Presentation is loading. Please wait.

Presentation is loading. Please wait.

Chapter 2: The Research Enterprise in Psychology.

Similar presentations

Presentation on theme: "Chapter 2: The Research Enterprise in Psychology."— Presentation transcript:

1 Chapter 2: The Research Enterprise in Psychology

2 The Scientific Approach: A Search for Laws Basic assumption: events are governed by some lawful order Goals: –Measurement and description –Understanding and prediction: psychologists form hypotheses about how variables interact. A hypothesis is a tentative statement about the relationship between 2 or more variables. Variables are the things that are observed or controlled in a study.

3 The Scientific Approach: A Search for Laws Goals (cont.): –Application and control: information gathered by scientists may be of some practical value in helping to solve problems

4 Figure 2.1 Theory construction

5 Figure 2.2 Flowchart of steps in a scientific investigation

6 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

7 The Scientific Method: Terminology 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

8 Table 2.1 Key Data Collection Techniques in Psychology

9 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 or controlled Dependent variable (DV) = variable affected by manipulation –How does X affect Y? –X = Independent Variable, and Y = Dependent Variable

10 Experimental and Control Groups: The Logic of the Scientific Method Experimental group: who receives a special treatment in regard to the independent variable Control group: who do not receive the special treatment –Manipulate independent variable for one group only –Resulting differences in the two groups must be due to the independent variable

11 Experimental and Control Groups: The Logic of the Scientific Method Extraneous and confounding variables –An extraneous variable is a variable, other than the independent variable, that may influence the dependent variable. –Confounding of variables occurs when participants in one group of subjects are inadvertently different in some way from participants in the other group, influencing outcome. Random assignment: Random assignment of subjects is used to control for confounding variables

12 Figure 2.5 The basic elements of an experiment

13 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

14 Figure 2.6 Manipulation of two independent variables in an experiment

15 Strengths and Weaknesses of Experimental Research Strengths: –conclusions about cause-and-effect can be drawn, No other research method has this power. Weaknesses: –artificial nature of experiments; researchers must create fake settings so that they have control over the environment. –ethical and practical issues: malnourish infants on purpose to see what the effects are on intelligence –Others cannot be done because of practical issues…no way to assign families to live in urban vs. rural areas to determine the effects of city vs. country living.

16 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

17 Figure 2.10 Comparison of major research methods

18 Descriptive/Correlational Methods: Looking for Relationships Advantages and Disadvantages: –Naturalistic Observation: ADV: less artificial DIS: hard to stay unobtrusive; can’t show cause and effect or why certain behaviors were observed –Case Studies: ADV: good for studying specific phenom.; can provide real examples to support some theories DIS: often leads to psy. Seeing what he/she wants; clinical samples often unrepresentative

19 Descriptive/Correlational Methods: Looking for Relationships Advantages and Disadvantages (cont.): –Survey: ADV: easy to gather data on hard to observe behaviors; easy way to collect a large amount of data DIS: data often unreliable due to intentional deception, social des. Bias, response sets, memory lapse, and wishful thinking

20 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

21 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?

22 Figure 2.11 Measures of central tendency

23 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

24 Figure 2.12 Variability and the standard deviation

25 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

26 Figure 2.14 Interpreting correlation coefficients

27 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

28 Figure 2.15 Three possible causal relationships between correlated variables

29 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

30 Evaluating Research: Methodological Pitfalls Sample: collection of subjects chosen for observation in a study Population: larger collection from which researchers want to generalize about Sampling bias: when a sample is not representative of the population Placebo effects: when a participant’s expectations lead them to experience some change even though they receive empty, fake, or ineffectual treatment

31 Evaluating Research: Methodological Pitfalls Distortions in self-report data: –Social desirability bias: a tendency to give socially approved answers to questions about oneself –Response set: a tendency to respond to questions in a particular way Experimenter bias: when a researcher’s expectations or preferences about the outcome of a study influence the results obtained –the double-blind solution

32 Figure 2.16 The relationship between the population and the sample

33 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

34 Figure 2.17 Ethics in research

35 Ethics in Psychological Research: Do the Ends Justify the Means? APA Guidelines: –1. Participation must be voluntary and based on informed consent and people must be able to withdraw –2. No exposure to harmful or dangerous procedures (psy. and phys) –3. Researchers must debrief ASAP –4. Right to privacy must not be violated –5. Harmful procedures on animals must be justified in terms of knowledge gained –6. Researchers must obtain permission from host institutions and review committees prior to starting a study.

Download ppt "Chapter 2: The Research Enterprise in Psychology."

Similar presentations

Ads by Google