sampling and data collection in mathematics

math7 q3 1 FINAL JO.pptx

1. SAMPLING AND DATA COLLECTION

2. Learning Competency: I nvestigate different data collection and sampling techniques

3. Which of the following best describes a sample in data collection? A ) A summary of data B ) A large group of people C ) A small group chose

4. Why do researchers use sampling in data collection? A ) To collect data from every individual in the population B ) To save time and resources C ) To ensure they get different answers D ) To avoid using statistics

5. What is the term for the entire group from which a sample is taken? A ) Data set B ) Subgroup C ) Population D ) Cluster

6. Data collection and sampling techniques are critical components of research methodology in various fields, including social sciences, natural sciences, and business.

7. DATA COLLECTION Data collection is the process of gathering information to use for analysis this concept is introduced to help students understand how data can be collected, recorded, and used to make decisions or draw conclusions

8. Data collection is the process of gathering facts, figures, or information from various sources to learn something or answer a question DATA COLLECTION

9. Data Collection Techniques 1. Surveys and Questionnaires: Description: Structured tools with a series of questions to gather information from respondents. Types: Online surveys, paper surveys, telephone surveys. Advantages: Cost-effective, scalable, can reach a large audience. Disadvantages: Potential for low response rates, survey fatigue, and biased responses.

10. 2. Interviews : Description : Direct, face-to-face, or virtual conversations to gather detailed information. Types: Structured, semi-structured, unstructured. Advantages: Depth of information, ability to probe responses. Disadvantages: Time-consuming, potential interviewer bias, costly .

11. 3. Observations: Description: Systematically watching and recording behavior or events. Types: Participant observation, non-participant observation. Advantages: Provides real-time data, context-rich information. Disadvantages: Observer bias, can be intrusive, time-consuming.

12. 4. Experiments: Description: Controlled studies to test hypotheses by manipulating variables. Types: Laboratory experiments, field experiments. Advantages: High internal validity, ability to establish causation. Disadvantages: Can lack external validity, ethical concerns

13. Sampling Techniques Probability Sampling: 1. Simple Random Sampling: Description: Each member of the population has an equal chance of being selected. Advantages: Reduces selection bias, easy to implement. Disadvantages: Can be impractical for large populations. 2. Systematic Sampling: Description: Selecting every nth member from a list. Advantages: Simple and quick.

14. Stratified Sampling: Description : Dividing the population into strata and randomly sampling from each stratum. Advantages: Ensures representation of all subgroups. Disadvantages: Requires detailed population information. Cluster Sampling: Description: Dividing the population into clusters, then randomly sampling clusters. Advantages: Cost-effective for large populations.

15. 5. Multistage Sampling: Description: Combining multiple sampling methods, usually involving clustering. Advantages: Flexible, can handle large populations. Disadvantages: Complexity can introduce errors.

16. 2. Non-Probability Sampling: 1 . Convenience Sampling: Description: Sampling individuals who are easily accessible. Advantages: Quick and easy. Disadvantages: High risk of bias, not representative. 2. Judgmental (Purposive) Sampling: Description: Selecting individuals based on specific criteria or purpose. Advantages: Focused, useful for exploratory research. Disadvantages: Subjective, can introduce bias.

17. 3. Snowball Sampling: Description: Participants recruit other participants. Advantages: Useful for hard-to-reach populations. Disadvantages: Potential for biased samples, reliance on initial subjects. 4. Quota Sampling: Description: Ensuring sample reflects certain characteristics in proportion to the population. Advantages: Ensures diversity within the sample. Disadvantages: Not random, can introduce bias.

18. V: SAMPLING AND DATA COLLECTION Explain the sampling process Describe the methods of data collection

19. V: SAMPLING AND DATA COLLECTION Definition of Population, Sample, Sampling criteria, factors influencing Sampling process, types of sampling techniques. Data- why, what, from whom, when and where to collect. Data collection methods and instruments: Methods of data collection: Questioning, interviewing, Observations, record analysis and measurement Types of instruments Validity & Reliability of the Instrument Pilot study Data collection procedure

20. Introduction - Sampling Sampling - Part of our daily life. We decide about certain things – checking small portion. Eg: Rice, Tea. Sampling is similar concept in research. Generally not possible to observe each and every individual in the population the researcher wants to study.

21. Various constrains – lack of time, money, and problem of accessibility etc. So sample of people is studied – to make inferences. Sampling is crucial stage in research process. And vital part of research methodology. Introduction - Sampling

22. Quality of sample can have profound impact on outcome of study. Poor Sampling Technique – Compromise research findings. Introduction - Sampling

23. So researcher must use a appropriate sampling technique – To select samples - Reflecting the characteristics of study population accurately. All decisions in study is based on data from sample. Introduction - Sampling

24. 1. Identify the population of interest General term of population - People in our town, region, state or country – irrespective of gender, age, religion, ethnicity, marital status, etc. Population (Universe) – group have specific common characteristics that researcher wishes to investigate in his research study.

