Research methodology for natural resource management students

Research methodology. Jigjiga university. Natural resource management department

1. CHAPTER THREE SAMPLING

2. Concept of Sampling Let us take a very simple example to explain the concept of sampling. Suppose you want to estimate the average age of the students in your class. There are two ways of doing this. The first method is to contact all students in the class, find out their ages, add them up and then divide this by the number of students (the procedure for calculating an average). The second method is to select a few students from the class, ask them their ages, add them up and then divide by the number of students you have asked. 11/18/2024 Research Methods for NRM Studenst 2

3. Cont….. Sampling , therefore, is the process of selecting a few (a sample) from a bigger group (the sampling population) to become the basis for estimating or predicting the prevalence of an unknown piece of information, situation or outcome regarding the bigger group. The  population  is the entire group that you want to draw conclusions about. The  sample  is the specific group of individuals that you will collect data from. 11/18/2024 Research Methods for NRM Studenst 3

4. STEPS IN SAMPLING A sampling design is a definite plan for obtaining a sample from a given population. It refers to the techniques or procedure the researcher would adopt in selecting items for the sample. There are four major steps that are applied in the process of sample selection. Defining the population Listing the population Selecting a representative sample Obtaining an adequate sample 11/18/2024 Research Methods for NRM Studenst 4

5. Basic terms and concepts in sampling Types of Sampling Two broad categories of sampling: Probability and non-probability sampling. Probability sampling also known as Random sampling - a sample that has been selected using random selection so that each unit in the population has a known chance of being selected. The aim of probability sampling is to keep sampling error to a low minimum. 11/18/2024 Research Methods for NRM Studenst 5

6. Basic terms and concepts in sampling Non- probability sampling- a sample that has not been selected using a random selection method. Essentially this implies that some units in the population are more likely to be selected than others. Sampling error- the difference between a sample and the population from which it is selected, even though a probability sample has been selected. 11/18/2024 Research Methods for NRM Studenst 6

7. Cont………. Non sampling error: differences b/n the population and sample that arise either from deficiencies in the sampling approach, such as inadequate sampling frame or non-response, or from such problems as poor question wording, poor interviewing, or flawed processing of data. Non response: a source of non-sampling error that is particularly likely to happen when individuals are being sampled. It occurs whenever some members of the sample refuse to cooperate, cannot be contacted, or are for some reasons not supplying the required data. Census: the complete enumeration of all members of a population. 11/18/2024 Research Methods for NRM Studenst 7

8. Probability sampling Probability sampling means that every member of the population has a chance of being selected. It is mainly used in quantitative research. There are five common methods of selecting probability sample . These include Simple random sampling, Systematic random sampling, Stratified random sampling, Cluster sampling, and Multistage sampling. 11/18/2024 Research Methods for NRM Studenst 8

9. Types of probability sampling Assume that there are 9, 000 full time students in the university. How to select simple Random samples? Simple random sample In a simple random sample, every member of the population has an equal chance of being selected Example: Simple random sampling You want to select a simple random sample of 1000 employees of a social media marketing company. You assign a number to every employee in the company database from 1 to 1000, and use a random number generator to select 100 numbers. 11/18/2024 Research Methods for NRM Studenst 9

10. Key steps in devising our simple random sample can be represented as follows 1. Define (Fix) the . e.g. 9000 university students. 2. Select or devise a comprehensive sampling frame . i.e. identify the records of students. 3. Decide your sampling size-n 4. List all the students in the population and assign them consecutive numbers from 1 to N. 1 -9000 students 5. Using a table of random number, or a computer programme that can generate random numbers , select n- 450 different numbers that lie between 1 and N- 9000. 6. The students to which the n=450 random numbers refer constitute the sample. NB. No bias!! 11/18/2024 Research Methods for NRM Studenst 10

11. B. Systematic Random sample Systematic sampling is similar to simple random sampling, but it is usually slightly easier to conduct. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals. Example: Systematic sampling All employees of the company are listed in alphabetical order. From the first 10 numbers, you randomly select a starting point: number 6. From number 6 onwards, every 10th person on the list is selected (6, 16, 26, 36, and so on), and you end up with a sample of 100 people . 11/18/2024 Research Methods for NRM Studenst 11

