Transcript Research
Chapter 2 The Research Enterprise in Psychology – 8th Edition The Scientific Approach: A Search for Laws Empiricism 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 Table of Contents Table of Contents Figure 2.2 Five steps of the Scientific Method Table of Contents 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 Table of Contents Table of Contents Peer Review of Scientific Articles The process of publishing scientific studies allows other experts to evaluate and critique new research findings. They carefully evaluate each study’s methods, statistical analyses, and conclusions, as well as its contribution to knowledge and theory. The purpose of the peer review process is to ensure that journals publish reliable findings based on high-quality research. Table of Contents Figure 2.4 The peer review process for journal submissions. Table of Contents 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 Table of Contents 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 Table of Contents Youmans and Jee ( 2007) Fudging the Numbers IV: Candy condition DV: Nine question evaluation of instruction form Overall rating scores Results: Significant difference in overall rating Questions? Other effects and limitations Table of Contents Figure 2.6 The basic elements of an experiment Table of Contents 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 Table of Contents Figure 2.7 Manipulation of two independent variables in an experiment Table of Contents 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 Table of Contents Descriptive/Correlational Methods: Looking for Relationships Methods used when a researcher cannot manipulate the variables under study • Naturalistic observation – Table 2.2, Levine & Norenzayan (1999) – ranking of pace of life in 31 cultures • Case studies • Surveys – Allow researchers to describe patterns of behavior and discover links or associations between variables but cannot imply causation Table of Contents Figure 2.10 Sample from a case study – a descriptive research method Table of Contents XXXXXX Table of Contents 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 Table of Contents 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? Table of Contents XX 2.11 Table of Contents 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 Table of Contents XX 2.12 Table of Contents 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 Table of Contents Figure 2.13 Positive and negative correlation Table of Contents XX 2.14 Table of Contents 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 Table of Contents XX 2.15 Table of Contents 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 resultS Table of Contents 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. Table of Contents XX 2.16 Table of Contents The Internet and Psychological Research Internet-mediated research refers to studies in which data collection occurs over the web. Possible Advantages – Samples that are much larger and much more diverse than the samples typically used in laboratory research – Have the potential to yield more diverse and representative samples Potential Disadvantages – Sampling bias resulting from self-selection may be a more troublesome issue in Internet-mediated research • Web users tend to be younger, brighter, and more affluent than nonusers – Data are collected under far less controlled conditions than in traditional studies Table of Contents Ethics in Psychological Research: Do the Ends Justify the Means? Tuskegee Syphilis Study: http://www.cdc.gov/tuskegee/timeline.htm http://www.tuskegee.edu/global/story.asp?s=1207598 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 Table of Contents XX 2.17 Table of Contents Using databases to access research articles PsychINFO – psychological literature 1887present To access at UNA http://www.una.edu/library Table of Contents Research Issues – Critical Thinking Use of anecdotal evidence in psychology – “I have a friend who…” p.74 – 75 Urban legends? http://www.snopes.com Table of Contents