25. Well defined population increases the probability – including appropriate sample (fit) to the research objective. The elements of population may include – human beings, places – hospital, objects, procedure like hand washing, observation of BP etc. 1. Identify the population of interest

26. Definition: Population The term population refers to the aggregate or totality of all the objects, subjects, or members that conform to a set of specifications. Population composed of two groups. Target population Accessible population

27. The Target Population The whole group of the people/objects to which the researcher wishes to generalize the study findings and which meet a eligibility criteria or inclusion criteria set by the researcher .

28. Eligibility criteria or inclusion criteria – criteria specified by the researcher to define who will be included in the study (Exclusion criteria). The Target Population

29. The Target Population EXAMPLES All the School age children with asthma, All the Lactating women All low birth weight infants.

30. Not possible to include entire target population for the research study – manpower, time, money, etc. Geographically dispersed or unwilling to participate. So, need to take a part of population, accessible to the researcher – Accessible population. The Target Population

31. Accessible Population Accessible population – is a subset of the target population. It is limited to region, state, city, country, or institution. Sample taken from accessible population and generalization is made to target population.

32. The Target Population Subset of the target population . Conform to the designated criteria. Accessible to the researcher. The Accessible Population The aggregate of cases. The researcher would like to make generalizations. Criteria Eligibility criteria or inclusion criteria. Exclusion criteria.

33. Eg All School age children with asthma treated in allergic clinic of SDS TRC and RGICD, All Lactating women living in particular area, All low birth weight infants admitted into neonatal ICUs of IGICH. Accessible Population

34. The Target Population All the School age children with asthma , All the Lactating women All low birth weight infants. The Accessible Population All School age children with asthma treated in allergic clinic of SDS TRC and RGICD. All Lactating women living in particular area, All low birth weight infants admitted into neonatal ICUs of IGICH. EXAMPLES

35. Scenario To know the prevalence/incidence of hospital acquired infections among patients admitted in hospital in a month. Difficult to study all admitted patients. Sample of patients taken in few wards. Inference of this data can represent – Prevalence of hospital acquired infections among patients in general.

36. 2.Construct A sampling frame Once accessible population is clear – researcher prepares sampling frame. Sampling frame is the list of all the members of the population from which the sample is taken. Sampling frame is not large as the population – still it is a big group of people.

37. Not possible to study every single unit of accessible population – so researcher need to draw the sample from the sampling frame (using some techniques). 2.Construct A sampling frame

38. Sampling frame

39. Eg - Study to be conducted on nurses of hospital List of all nurses working in that particular hospital –fulfilling inclusion and exclusion criteria – Sampling frame. An ideal sampling frame – Name the elements only once. 2.Construct A sampling frame

40. 3. Specifying the sampling unit It is a basic unit which contains a single element or a group of elements of the population to be sampled. It refers to the one from where the subjects will be selected.

41. Unit of enquiry : is the “subject” from whom information is to be extracted or on whom a procedure is to be performed. Eg: Study on health workers Subcentre is sampling unit Health workers – unit of enquiry 3. Specifying the sampling unit

42. 3. Specifying the sampling unit

43. 4. Determine the sample size Sample size plays an important role in the process of sampling. The total number of subjects/units/observations in the sample constitutes the sample size of the study (n). N refers to the entire target population. Ratio of n/N is called sampling fraction.

44. Important concern - adequate number of units for inclusion in the sample. Calculation of exact sample size is very difficult – can get only approximation. It varies in different research settings. Bigger sample size leads to more precision in the results 4. Determine the sample size

45. Very important to have accurate sample size. Too large sample – waste of time, resources and money. Too small sample – lead to inaccurate results. So determining the appropriate sample size – important step in any research study. 4. Determine the sample size

46. 5. Choose a sampling technique Sampling is the act, process or technique of selecting a group of people, events, behaviours, or other elements with which to conduct a study. Sampling: It refers to the process of selecting a portion of the population to represent the entire population.

47. Sampling is the process of selecting observations (a sample) to provide an adequate description and inferences of the population. Sampling method outline the technique or approach for selecting the sample units. Sampling

48. Choice of selecting the sampling method is influenced by – objectives of the study, availability of financial resources, time constraints and the nature of the problem to be studied. Basically two methods to select a sample from sampling frame- Random/Probability, Non-random/Nonprobability 5. Choose a sampling technique

49. 6. Select sample as per the chosen sampling technique Population, sampling frame, sampling method, and sample size – use all theses information – to select sample for the study. Final step in sampling process Actual selection of the sample elements carried out in this stage.

50. Definition: Sample is a subgroup of the population. It is defined as a collection of individual observations from the population (about which inferences are to be made), and is obtained by a specific method. Sample

51. Sampling error - Refers to differences between populations values and sample values Sampling frame - A list of all the elements in the population, from which the sample is drawn

52. ACTIVITY Favorite Book Bar Graph: Objective: Visualize categorical data. Activity: Ask each student to name their favorite book. Tally the results and create a bar graph to show the popularity of different books