Quantitative Research Sampling Techniques

This is a presentation about sampling techniques used in Quantitative Research

1. SAMPLING TECHNIQUES P R A C T I C A L R E S E A R C H 2 | E N G R . G A R C I A , J M S

2. POPU L A T I O N It is the entirety of the group that the researcher wants to draw a conclusion about. S A M P L E It is the specific group that the researcher will collect the data from.

3. S A M P L I N G T E C H N IQ U E A process in which researchers take a group of people from a larger crowd for measurement

4. P R O B A B I L I T Y S A M P L I N G T E C H N IQ U E Probability sampling means that every member of the population has a chance of being selected. It is mainly used in quantitative research. If you want to produce results that are representative of the whole population, probability sampling techniques are the most valid choice.

5. S L O V I N ’ S F O R M UL A A tool used to calculate sample size n = sample size N = population size e = margin of error (e = 5% and confidence rate = 95%) n = 𝑁 2 (1+𝑁𝑒 ) where:

6. S L O V I N ’ S F O R M UL A Sample Problem: A researcher is conducting a survey on the reading habits of Grade 12 HUMSS students in a senior high school. There are 850 HUMSS students enrolled. The researcher wants to achieve a 95% confidence level and decides to use a margin of error (e) of 5% .   Given: N = 850 HUMSS students e = 5% n = 264 HUMSS students  

7. PROBABILITY SAMPLING TECHNIQUE S I M P L E R A N D O M S A M P L I N G This technique is the most basic random sampling wherein , each element in the population has an equal probability of being selected. Example: Fishbowl recitation , draw lots

8. PROBABILITY SAMPLING TECHNIQUE S Y S T E M A T I C R A N D O M S A M P L I N G This can be done by listing all the elements in the population and selecting every kth element in your population list. This is equally precise as the simple random sampling. It is often used on long population lists.

9. PROBABILITY SAMPLING TECHNIQUE S Y S T E M A T I C R A N D O M S A M P L I N G To determine the interval to be used in identifying the samples to who will participate in the study, use the formula: 𝐾 = 𝑁 (𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑠𝑖𝑧𝑒) 𝑛 (𝑆𝑎𝑚𝑝𝑙𝑒 𝑆𝑖𝑧𝑒

10. PROBABILITY SAMPLING TECHNIQUE CLUSTER SAMPLING It is a random sampling wherein population is divided into clusters or groups and then the clusters are randomly selected. All elements of the clusters randomly selected are considered the samples of the study.

11. P R O B A B I L I T Y S A M P L I N G T E C H N I Q U E CLUSTER SAMPLING Example: A researcher would like to interview of all public senior high school students across Luzon . As a researcher, cluster will be selected to satisfy the plan size. In the given example, the first cluster can be by region, second cluster can be by division, and the third cluster can be by district.

12. P R O B A B I L I T Y S A M P L I N G T E C H N I Q U E CLUSTER SAMPLING Example: A researcher would like to interview of all public senior high school students across Luzon . As a researcher, cluster will be selected to satisfy the plan size. CLUSTER 1 Regions in Luzon: 8 Luzon is divided into 8 administrative regions : Ilocos Region (Region I) Cagayan Valley (Region II) Central Luzon (Region III) CALABARZON (Region IV-A) MIMAROPA (Region IV-B) – considered part of Luzon group, though geographically includes islands Bicol Region (Region V) Cordillera Administrative Region (CAR) – an autonomous region National Capital Region (NCR) – Metro Manila

13. P R O B A B I L I T Y S A M P L I N G T E C H N I Q U E CLUSTER SAMPLING Example: A researcher would like to interview of all public senior high school students across Luzon . As a researcher, cluster will be selected to satisfy the plan size. CLUSTER 2 Provinces in Luzon: 38 These regions are subdivided into 38 provinces (including island provinces under MIMAROPA like Palawan, Marinduque, etc.)

14. P R O B A B I L I T Y S A M P L I N G T E C H N I Q U E CLUSTER SAMPLING Example: A researcher would like to interview of all public senior high school students across Luzon . As a researcher, cluster will be selected to satisfy the plan size. CLUSTER 3 Districts (Congressional Districts): 144 in Luzon These are legislative districts represented in the House of Representatives. Luzon has approximately 144 congressional districts , including those in NCR and highly urbanized cities.

15. PROBABILITY SAMPLING TECHNIQUE STRATIFIED RANDOM SAMPLING The population is first divided into strata or groups before selecting the samples. The samples are chosen from these subgroups and not directly from the entire population.

16. PROBABILITY SAMPLING TECHNIQUE STRATIFIED RANDOM SAMPLING A population of 600 Junior High School students include 180 Grade 7, 160 Grade 8, 150 Grade 9, and 110 Grade 10. If the computed sample size is 240, the following proportionate sample will be as follows N = 600 n = 𝑁 (1+𝑁𝑒 2 ) 600 n = ( 1 + 600 ( 0. 05) 2 ) n = 240

17. PROBABILITY SAMPLING TECHNIQUE S T R A T I F I E D R A N D O M S A M P L I N G The number of members per subgroup is divided by the total accessible sample size. The percentage result of member per subgroup will be multiplied from the computed total sample size. After obtaining the sample size per strata, then simple random sampling will be done for selection of samples from each group.

18. PROBABILITY SAMPLING TECHNIQUE S T R A T I F I E D R A N D O M S A M P L I N G SAMPLE SIZE PER SUBGROUPS 180/600 = 0.30 x 240 = 72 Grade 7 students 160/600 = 0.27 x 240 = 65 Grade 8 students 150/600 = 0.25 x 240 = 60 Grade 9 students 110/600 = 0.18 x240 = 43 Grade 10 students 100% 240 students

19. PROBABILITY SAMPLING TECHNIQUE STRATIFIED RANDOM SAMPLING A population of 2500 employees of ABC Corporation include , 180 factory workers , 300 Quality Assurance , 200 Office workers , and 200 Field workers . Find the: (n) Sample size & (n) Sample size per strata

20. N ON - P R O BAB I L I T Y S A M P L I N G T E C H N I QU E involves the intentional selection of certain participants in order to gather information about members of a specific group or people with specific insight into a particular area.

21. NON- PROBABILITY SAMPLING TECHNIQUE C O N V E N I E N C E S A M P L I N G Selecting a sample based on the availability of the member and/or proximity to the researcher. Also known as “accidental”, “ oppo r tunit y ” , or “grab” sampling.

22. NON- PROB. SAMPLING TECHNIQUE QO U T A SA M P L I N G Proportion of the groups in the population were considered in the number and selection of the respondents.

23. NON- PROB. SAMPLING TECHNIQUE P U R PO S I V E S A M P L I N G Intentional selection of participants or respondents based on their ability to explain a certain phenomenon, specific theme or concept.

24. NON- PROB. SAMPLING TECHNIQUE P U R PO S I V E S A M P L I N G On this sampling, researcher relies on his/ her own judgement when choosing participants through predetermined standards.

25. T Y P E O F P U R P O S I V E S A M P L I N G C R I T E R I O N S A M P LI N G It is a purposeful sampling that identifies participants through particular criteria based from the needs of the study. This can be based on profile experience, or the concern of the research.

26. EXAMPLE: WINE TASTING

27. T Y P E O F P U R P O S I V E S A M P L I N G SN O W B A L L S A M P L I N G Participants in the study were tasked to recruit other members for the study.