Sampling Techniques PDF
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This document provides an overview of various sampling techniques. It explores both probability and non-probability methods, demonstrating how they can be utilized for different research purposes. Examples from different research scenarios are shown.
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Suppose you want to conduct a study on a small town with a population of 750 residents. Using Slovin's formula and a margin of error of 0.01, determine the sample size required for the study. A survey needs to be conducted on a population of 8,000 students. If the researcher is willing...
Suppose you want to conduct a study on a small town with a population of 750 residents. Using Slovin's formula and a margin of error of 0.01, determine the sample size required for the study. A survey needs to be conducted on a population of 8,000 students. If the researcher is willing to accept a margin of error of 10%, what is the required sample size using Slovin's formula? You are conducting a study with a population of 2,500 people. You want to use Slovin's formula to determine the sample size, with a margin of error of 5%. Calculate the required sample size. Read and analyze the scenario below. Total no. of residents A group of researchers from TVL- Cookery conducted a survey about the acceptance of the residents of Sitio Dalawang Kawayan in the taste, appearance, and price of their own innovated pandesal. Step (1) conducted in gathering the people who participated in the study In determining the participants of their study, they secured a letter to the barangay captain and asked for the total number and the list of the names of their residents whose ages range from 18 and above. Step (2) conducted in gathering the people who They found out that there were 450 residents. Then, they computed participated in the study the sample size, which was 212, using the Slovin’s. Then, they picked indiscriminately their participants using the fishbowl where the names of the residents were all inside the bowl. Total no. of people who participated in their study How did the researchers from the scenario above, gather the people who participated in their study? Total no. of residents Read and analyze the scenario below. A group of researchers from the TVL- BPP conducted a survey to the SHS graduates in Tanay who took and passed the TESDA NCII Step (1) conducted in gathering the people who Assessment. An assessor form Tanay introduced them to two participated in the study passers of the said assessment. They learned that the passers have friends who took the assessment, too, and have recommended them five more. These recommended friends also Step (2) conducted in recommended another 10 more who participated in the study. gathering the people who participated in the study Then those people spread word of the study ‘til another 23 more were added participants who passed the NCII. Total no. of people who How did the researchers from the scenario above, gather the participated in their study people who participated in their study? Probability Sampling means that every member of the population has a chance of being selected. Stratified Random Sampling? Stratified random sampling is a method of sampling that involves the division of a population into smaller subgroups known as strata. Stratified random sampling is also called proportional random sampling or quota random sampling. Given: Total Population = 450 Sample Size (using Slovin’s, margin of error) = 212 Group 1 = 280 Group 2 = 100 Group 3 = 70 Group 1 SRS = 212 X 280 Group 2 SRS = 212 X 100 450 450 =.47 X 280 =.47X 100 = 132 = 47 Group 3 SRS = 212 X70 450 =.47 X 70 = 33 To find the proportional % 280 X.62 100 X.22 = group population Total population 70 X.16 280 /2 100 /2 75 /2 Simple vs. Stratified Random Samples Simple random samples and stratified random samples are both statistical measurement tools. A simple random sample is used to represent the entire data population. 2 A stratified random sample divides the population into smaller groups, or strata, based on shared characteristics. However, stratified sampling is more complicated, time consuming, and potentially more expensive to carry out than simplified random sampling.