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Descriptive Research

Descriptive Research. This lecture ties into chapter 17 of Terre Blanche How do we create hypotheses ? Start with a rough idea of how the world is The more accurate the idea, the better the hypothesis Ideas are based on data Who is doing what, how often, how much

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Descriptive Research

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  1. Descriptive Research • This lecture ties into chapter 17 of Terre Blanche • How do we create hypotheses? • Start with a rough idea of how the world is • The more accurate the idea, the better the hypothesis • Ideas are based on data • Who is doing what, how often, how much • The collection of this plain “information” is a type of study

  2. Describing the world • Descriptive research aims to simply describe the population • Paint a picture by looking at a sample • Descriptive research collects data, but does not analyze it • Analysis will be made later when hypotheses are formed based on the data collected • “first step” in investigating something

  3. Example: The Kinsey Report • Kinsey was a part time marriage councellor in the 1950s • Felt he could give better advice if he knew what was happening sexually • Taboo topic, so no solid information was available – science would change that • Kinsey set out to “paint a picture” of sexual activity, scientifically • First with men, then with women

  4. Kinsey Pics Kinsey conducting an interview Kinsey Report – blues band

  5. Kinsey’s plan • Interview thousands of people about their sexul habits, compile a document with charts & graphs • To do this: • Recruited hundreds of assistants • Made them memorize a code so that the subject’s responses were kept confidential • Project took several years, published as a book

  6. More Kinsey Pics The IBM data sorter & Punch cards – high tech! Data collection – the code

  7. Some of Kinsey’s findings • 92% of men and 60% of women masturbate • 50% of men and 25% of women have engaged in extramarital sex • 37% of men and 13% of women have had at least one homosexual experience leading to orgasm • By age 35, almost 70% of men have had sex with a prostitute • 10% of men and women are primarily homosexual

  8. Overall: Kinsey’s results • General shock at the book • “polite society” labelled him a pervert • The information spawned a mass of useful consequences • STD epidemiological breakthroughs • Family councelling techniques (Masters & Johnson) • Social awareness & de-mystification of “deviant” practices • His findings now dated, but the tradition continues

  9. Analysis of Kinsey • Important aspects to note: • Large n (sample size) • Sampled across all sub-groups • Used quite precise measurements • Did not generate hypotheses • Presented information in various forms (graphically & textually)

  10. Descriptive designs • Very simple design: • O  X • No sub groups, everyone is measured on the same variables. • No interventions • All variables are independent

  11. Sampling for description • Most important: sample widely & deeply • Identify & capture all sub-groups • Careful sampling will ensure that results can be generalized • The sample must be able to describe the population well • The quality of sample directly affects the quality of descriptive research

  12. Kinsey’s sample • Used volunteers • Excludes certain people, but unavoidable • Stratified into groups • Ensures small groups are sampled • Large sample • Better generalization • Non-probabilistic methods when appropriate • Eg. Snowball sampling for gays

  13. Measurement • Variables need to be carefully decided on • Often a large number of variables • Operationalisation & measurement of variables is important • Poor reliability would lead to a “blurred” picture of the population • Poor validity would lead to a picture of the wrong thing

  14. Kinsey’s measurement • Precise, simple questions • “Have you ever had sex with a prostitute?” • Many variables • Didn’t know which were important, asked many • To get honest responses, built up careful rapport with subjects

  15. Results & Analysis • No data analysis (description) • Use descriptive statistics • Mean, Std. Deviation, percentages, etc. • Graphs • Histogram, line graphs, etc

  16. Summary: Descriptive Studies • Aim: describe some population • Ensuring validity: • Large n • Deep sample • Good measures • No DVs, no data analysis • Results presented using descriptive stats & charts

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