12. C. Stratified random sampling Stratified sampling involves dividing the population into subpopulations that may differ in important ways. It allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample. To use this sampling method, you divide the population into subgroups (called strata) based on the relevant characteristic (e.g., gender identity, age range, income, job role, occupation, religion etc. ). Based on the overall proportions of the population, you calculate how many people should be sampled from each subgroup. Then you use random or  systematic sampling  to select a sample from each subgroup. 11/18/2024 Research Methods for NRM Studenst 12

13. Cont ……….. Example: Stratified sampling The company has 800 female employees and 200 male employees. You want to ensure that the sample reflects the gender balance of the company, so you sort the population into two strata based on gender. Then you use random sampling on each group, selecting 80 women and 20 men, which gives you a representative sample of 100 people. 11/18/2024 Research Methods for NRM Studenst 13

14. Table 1. the advantages of random stratified sampling Faculty Population Stratified sample Possible simple random or systematic sample. Humanitarian 1800 90 85 Social sciences 1200 60 70 Pure sciences 2000 100 120 Applied sciences 1800 90 84 Agriculture 2200 110 91 total 9000 450 450 11/18/2024 Research Methods for NRM Studenst 14

15. D. Cluster sampling Cluster sampling also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups. If it is practically possible, you might include every individual from each sampled cluster. If the clusters themselves are large, you can also sample individuals from within each cluster using one of the techniques above. This is called  multistage sampling . 11/18/2024 Research Methods for NRM Studenst 15

16. Cont ….. Example: Cluster sampling The company has offices in 10 cities across the country (all with roughly the same number of employees in similar roles). You don’t have the capacity to travel to every office to collect your data, so you use random sampling to select 3 offices these are your clusters. To illustrate it let us suppose a researcher is interested in investigating the achievement of 5 th grade students in mathematics examination in Ethiopia primary school . Since primary schools are grouped by Region, zone, woreda , schools and classes, the researcher may take zones, woredas or schools as clusters. If he chooses schools as clusters then he may test all or a portion of students from the selected schools as his sample . 11/18/2024 Research Methods for NRM Studenst 16

17. E. Multistage sampling This is a further development of cluster sampling. This technique is used for large scale survey or inquiries extending to a considerably large geographical area like an entire country or nation. In this case the researcher has to use two or three or four or more stage sampling. The first stage may be to select a large primary sample units such as regional states, then administrative zones, then woredas , and finally certain families within woredas . When you want to study the behavior of students in the universities of a given country it is difficult for the data collection to travel throughout the country and collect a national sample. Collecting data from a widely dispersed population is costly, difficult and time taking . 11/18/2024 Research Methods for NRM Studenst 17

18. Multistage cluster sampling……. With cluster sampling, the primary sampling unit, the first stage of the sampling procedure- is not the units of the population to be sampled but groupings of those units. It is the later groupings or aggregations of population units that are known as clusters. Imagine that we want a nationally representative sample of 5000 students. Using simple random or systematic sampling would yield a widely dispersed sample which would result in a great deal of travel for interviews. 11/18/2024 Research Methods for NRM Studenst 18

19. Multistage cluster sampling….. One solution might be to sample universities and then students from each of the sampled universities. A probability sampling method would need to be employed at each stage. Thus we might randomly sample ten universities from the entire population of universities, thus yielding ten clusters and we would then interview 500 randomly selected. 11/18/2024 Research Methods for NRM Studenst 19

20. Multistage cluster sampling….. The ten universities need to be grouped by standard region . In this example two standard regions are identified. Five universities in each standard are being allocated. Then 500 students are to be sampled from each university in each standard groups. 11/18/2024 Research Methods for NRM Studenst 20

21. Multistage cluster sampling…….. In short group Ethiopia representatives by standard region and sample two regions. Then sample five universities from each of the two regions. Sample 500 students from each of the ten universities. 11/18/2024 Research Methods for NRM Studenst 21

22. Non-probability Sampling In a non-probability sample, individuals are selected based on non-random criteria, and not every individual has a chance of being included. Four types of non-probability sampling: Convenience sampling, Snowball sampling, Purposive sampling, and Quota sample. 11/18/2024 Research Methods for NRM Studenst 22

23. Convenience Sampling A convenience sample simply includes the individuals who happen to be most accessible to the researcher. This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can’t produce generalizable results. Convenience samples are at risk for both sampling bias and selection bias. 11/18/2024 Research Methods for NRM Studenst 23

