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The Research Enterprise in Psychology. The Scientific Method: Terminology Operational definitions are used to clarify precisely what is meant by each.

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Presentation on theme: "The Research Enterprise in Psychology. The Scientific Method: Terminology Operational definitions are used to clarify precisely what is meant by each."— Presentation transcript:

1 The Research Enterprise in Psychology



4 The Scientific Method: Terminology Operational definitions are used to clarify precisely what is meant by each variable Participants or subjects are the organisms whose behavior is systematically observed in a study Data collection techniques allow for empirical observation and measurement Statistics are used to analyze data and decide whether hypotheses were supported Findings are shared through reports at scientific meetings and in scientific journals – periodicals that publish technical and scholarly material –Advantages of the scientific method: clarity of communication and relative intolerance of error Research methods: general strategies for conducting scientific studies


6 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

7 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 As this example shows, when two independent variables are manipulated in a single experiment, the researcher has to compare four groups of subjects (or conditions) instead of the usual two. The main advantage of this procedure is that it allows an experimenter to see whether two variables interact.

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

12 Descriptive/Correlational Methods: Looking for Links 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


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

15 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?

16 Describing Data A meaningful description of data is important in research. Misrepresentation may lead to incorrect conclusions.


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 Measures of Variation Range: The difference between the highest and lowest scores in a distribution. Standard Deviation: A computed measure of how much scores vary around the mean.

21 Standard Deviation

22 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


24 Correlation: Prediction, Not Causation Higher correlation coefficients = increased ability to predict one variable based on the other –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

25 If variables X and Y are correlated, does X cause Y, does Y cause X, or does some hidden third variable, Z, account for the changes in both X and Y?

26 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

27 Evaluating Research: Methodological Pitfalls Sampling bias Placebo effects Distortions in self-report data: –Social desirability bias –Response set Experimenter bias –the double-blind solution


29 Ethics in Psychological Research: Do the Ends Justify the Means? The 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


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