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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
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
Steps in Designing an Experiment
1. Hypothesis
2. 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..
3. Gather Data
4. Analyze Results
5. Publish
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
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
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
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
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
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
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?
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
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
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
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
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.
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