Sampling in Sociological Research

elective courses

The aim of the course is to acquaint participants with probabilistic foundation of survey sampling and to teach them to design, draw and analyze elementary survey samples. Basic topics: 1. Population, sample, sample design. Sample statistics and its distribution properties. 2. Estimation accuracy for typical sample designs. 3. Practical problems of estimation accuracy: sample frame quality, complex sample design, missing values, nonresponse. 4. Non-random samples and estimation accuracy. After the cours participants should be able to determine estimation accuracy for typical sample designs and recognize statistical foundation s of determining estimation accuracy in practice of survey research.

Statistical inference in statistical courses for sociologists usually makes idealistic assumption about survey, in which sample is drawn in the simpliest possible way and all sampled units participate in a survey and respond to all questionnaire questions. Such situations never happen in real survey research in which sample design is complex and nonresponse and missing answers are present. Knowledge and skills aquired in elementary statistical training are not sufficient to assess the quality of statistical inference from sample data and to determine validity and accuracy of estimation. Statisticaly speaking, estimator bias and estimator variance is unknown. The course aim is to prepare participants to recognize such situation and to deal with tem with the help of popular statistical software

Topics:

I. Introduction to survey sampling

a. Population, sample, inclusion probability, sample design

b. Sample statistics distribution and its parameters

c. Estimator and its required properties

d. Random variable important in statistical inference. Limit theorems.

e. Estimation of population mean and proportion for simple random sampling

II. Single stage sample design

a. Simple random samle without replacement

b. Estimation of small proportion in simple random sampling

c. Stratified sampling. Sample allocation

d. Cluster sampling

e. Systematic sampling

III. Multistage sampling design

a. Deternining inclusion probabilities

b. Population total estimator

c. Ratio and regression estimators

d. Variance of population total estimator in miltistage complex designs

e. Estimation accuracy in multistage complex sample design.

IV. Practical problems of estimation accuracy

a. Missing data

b. Nonresponse. Quasi-confidence interval for population proportion

V. Nonrandom sampling and the problem of estimation accuracy

a. Random Digit Dialing

b. Internet research - Web Assissted Inteview

c. Random-quota sampling

1. Lissowski, G. (1968). Z zagadnień doboru próby. W: Metody statystyczne w socjologii. Pod redakcją Klemensa Szaniawskiego (pp. 11–69). Państwowe Wydawn. Naukowe.

2. Lissowski, G. (1971). Problem jednostek niedostępnych w reprezentacyjnych badaniach socjologicznych. W: Metody matematyczne w socjologii. Zaganienia wybrane. Pod redakcją Klemensa Szaniawskiego (pp. 7–34). Ossolineum.

3. Lissowski, G., Haman, J., & Jasiński, M. (2008). Podstawy statystyki dla socjologów (p. 670). Wydawnictwo Naukowe Scholar.

4. Steczkowski, J. (1995). Metoda reprezentacyjna w badaniach zjawisk ekonomiczno-społecznych. Wydaw. Naukowe PWN.

5. Thompson, S. K. (2012). Sampling. John Wiley & Sons.

Has in-depth knowledge of selected methods and techniques of social research, their limitations, specificity and areas of application

Is aware of the importance of a reflective and critical approach to the results of social research, analyses and research procedures

Knows how to plan and carry out complex qualitative and quantitative empirical research; is aware of the consequences of methodological choices

Can use theoretical categories and research methods in the description and analysis of social and cultural changes in modern societies, as well as their consequences

Can plan and carry out a social study using advanced quantitative and qualitative methods and techniques of social research

Can use a selected computer program for data analysis, including its advanced functions

Can prepare a presentation of a selected problem or study in Polish and in a foreign language

Can gather, find, synthesize and critically assess information about social sciences

Can argue a thesis using scientific evidence

Takes responsibility for planned and performed tasks

Written report containing analysis of sampling outcome. Sample is selected by participant from artificial population prepared by instructor.