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26 Cards in this Set
- Front
- Back
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What is the scientific attitude
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Based on skepticism and humility. Analyze what is being said and consider what is not being said.
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What is a theory
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-Organized set of principles
-Helps simplify/order myriad facts about aspect of the world -Coherent explanation -Should allow testable predictions -should be supported by evidence |
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Difference between scientific law and theory
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Laws can describe but theories attempt to explain
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The steps in the scientific method
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1.Develop a theory
2. Generate a hypothesis (testable prediction) 3. Design a research study (select methodology) 4. Collect relevent information 5. Analyze data 6.Solicit peer reviews and report findings |
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Case study definition and pros and cons
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-In depth study of an individual
Pro: can be revealing and detailed Con: cannot determine cause of behaviour, limited reliability and precludes generalization |
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Survey definition, pros and cons
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-Peoples self reports to questionnaire or interview
Pro: Reveals patterns in large numbers of ppl, easy to administer and score, effects of extremes are mediated Con: cannot determine cause of behaviour, demand characteristic (response influenced by question) |
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Naturalistic observation definition, pros and cons
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-Recording behaviour in organisms natural environment
Pro: subjects unaffected by presence of researcher, describes behaviour in natural context Con: cannot determine cause of behaviour, loss of experimental control |
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Correlation as a method, pros and cons
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-Statistic that shows how two variables relate. Can be positive, negative or non existant.
Pro: May reveal relationships between variables, can generate future hypotheses Con: correlation does not imply causation |
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Components of experimentation
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-Independent variable: factor of interest manipulated by experimentor
-Dependent variable: factor measured by experimentor. -All extraneous factors held constant |
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Experiments look for differences between...
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Experimental group (receive manipulated level of independent variable) and control group (receive normal levels)
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Pros and cons of experiments
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Pro: allows for clear and concise conclusions
Con: unexpected/uncontrolled variables and some variables can not be manipulated (age and sex) |
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Hindsight bias pitfall
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events aren't obvious beforehand, but seem very predictable afterwards.
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Overconfidence pitfall
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confidence does not equal correctness
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conformation bias pitfall
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seeking evidence confirming your belilefs even to the exclusion of contradictory information.
Solution: replication of observations by others |
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Sampling bias pitfall
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Content of sample does not match population
Solution: do random sampling. |
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Placebo effect pitfall
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subjects expectations cause a change in dependent variable
Solution: compare treatment group with placebo group with control group |
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Experimentor bias pitfall
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reasearchers expectations influence dependent variable (or interpretation of results)
Solution: double blind study |
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Ethical guides for human testing
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-Minimal risk
-beneficial to participants and society -informed consent -limited deception -privacy / confidentiality -debriefed -care for vunreable pop's |
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Ethical guides for animal testing
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-research topic must be important
-minimized harm to animal -recieve best possible care -treated humanely |
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Descriptive statistics for central tendency
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-Mode: most common score
-Median: middle score -Mean: average of all the scores |
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Descriptive statistics for variability
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-Range: from highest to lowest
-Standard deviation: indicates spread of scores around mean -Normal curve: regular pattern of variability of human characteristics in the population |
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Graphical correlations
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-Scatterplot.
-Positive slope is positive correlation, negativve is negative and no slope is no correlation |
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Numerical correlation
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Correlation coefficient: index of degree of relationship between two variables
r=(+/-)(number between 0.00 and 1.00) |
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Problems with testing hypothesis
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-Cannot test entire population so use inferential statistics which allows for generalization
-Is difference significant. Fix it by stating confidence about conclusion |
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Null hypothesis
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Is the opposite of the hypothesis is negative or positive wording. Null hypothesis are made to be disproved.
ex: instead of ALL mice are green null would be NO mice are green |
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Implications of inferential statistics
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-Representative samples are better
-Less variability is preferable -Larger samples are better -Small differences may be significant but not important -average person vs average score of people. |
