Sampling
This document was uploaded by user and they confirmed that they have the permission to share it. If you are author or own the copyright of this book, please report to us by using this DMCA report form. Report DMCA
Overview
Download & View Sampling as PDF for free.
More details
- Words: 493
- Pages: 12
Sampling Techniques & Data Gathering Methods
J.O.Gonzales
Sampling
Sampling - process of selecting members or elements of a sample from a given population.
Requires
Time Effort Money Careful planning
Slovin’s Formula
There are scientific ways of determining a representative (acceptable) sample size from any given population. One of them is Slovin’s formula:
where
N n= (1 + Ne 2 )
n = sample size N = population size e = margin of error (usually 0.05, since the preferred confidence level in sampling is 95%)
Sampling Techniques 1. Probability Sampling – samples are chosen in such a way that each element of the population has a known and usually equal chance of being included in the sample. 2. Non-probability Sampling – samples are chosen in such a way that some members of the population may not have any chance of being included in the sample.
1. Probability Sampling 1.1 Simple Random Sampling – sampling is done by drawing lots or through the use of random numbers. 1.2 Systematic Random Sampling – sampling is done by selecting every kth element in the population with the starting point determined at random. (usually by making k = N/n ) NOTE: This sampling technique should not be used if there is an underlying periodicity in the sampling interval.
1. Probability Sampling 1.3 Stratified Random Sampling – sampling is done by first dividing the population into a number of nonoverlapping sub-populations or strata and then taking samples from each stratum.
There are two procedures that can be used to determine the sample size per stratum.
Stratified Random Sampling 1.3.1Equal
Allocation – divide the intended sample size (n) by the number of strata (k) in order to obtain the number of samples from each stratum ( n1 , n2 , nk). Formula:
n ni = k
Stratified Random Sampling 1.3.2
Proportional Allocation – divide the size of each stratum ( N1 , N 2 , N k ) by the population size (N) & multiply the result by the intended sample size (n). Formula:
Ni ni = ×n N
1. Probability Sampling 1.4 Cluster Sampling 1. divide the population into (geographical) groups called clusters, 2. select a random sample of clusters, and 3. select a random sample of elements from each of the selected clusters.
2. Non-Probability Sampling 2.1Convenience Sampling – selecting those elements that are readily available (doing a survey by phone) or those that happen to be in a place at a certain time (conducting a taste test) in order to obtain quick results. 2.2Quota Sampling – samples are chosen based on the judgment or prior knowledge of the researcher with the objective of reaching a certain target quota (polls conducted via radio or television).
Data Gathering Methods Direct Methods Observation Interview Focus Groups
2. Indirect Method Questionnaire Journals Review of Records
Sampling Techniques & Data Gathering Methods
-end-
J.O.Gonzales
Sampling
Sampling - process of selecting members or elements of a sample from a given population.
Requires
Time Effort Money Careful planning
Slovin’s Formula
There are scientific ways of determining a representative (acceptable) sample size from any given population. One of them is Slovin’s formula:
where
N n= (1 + Ne 2 )
n = sample size N = population size e = margin of error (usually 0.05, since the preferred confidence level in sampling is 95%)
Sampling Techniques 1. Probability Sampling – samples are chosen in such a way that each element of the population has a known and usually equal chance of being included in the sample. 2. Non-probability Sampling – samples are chosen in such a way that some members of the population may not have any chance of being included in the sample.
1. Probability Sampling 1.1 Simple Random Sampling – sampling is done by drawing lots or through the use of random numbers. 1.2 Systematic Random Sampling – sampling is done by selecting every kth element in the population with the starting point determined at random. (usually by making k = N/n ) NOTE: This sampling technique should not be used if there is an underlying periodicity in the sampling interval.
1. Probability Sampling 1.3 Stratified Random Sampling – sampling is done by first dividing the population into a number of nonoverlapping sub-populations or strata and then taking samples from each stratum.
There are two procedures that can be used to determine the sample size per stratum.
Stratified Random Sampling 1.3.1Equal
Allocation – divide the intended sample size (n) by the number of strata (k) in order to obtain the number of samples from each stratum ( n1 , n2 , nk). Formula:
n ni = k
Stratified Random Sampling 1.3.2
Proportional Allocation – divide the size of each stratum ( N1 , N 2 , N k ) by the population size (N) & multiply the result by the intended sample size (n). Formula:
Ni ni = ×n N
1. Probability Sampling 1.4 Cluster Sampling 1. divide the population into (geographical) groups called clusters, 2. select a random sample of clusters, and 3. select a random sample of elements from each of the selected clusters.
2. Non-Probability Sampling 2.1Convenience Sampling – selecting those elements that are readily available (doing a survey by phone) or those that happen to be in a place at a certain time (conducting a taste test) in order to obtain quick results. 2.2Quota Sampling – samples are chosen based on the judgment or prior knowledge of the researcher with the objective of reaching a certain target quota (polls conducted via radio or television).
Data Gathering Methods Direct Methods Observation Interview Focus Groups
2. Indirect Method Questionnaire Journals Review of Records
Sampling Techniques & Data Gathering Methods
-end-