24. Convenience Sampling……. Example: Convenience sampling You are researching opinions about student support services in your university, so after each of your classes, you ask your fellow students to complete a survey on the topic. This is a convenient way to gather data , but as you only surveyed students taking the same classes as you at the same level, the sample is not representative of all the students at your university. 11/18/2024 Research Methods for NRM Studenst 24

25. Snowball sampling If the population is hard to access, snowball sampling can be used to recruit participants via other participants. The number of people you have access to “snowballs” as you get in contact with more people. The downside here is also representativeness, as you have no way of knowing how representative your sample is due to the reliance on participants recruiting others. This can lead to sampling bias. 11/18/2024 Research Methods for NRM Studenst 25

26. Quota sampling…… Example: Quota sampling You are researching experiences of homelessness in your city. Since there is no list of all homeless people in the city, probability sampling isn’t possible. You meet one person who agrees to participate in the research, and she puts you in contact with other homeless people that she knows in the area. 11/18/2024 Research Methods for NRM Studenst 26

27. Purposive Sampling his type of sampling, also known as judgement sampling, involves the researcher using their expertise to select a sample that is most useful to the purposes of the research. It is often used in qualitative research, where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences, or where the population is very small and specific. An effective purposive sample must have clear criteria and rationale for inclusion. Always make sure to describe your inclusion and exclusion criteria and beware of observer bias affecting your arguments. 11/18/2024 Research Methods for NRM Studenst 27

28. Purposive Sampling Example: Purposive sampling You want to know more about the opinions and experiences of disabled students at your university, so you purposefully select a number of students with different support needs in order to gather a varied range of data on their experiences with student services. 11/18/2024 Research Methods for NRM Studenst 28

29. Review questions What do each of the following terms mean: population, probability sampling, non-probability sampling, sampling frame, repetitive sample, and sampling and non-sampling error? What area the goals of sampling? What are the main areas of potential bias in sampling? What is the significance of sampling error for achieving a representative sample ? 5. What are the main types of probability sample? 6. How does a stratified random sample offer precision than a simple random or systematic sample? 11/18/2024 Research Methods for NRM Studenst 29

30. Deductive research/approach A deductive approach is concerned with “developing a hypothesis (or hypotheses) based on existing theory, and then designing a research strategy to test the hypothesis. Deductive approach can be explained by the means of hypotheses, which can be derived from the propositions of the theory. In other words, deductive approach is concerned with deducting conclusions from premises or propositions. Deduction begins with an expected pattern “that is tested against observations, whereas induction begins with observations and seeks to find a pattern within them 11/18/2024 Research Methods for NRM Studenst 30

31. Deductive Research……… Style of reasoning in research that starts from theories or laws that are assumed to be universally true Hypothesis/propositions implied by these general theories/laws are developed and empirically tested general to particular E.g. For most normal goods, demand and price are negatively related Supply and price are positively related Price is directly related to the cost of production of a good Increase in the quality of road decreases cost of production Therefore, road construction decreases the price of the good while increasing its demand 11/18/2024 Research Methods for NRM Studenst 31

32. Inductive Research/Approach : Inductive approach, also known in inductive reasoning, starts with the observations and theories are proposed towards the end of the research process as a result of observations.  Inductive research “involves the search for pattern from observation and the development of explanations – theories – for those patterns through series of hypotheses Styles of reasoning that works from the particular phenomenon (observations) to a general/universal (theory or law). Begin with specific observations and measures, detect patterns and regularities, formulate tentative hypotheses and explore, and finally develop some general conclusions or theories 32 11/18/2024 Research Methods for NRM Studenst

33. Inductive research/approach…… E.g . All records made in many countries in the past 50 years have shown that the incidence of forest fire was significantly higher in areas that are more accessible and densely populated Therefore, human settlement and activities are one of the major causes of forest fire 11/18/2024 Research Methods for NRM Studenst 33

34. Contd. Deductive method is the most commonly followed as most researches are based on a certain theoretical framework Most researches involve both inductive and deductive reasoning Hypothetico-deductivist (thinking up hypotheses/postulates and deducing consequences from them, which can then be used to test the theory by experiment) Propositions based on tentative theoretical explanations Adopted by most scientific studies Both arguments need caution to avoid fallacies Differentiating facts from assumptions Accidental regularities or patterns 34 11/18/2024 Research Methods for NRM Studenst

35. End of Chapter 3 11/18/2024 35 Research Methods for NRM Studenst