Statistical Reasoning in Everyday Life
Statistical Reasoning in Everyday Life PSYC 2010 - 001
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This 2 page Class Notes was uploaded by Myrissa Webb on Monday August 29, 2016. The Class Notes belongs to PSYC 2010 - 001 at Auburn University taught by Jennifer Daniels in Fall 2016. Since its upload, it has received 7 views.
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Date Created: 08/29/16
Statistical Reasoning in Everyday Life Experimental Research Ethical Considerations Experimentation Exploring Cause and Effect Like other sciences, experimentation is the backbone of psychology research. Experiments isolates causes and their effects Many factors influence out behavior experiments (1) manipulate factors that interests us, while other factors are kept under (2) control Effects generated by manipulated factors isolate cause and effect relationships Evaluating Therapies 1 Double-blind procedure In evaluating drug therapies, patients, and experimenter's assistants should remain unaware of which patients had the real treatment and which patients had the placebo treatment Keep bias out of the equation 1 Random Assignment Assigning participants to experimental (writing about trauma) and control (writing about previous day) conditions by random assignment minimizes pre-existing differences between the two groups Independent Variables This is a factor manipulated by the experimenter. The effect of the independent variable is the focus of the study. Example: When examining the effects of writing about trauma upon stress, what is being written about is the independent variable Dependent Variable This is a factor that may change in response to an independent variable. In psychology, it is usually a behavior or a mental process "Did the independent variable have an effect?" Example: In our study on the effect of writing about trauma upon stress, stress is the dependent variable Confounding Variable A situation in which the independent variable is intertwined or mixed up with another, uncontrolled variable We cannot tell which variable is responsible for changes in the behavior of interest Operational Definition: A statement of the procedures used to define research variables Examples: Love, Intelligence, Health, Trust Comparing Research Methods Research Basic Purpose How What is Weaknesses Methods Conducted Manipulated Descriptive To observe and Do case Nothing No control of record behavior studies, variables; single surveys, or cases may be naturalistic misleading observations Correlationa To detect Compute Nothing Does not l naturally statistical specify cause occurring association, and effect relationships; sometimes to assess how among survey well one responses variable predicts another Experiment To explore Manipulate The Sometimes not al cause and one or more independent feasible; results effect factors; use variable(s) may not random generalize to assignment other contexts; no ethical to manipulate certain variables Statistical Reasoning in Everyday Life Doubt big, round undocumented numbers as they can be misleading and before long, becomes public misinformation Statistical Significance: The results are not due to change along; based only on numbers Clinical Significance: It makes a difference in our lives Just because it is statistically significant doesn’t mean it is clinically significant Example: They are testing a sleeping pill. They find out that people who took it slept on average 20 minutes longer than those who didn’t. Statistically this is significant because there is a numerical difference (20 mins). However, it was not clinically significant because 20 minutes more doesn’t actually make much of a difference to our sleep. Describing Data A meaningful description of data is important in research. Misrepresentation my lead to incorrect conclusions Ethical Conclusions Informed Consent: The person has to understand what they are agreeing to participate in Confidentiality: All data has to be confidential Debriefing: When the study is done they have to let them know what happened Deception: They have to go through the IRB (Institutional Review Board) to research. The benefits have to far outweigh the risks of deception Other Considerations Gender Bias Cultural & Ethic Bias Socioeconomic Bias Religion Bias And more Bias's
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