Random Sampling Techniques for SHS Grade 11

Random Sampling Techniques Grade 11

1. Random Sampling Techniques

2. Learning Outcomes Students should be able to define essential concepts in sampling. Students should be able to identify different sampling methods. 1 2

3. Topics for Discussion Definition of Terms Advantages of Sampling Non-Probability Sampling 1 2 3 4 Probability Sampling

4. It refers to a collection of individuals who share one or more noteworthy traits that are of interest to the researcher. The population may be all the individuals belonging to a specific category or a narrower subset within that larger group. POPULATION It is a small portion of the population selected for observation and analysis. SAMPLE It is the procedure of getting a small portion of the population for research. SAMPLING Definition of Terms

5. Advantages of Sampling It saves time, money, and effort. It yields better outcomes. It is faster, less expensive, and more cost-effective. It is more accurate. It provides more comprehensive information.

6. Random Sampling Every member of the population has a probability of being selected or included in the sample.

7. Random Sampling It is a sampling method of choosing representatives from the population wherein every sample has an equal chance of being selected. Accurate data can be collected using random sampling techniques.

8. Random Sampling Techniques SIMPLE RANDOM SAMPLING All members of the population have an equal chance at being chosen as part of the sample. STRATIFIED RANDOM SAMPLING The population is split into different groups. People from each group will be randomly chosen to represent the whole population. The sample is drawn by randomly selecting a starting number and then selecting every nth unit in arbitrary order until the desired sample size is reached. SYSTEMATIC RANDOM SAMPLING CLUSTER/AREA SAMPLING Districts or blocks of a municipality or a city which are part of the cluster are randomly selected. SIMPLE RANDOM SAMPLING

9. Systematic Random Sampling 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 list. To determine the interval to be used in identifying the samples to who will participate in the study, use the formula; K=N/n (population/sample).

10. Non-Probability Sampling The sampling technique that does not involve random selection of data. Participants are intentionally selected based on certain identified factors.

11. Non-Probability Sampling Methods CONVENIENCE SAMPLING Participants are chosen for their convenience and availability, rather than through a random or systematic selection process. EXPERT SAMPLING QUOTA SAMPLING SNOWBALL SAMPLING Individuals with specialized knowledge or expertise in a particular field are selected to participate in a study. Participants are selected based on pre-defined quotas to represent specific characteristics or subgroups. Participants are chosen based on referrals or recommendations from existing participants.

12. Slovin’s Formula It is used to compute for the sample size in a study given the population and margin of error. n = ___ N___ 1 + N N- population n-sample size e- margin of error  

13. Slovin’s Formula 1. Find out how many samples from the population of 2000 student drivers you need to take for a survey with a margin of error of 8%.

14. Slovin’s Formula 2. Suppose that a company wants to conduct marketing supply research to know about consumer preferences. The company estimates that a total of N = 10000 people are regular loyal customers of the company. How many of these people should be interviewed to understand customer preferences? Take the margin of error to be 5%.

15. Activity Suppose a lawyer wants to estimate the proportion of individuals in a certain neighborhood that are in favor of a new law. Suppose he knows there are 10,000 individuals in this neighborhood, and it would take far too long to survey each individual, so he would instead like to take a random sample of individuals. Assume that he would like to estimate this proportion with a margin of error of .05 or less. Suppose a botanist wants to estimate the mean height of a certain species of plant in some region. Suppose she knows there are 500 of these plants in the region and it would take far too long to measure each individual plant, so she would instead like to take a random sample of plants. Assume that she would like to estimate this mean with a margin of error of .02 or less.

16. Thank you for listening!