### Demo presentation SVPISTM Sampling and scales.pptx

1. Research Methodology Sampling and Scales By PRADEEPKUMAR CHOKKANNAN 06.05.2021 Teaching Demonstration for Recruitment for Assistant Professor ,Management Sardar Vallabhbhai Patel International School Of Textiles & Management Coimbatore
2. Types of Research Variables • Independent variables (IV) • Dependent variables (DV) • Intervening variables 1. Mediating variable • Moderating Variable • Extraneous variables/Control variables In real-life situations, there can be many factors or variables that may affect the outcome. These variables are termed as extraneous variables • Confounding variable If an extraneous variable is the real reason for an outcome instead of independent variables
3. Mediation
4. Moderation
5. Types of Data � Primary & Secondary � Quantitative & Qualitative Data Collection � Observation ,Survey ,Telephone, interview ,focus group(6-10). Questionnaire � Close and Open Ended
6. Scales � For Measurement ,understanding,comparision . � Series of items arranged according to value for the purpose of quantification,numbers,symbols etc � A continuous spectrum
7. Scale characteristics � Description/classification/label (attendendence register) � Order or rank or > or < or = (100mtr Dash ranking) � Distance (Age difference btw 1st brother and 2nd brother is 2 years,2nd brother and 3rd brother is 2 years ) � Origin has a fixed beginning or true zero not assumed zero.(Income)
8. Primary Scales of Measurement 73 35 81 Scale Nominal Numbers Assigned to Runners Ordinal Rank Order of Winners Interval Performance Rating on a 0 to 10 Scale Ratio Time to Finish in Seconds Third place Second place First place 8.2 9.1 9.6 15.2 14.1 13.4
9. Primary Scales of Measurement
10. The Sampling Design Process A. Define the Population B. Determine the Sampling Frame C. Select Sampling Technique(s) D. Determine the Sample Size E. Execute the Sampling Process
11. Classification of Sampling Techniques Sampling Techniques Nonprobability Sampling Techniques Probability Sampling Techniques Convenience Sampling Judgmental Sampling Quota Samplin g Snowball Samplin g Systematic Sampling Stratified Samplin g Cluster Samplin g Simple Random Sampling
12. � A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample. � Nonprobability sampling is any sampling method where some elements of the population have no chance of selection � these are sometimes referred to as 'out of coverage'/'undercovered'.
13. Convenience sampling attempts to obtain a sample of convenient elements. Often, respondents are selected because they happen to be in the right place at the right time. Examples: � Use of student respondents � Members of social organizations � “People on the street” interviews • Judgmental sampling is a form of nonprobability sampling in which the population elements are selected based on the judgment of the research • Eg:This is the area of particular political party favours
14. Quota sampling may be viewed as two-stage restricted judgmental sampling. 1. The first stage consists of developing quotas of population elements. 2. In the second stage, sample elements are selected based on convenience or judgment. • In snowball sampling, an initial group of respondents is selected, usually at random. • Eg: Alcoholics
15. Simple Random Sample: �Each element in the population has a known and equal probability of selection Systematic Sampling �The sample is chosen by selecting a random starting point and then picking every ith (e.g. 5th, 10th) element in succession from the sampling frame
16. Stratified Sampling: 1.A two-step process in which the population is partitioned into subpopulations, or strata. � Every person in the population should be assigned to one and only one stratum and no population elements should be omitted. 2.Next, elements are selected from each stratum by a random procedure, usually simple random sampling. �A major objective of stratified sampling is to increase precision without increasing cost.
17. Cont.. � The elements/people within a stratum (e.g. male) should be as homogeneous as possible. � The elements/people across strata (e.g. male, female) should be as heterogeneous as possible. • The stratification variables should also be closely related to the characteristic of interest.
18. Cluster Sampling: 1.The target population is first divided into mutually exclusive and collectively exhaustive subpopulations, or clusters. 2.Then a random sample of clusters is selected, based on a probability sampling technique such as simple random sampling. 3.For each selected cluster, all the elements are generally included in the sample.
19. Technique Strengths Weaknesses Nonprobability Sampling Convenience sampling Least expensive, least time-consuming, most convenient Selection bias, sample not representative, not recommended for descriptive or causal research Judgmental sampling Low cost, convenient, not time-consuming Does not allow generalization, Subjective, selection bias Quota sampling Sample can be controlled for certain characteristics Selection bias, no assurance of representativeness Snowball sampling Can estimate rare Characteristics, convenient Selection bias, time-consuming Probability Sampling Simple random sampling Representative, results, projectable Difficult to construct sampling frame, expensive, lower precision Systematic sampling Can increase representativeness, easier to implement than SRS, sampling frame not necessary Can accidentally decrease representativeness Stratified sampling Include all important subpopulations, representative Difficult to select relevant stratification variables, not feasible to stratify on many variables, expensive Cluster sampling Easy to implement, cost effective, more representative Imprecise, difficult to compute and interpret results Choosing Nonprobability Vs. Probability Sampling
20. Validity and Reliability • The ability of a scale to measure what was intended to be measured is Validity � Reliability of measure indicates extent to which it is without bias and hence ensures consistent measurement across time (stability) and across the various items in the instrument (internal consistency).
21. Old Rifle New Rifle New Rifle Sun glare Low Reliability High Reliability Reliable but Not Valid Valid (Target A) (Target B) (Target C) Reliability and Validity on Target