Statistics and probability - For Demo in Senior High School.pptx

Statistics and probability
Tell me something about the picture
What are the things that you want to study?
What is random sampling?
The leader of the group will present their output in the class.

Rubric for presentation:

Criteria
content
presentation
score
total
100
100
200
Random Sampling

1. Statistics and Probability

2. Tell me something about the picture

3. What are the things that you want to study?

4. What is random sampling?

5. The leader of the group will present their output in the class. Rubric for presentation: Criteria Score Content 5 Presentation 5 Total 10

6. Random Sampling

7. The population refers to the whole group under study or investigation. In research, the population does not always refer to people. It may mean a group containing elements of anything you want to study, such as objects, events, organizations, countries, species, organisms, etc.

8. A sample is a subset taken from a population, either by random sampling or by non-random sampling. A sample is a representation of the population where it is hoped that valid conclusions will be drawn from the population. Target population Sample

9. Random sampling is a selection of n elements derived from the N population, which is the subject of an investigation or experiment, where each point of the sample has an equal chance of being selected using the appropriate sampling technique.

10. Types of Random Sampling Techniques Lottery Sampling Systematic Sampling Stratified Random Sampling Cluster Sampling Multi-stage Sampling

11. Lottery sampling 1. Lottery sampling is a sampling technique in which each member of the population has an equal chance of being selected. An instance of this is when members of the population have their names represented by small pieces of paper that are then randomly mixed together and picked out. In the sample, the members selected will be included.

12. Systematic sampling 2. Systematic sampling is a sampling technique in which members of the population are listed and samples are selected at intervals called sample intervals. In this technique, every nth item in the list will be selected from a randomly selected starting point. For example, if we want to draw a 200 sample from a population of 6,000, we can select every 3rd person in the list. In practice, the numbers between 1 and 30 will be chosen randomly to act as the starting point.

13. Systematic sampling

14. Stratified random sampling 3. Stratified random sampling is a sampling procedure in which members of the population are grouped on the basis of their homogeneity. This technique is used when there are a number of distinct subgroups in the population within which full representation is required. The sample is constructed by classifying the population into subpopulations or strata on the basis of certain characteristics of the population, such as age, gender or socio-economic status. The selection of elements is then done separately from within each stratum, usually by random or systematic sampling methods.

15. Stratified random sampling Example: Using stratified random sampling, select a sample of 400 students from the population which are grouped according to the cities they come from. The table shows the number of students per city. City Population (N) A 12,000 B 10,000 C 4,000 D 2,000 Total 28,000

16. Stratified random sampling Solution: To determine the number of students to be taken as sample from each city, we divide the number of students per city by total population (N= 28,000) multiply the result by the total sample size (n= 400).

17. Stratified random sampling City Population (N) Sample (n) A 12,000 B 10,000 C 4,000 D 2,000 City Population (N) Sample (n) A 12,000 B 10,000 C 4,000 D 2,000

18. Cluster sampling 4. Cluster sampling is sometimes referred to as area sampling and applied on a geographical basis. Generally, first sampling is performed at higher levels before going down to lower levels. For example, samples are taken randomly from the provinces first, followed by cities, municipalities or barangays, and then from households.

19. Multi-stage sampling 5. Multi-stage sampling uses a combination of different sampling techniques. For example, when selecting respondents for a national election survey, we can use the lottery method first for regions and cities. We can then use stratified sampling to determine the number of respondents from selected areas and clusters.

20. Do you have any question class? If none, let us proceed to activity 1.

21. Direction: Identify the terms being described and write your answer on a separate sheet of paper. It refers to the entire group that is under study or investigation. It is a subset taken from a population, either by random or non-random sampling technique. A sample is a representation of the population where one hopes to draw valid conclusions from about population. This is a selection of n elements derived from a population N, which is the subject of the investigation or experiment, where each sample point has an equal chance of being selected using the appropriate sampling technique. A sampling technique where every member of the population has an equal chance of being selected. It refers to a sampling technique in which members of the population are listed and samples are selected in intervals called sample intervals.

22. Answers Population Sample Random sampling Lottery sampling Systematic sampling

23. Assignment Direction: On your answer sheet, give one situation where each of the sampling methods is being applied.   Lottery sampling: Systematic sampling: Stratified random sampling: Cluster sampling: Multi-stage sampling: