Research Method and Design
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Explains the different portions of an APA style joural article including the purpose of the section and the information that can be found in that section
Items Below this line are lectures from the Fall 2010 semester
Elements making up scientific thinking such as determinism, empiricism, replication, data driven, empirical vs nonempirical questions. Concluded with categories of research including descriptive, relational, experimental, basic vs applied, field vs laboratory.
Discusses the fundamental principles of science. Mentions determinism again, discusses empiricism and especially operational definitions as well as arguments as to why operationalizing is a humanizing force in science.
Core elements of scientific research including theory and theory-driven observations, hypotheses, falsifiability, replication. Components of a good hypothesis including parsimony and coherence. Independent, dependent and extraneous variables.
Types of research literature, popular press and research articles, sections of a research article, research article databases, parts of the research article including abstract, introduction, methods, results and discussion
Measures of central tendency including mode, median and mean. Discussion included strengths and weaknesses of each measure. Also discussed how the mean is influenced by extreme scores leading to skewed distributions and how to distinguish between positively and negatively skewed distributions.
Discusses the range, variance and standard deviation as measures of variability. Walked through an example of how to derive the standard deviation.
Z Scores (2.4 mb; 9:55 min)
Importance of z_scores. How to use z scores. How to computer z scores.
Introduction to inferential statistics including why they are necessary and the importance of BOTH central tendency and variability for making inferences about the general population.
Probability, null hypothesis testing including what constitutes a correct decision, a Type 1 error and a Type 2 error. Discussed p values, their meaning and interpretation and the relationship between p values, alpha and Type 1 errors. Also discussed how p value relates to statistical significance and to marginally significant p values.
Illustrative example of null hypothesis testing. Includes discussion about how assumptions regarding the characteristics of the normal curve allow us to make inferences from a sample to the population. Finishes with an explanation of the relationship between alpha, beta, and power.
Discusses relationship between Type 2 errors, beta and power. Included in the discussion of power are the ways of increasing power and the advantages and disadvantages of each method. Concludes with a discussion of effect size, what it means and the relationship between power, effect size and sample size.
Description of correlational research and the situations in which it is used. How correlation can be used to examine the existence, strength and type of relationship might exist between variables but not whether any relationship is a causal relationship
Discussed how the correlation coefficient indicates whether a positive or negative relationship between variables and the strength of the relationship. Also discussed the relationship between the regrassion line and how data points clustered around the data line and central tendency and variability of the relationship. Discussed why correlation does not imply causation, the directionality problem, the third variable problem and problems with restricted range.
Random and systematic errors. For high reliability, it is important to make many observations, many times, across many situations. Finished with the discussion of inter-rater reliability.
Internal validity and threats to internal validity.
How to increase external validity including increasing mundane realism and experimental realism. Discussed face validity, content validity, criterion related validity and construct validity.
Control (5.0 mb; 20:55 min)
Discussed issues of control, comparison and manipulation in experimental design. Includes discussion of confounding variables.
Controlling subject variables through random assignment to condition and by using within subject designs. Discussed carryover effects, practice effects, fatigue effects and Latin square design.
Strengths and weaknesses of between and within subjects designs. Discussed control of subject variables such as demand characteristics. Includes discussion of the Clever Hans effect, good subject effects and subject biases.
Understanding the source of subject biases in order to control them. Discusses how subject expectations can affect a study.
Understanding and controlling for experimenter biases. Includes experimenter expectancy effect, single blind and double blind procedures.
Explains logic of Experimental Design. Includes correspondences between the methods of agreement and difference and the control and experimental conditions of an experiment. Concludes with discussion of preexperimental designs.
Posttest only conrol group design, pretest posttest control group design, Solomons Four Group design, multilevel or one way design.
Explaining factorial designs, terminology, main effects and interactions.
Uses of Small N Designs, terminology, guidelines, behavioral baseline and treatment phases of the design.
Discusses types of small n designs. ABA designs were not recorded due to mp3 recorder battery dying.
Muliple Baseline Designs and Changing criteria designs.
Discussion of Quasi-experimental designs including cross-sectional designs, longitudinal designs, interrupted time series designs and non-equivalent groups designs. Includes discussion of examples.
This work by Cynthia Sifonis is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License.