was obtained. The methodology to be used in sampling will depend on the type of analysis being performed. The methods include the following:-
1. SIMPLE RANDOM SAMPLING
Simple Random Sampling is obtained in such a way that each element of the population is given equal probability of being selected as a subject. The process is done in a single step with each subject selected independently of the rest of the members of the population. There are many methods of proceeding with simple random sampling techniques. For example, each member can be given a unique number, then all the numbers are placed in a container and mixed thoroughly. A blind folded researcher will then pick some tags from the container and the members whose number tags were picked become the population sample.
Advantages 1. The whole population is highly represented if all members of the population are present 2. It is free from sampling bias; its fair because every member of the population is given equal probability of being selected. 3.
INTERMEDIATE MICROECONOMICS
SAMPLING TECHNIQUES
INTRODUCTION
A sample is a unit or subset of selection from a larger population that is used in studying to draw conclusions regarding the whole population. A sample is usually selected from the population because it is not easy to study the entire population at once and the cost of doing so may be very high. The sample should be the best representation of the whole population to enable accurate outcomes and accurate decisions made from the findings. Before sampling, the population should be clearly defined to ensure that the correct sample is selected for accuracy.
Sampling, therefore, is the process used in statistics in which a predetermined number of observations will be taken from a large population. It is the selection of units from a population of interest so that by studying it, we may generalize the findings back to the population from which the sample was obtained. The methodology to be used in sampling will depend on the type of analysis being performed. The methods include the following:-
1. SIMPLE RANDOM SAMPLING
Simple Random Sampling is obtained in such a way that each element of the population is given equal probability of being selected as a subject. The process is done in a single step with each subject selected independently of the rest of the members of the population. There are many methods of proceeding with simple random sampling techniques. For example, each member can be given a unique number, then all the numbers are placed in a container and mixed thoroughly. A blind folded researcher will then pick some tags from the container and the members whose number tags were picked become the population sample.
Advantages 1. The whole population is highly represented if all members of the population are present 2. It is free from sampling bias; its fair because every member of the population is given equal probability of being selected. 3.