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This unit explores the various research methods used in psychology, including operational definitions, variables, data analysis, naturalistic observation, case studies, surveys, correlational studies, experiments, and statistical analysis.
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Language of Psychological Research • Operational Definition: A statement that defines the exact operations or methods used in research. EX: Using rats and a maze, I will attempt to assess the rat’s ability to learn patterns using food as a motivator. • Variable: A factor or characteristic that is manipulated or measured in research. -The type of food or the maze • Data: Numbers that represent research findings and provide the basis for research conclusions -The rats in the control group improved their overall time by 44%.
Theories??? • A theory is a general idea about the relationship of two or more variables. • We do research to try and prove theories that are created • As such theories must often be modified to fit the data collected through research.
Research Method: Naturalistic Observation • Naturalistic Observation: The process of watching without interfering as a phenomenon occurs in the natural environment. -The key is “without interfering” -EX: watching how children interact on a playground
Research Method: Case Study • Case Study: The intensive examination of some phenomenon in a particular individual, group or situation-Usually used for uncommon phenomenon -EX: Phinneas Gage: Gage, who was a construction foreman, suffered severe injury when a tamping iron went through his skull and his frontal lobe. While he survived, his personality was completely changed. This led doctors to question how traumatic brain injuries effected personality.
Research Method: Surveys • Survey: A research method that involves giving people questions or special interviews designed to collect descriptions of their attitudes, beliefs, intentions, or opinions -EX: Marketing Survey
Research Method: Correlational Studies • Correlational Studies: Examine the relationship between variables in order to analyze trends in data, to test predictions, to evaluate theories, and to suggest new hypotheses. EX: Why are there more shark attacks in summer than in winter?
Research Method: Experiment • Experiment: A situation in which the researcher manipulates one variable and then observes the effect of that manipulation on another variable, while holding all other variables constant EX: How does an increase in temperature in class effect the behavior of 3rd grade students?
People Involved in an Experiment: • Experimental Group: The group that receives the experimental treatment • Control Group: The group that receives no treatment or provides some other baseline against which to compare the performance or response of the experimental group
Variables in an Experiment: • Independent Variable: The variable manipulated by the researcher in an experiment • Dependent Variable: The factor effected by the independent variable • Confounding Variable: Any variable that effects the dependent variable that may or may not be accounted for • Random Variable: A confounding variable in which controlled or uncontrollable factors effect the independent variable
Creating Groups in an Experiment: • Random Assignment: A procedure by which people in an experiment group are placed into even groups by some random method • Double Blind Assignment: A method of placing people into experimental groups where the people involved and the experimenter are unaware of who is in a group • Experimenter Bias: A process by which an experimenter either willingly or unwillingly places people based on some biased factor. This creates a confounding variable.
Sampling in an Experiment: • Sampling: The process by which people are selected to participate in research an reflect the group the researcher wishes to study • Representative Sample: A group of research participants whose characteristics fairly reflect the characteristics from which they were selected • Random Sample: a group of research participants selected from a population whose members all had an equal chance of being selected • Biased Sample: When a researcher uses some type of bias when selecting participants. This can invalidate the research.
Types of Statistics in Psychology: • Descriptive Statistics: Numbers that describe and summarize a set of research data • Inferential Statistics: A set of mathematical procedures that help researchers infer what their data might mean
Types of Descriptive Statistics: • Mean: Describes the central tendencies of a set of scores using the average score • Median: Describes the central tendencies of a set of scores using the number that is half way between smallest and largest number • Mode: Describes the central tendencies of a set of scores by identifying the number that is most frequently collected in research • Range: A measure of variability that expresses the difference between the highest and lowest numbers in a set of data. • Standard Deviation: • Correlation: • Correlation Coefficient:
Types of Descriptive Statistics: • Standard Deviation: A measure of variability that is the average of difference between each score and the mean of the data set • Correlation: In research, the degree to which one variable is related to another • Correlation Coefficient: A statistic, r, that summarizes the strength and direction of a relationship between 2 variables
Graphs for Correlational Coefficients: The higher the number, the higher the relationship between variables.
Types of Inferential Statistics: • Statistical Significance: A term used to describe research results when the outcome of a test indicates that the probability of those results occurring by chance is small.
Practice FRQ: Outline for Tomorrow!!! • 1. Adapted from M. M. Duguid and J. A. Goncalo, Living Large: The Powerful Overestimate Their Own Height. In a study of power and self-image, participants were not told the true purpose of the study; instead, they believed they were participating in a business simulation. Researchers randomly assigned participants to a highpower (n = 44) or low-power (n = 44) condition. In the high-power condition, participants recalled a time when they had power over others, and in the low-power condition, they recalled a time when others had power over them. Participants were asked to adjust the height (in centimeters) of an electronic graphical image (an avatar) of themselves to reflect their personal appearance. Results indicated a statistically significant difference in participants’ perceptions of their own height across the two conditions. Participants in the high-power condition created taller self-images (mean = 6.0, standard deviation = 1.5) than participants in the low-power condition (mean = 4.0, standard deviation = 1.0). • Describe the levels of the independent variable. • Describe how the researchers measured the dependent variable. • Create a bar graph illustrating the results of the study. Correctly label each axis. • Explain why the researchers can conclude that there is a cause-and-effect relationship between the independent and dependent variables. • Explain what statistical significance means in the context of the study. • Explain why debriefing would be necessary in the study.