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Chapter 2

Chapter 2. Research Methods. The Scientific Approach: A Search for Laws. Empiricism: testing hypothesis Basic assumption: events are governed by some lawful order Goals: Measurement and description Understanding and prediction Application and control

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Chapter 2

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  1. Chapter 2 Research Methods

  2. The Scientific Approach: A Search for Laws • Empiricism: testing hypothesis • Basic assumption: events are governed by some lawful order • Goals: • Measurement and description • Understanding and prediction • Application and control • Goal of theory testing in science: refutation not proving – Karl Popper

  3. What is Experimental Research? • Explores cause and effect relationships • Has control and experimental groups • Laboratory experiments are good at controlling variables. Implementing school uniforms causes Less violence in school

  4. Steps in Designing an Experiment • Hypothesis • Design Study: • Pick Population: Random Selection then Random Assignment. • Operationalize the Variables • Identify Independent and Dependent Variables. • Look for Extraneous Variables • Type of Experiment: Blind, Double Blind etc.. • Gather Data • Analyze Results • Publish

  5. Experimental Research: Looking for Causes • Experiment = manipulation of one variable under controlled conditions so that resulting changes in another variable can be observed • Detection of cause-and-effect relationships • Independent variable (IV) = variable manipulated • Dependent variable (DV) = variable affected by manipulation • How does X affect Y? • X= Independent Variable, and Y= Dependent Variable

  6. Experimental and Control Groups: The Logic of the Scientific Method • Experimental group – subjects who receive some special treatment in regard to the independent variable • Control group – similar subjects who do not receive the special treatment • Logic: • Two groups alike in all respects (random assignment) • Manipulate independent variable for one group only • Resulting differences in the two groups must be due to the independent variable • Extraneous and confounding variables

  7. Experimental Designs: Variations • Expose a single group to two different conditions • Reduces extraneous variables • Manipulate more than one independent variable • Allows for study of interactions between variables • Use more than one dependent variable • Obtains a more complete picture of effect of the independent variable

  8. Figure 2.7 Manipulation of two independent variables in an experiment

  9. Strengths and Weaknesses of Experimental Research • Strengths: • conclusions about cause-and-effect can be drawn • Probabilistic causality • Weaknesses: • artificial nature of experiments • ethical and practical issues

  10. Descriptive/Correlational Methods: Looking for Relationships • Methods used when a researcher cannot manipulate the variables under study • Naturalistic observation • Case studies • Surveys • Allow researchers to describe patterns of behavior and discover links or associations between variables but cannot imply causation

  11. Figure 2.9 Sample from a case study – a descriptive research method

  12. Statistics and Research: Drawing Conclusions • Statistics – using mathematics to organize, summarize, and interpret numerical data • Descriptive statistics: organizing and summarizing data • Inferential statistics: interpreting data and drawing conclusions – use of probability

  13. Descriptive Statistics: Measures of Central Tendency • Measures of central tendency = typical or average score in a distribution • Mean: arithmetic average of scores • Median: score falling in the exact center • Mode: most frequently occurring score • Which most accurately depicts the typical?

  14. Statistics and Research: Drawing Conclusions • Statistics – using mathematics to organize, summarize, and interpret numerical data • Descriptive statistics: organizing and summarizing data • Inferential statistics: interpreting data and drawing conclusions – use of probability

  15. Statistics and Research: Drawing Conclusions • Statistics – using mathematics to organize, summarize, and interpret numerical data • Descriptive statistics: organizing and summarizing data • Inferential statistics: interpreting data and drawing conclusions – use of probability

  16. Descriptive Statistics: Variability • Variability = how much scores vary from each other and from the mean • Standard deviation = numerical depiction of variability • High variability in data set = high standard deviation • Low variability in data set = low standard deviation

  17. Descriptive Statistics: Correlation • When two variables are related to each other, they are correlated • Correlation = numerical index of degree of relationship • Correlation expressed as a number between 0 and 1 • Can be positive or negative • Numbers closer to 1 (+ or -) indicate stronger relationship

  18. Figure 2.13 Positive and negative correlation

  19. XX 2.14

  20. Correlation: Prediction, Not Causation • Higher correlation coefficients = increased ability to predict one variable based on the other Example: SAT/ACT scores moderately correlated with first year college GPA • 2 variables may be highly correlated, but not causally related • Foot size and vocabulary positively correlated • Do larger feet cause larger vocabularies? • The third variable problem

  21. Inferential Statistics: Interpreting Data and Drawing Conclusions • Hypothesis testing: do observed findings support the hypotheses? • Are findings real or due to chance? • Statistical significance = when the probability that the observed findings are due to chance is very low • Very low = less than 5 chances in 100/ .05 level • Other factors might account for the resultS

  22. Evaluating Research: Methodological Pitfalls • Sampling bias • Placebo effects – is not always uniform – cost factors and perceived pain http://www.youtube.com/watch?v=yfRVCaA5o18 • Distortions in self-report data: • Social desirability bias • Response set • Experimenter bias • the double-blind solution • Research protocol of clinical trial for drugs – FDA in U.S.

  23. Ethics in Psychological Research: Do the Ends Justify the Means? • Question of deception http://www.youtube.com/watch?v=KPgpRw9tiuM&feature=relmfu • The question of animal research • Controversy among psychologists and the public http://www.youtube.com/watch?v=l0QXUHeGeOc • Ethical standards for research: the American Psychological Association • Ensures both human and animal subjects are treated with dignity

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