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

5. 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

7. 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

8. 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

9. 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

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

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

12. 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

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

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: 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?

18. 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

20. 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

21. Figure 2.13 Positive and negative correlation

22. XX 2.14

23. 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

24. 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 result

25. Evaluating Research: Methodological Pitfalls
Sampling bias
Placebo effects – is not always uniform – cost factors and perceived pain
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.

27. Ethics in Psychological Research: Do the Ends Justify the Means?
Question of deception
The question of animal research
Controversy among psychologists and the public
Ethical standards for research: the American Psychological Association
Ensures both human and animal subjects are treated with dignity