Lesson 5 Describing Sample Size and Sampling Procedures
SAMPLE SIZE DETERMINATION -A sample (n) is a selection of respondents for a research study to represent the total population (N). - Too large a sample could mean a waste of resources, both human & financially; too small a sample decreases the utilization of results.
REASONS FOR THE USE OF SAMPLES: 1. It saves time compared to doing a complete sensus which requires more time. 2. It also saves money because it is less costly than conducting a compelete census.
3. It allows more particular attention to be given to a number of elements than when doing a census. 4. There is a greater error in reporting results of a census caused by inexperienced interviewers. There is less sampling errors in a survey.
5. Some research studies in the industry may only be performed on a sample of items.
SLOVIN’S Formula in Determining the Sample Size
Informations needed to determine the sample size using Slovin’s formula: Population (N) - consists of members of a group that a researcher is interested in studying the members of a group that usually have a common or similar characteristics.
Margin of Error - the allowable error margin in research. A confidence interval of 95% gives a margin of error of 5%; a 98% gives a margin of error of 2%; and so on.
Sample size can be obtained using this formula: n = N 1 + N e 2 where; n= sample size N= total population e= margin of error
EXAMPLE #1 A researcher wants to conduct a survey; if the population of a big university is 35,000, find the sample size if the margin of error is 5%. Using the formula: n = N 1 + Ne 2
Substituting the given data: n = 35,000 1 + (35,000)(.05) 2 n = 35,000 1 + (35,000)(.0025)
= 35,000 1 + 87.5 = 35,000 88.5 n = 395
EXAMPLE #2 Suppose you plan to conduct a study among 1,500 Grade 11 students enrolled in the STEM track. How many respondents are needed using a margin error of 2%? Given: N = 1, 500 n = 2%
n = N 1 + Ne 2 n = 1, 500 1 + (1, 500)(.02) 2 n = 1, 500 1 + (1, 500)(.0004)