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Module 2 Week 1 Notes: Types of Studies & Data

by: Samantha Melton

Module 2 Week 1 Notes: Types of Studies & Data PSYC 301

Marketplace > University of Louisville > Psychlogy > PSYC 301 > Module 2 Week 1 Notes Types of Studies Data
Samantha Melton
U of L

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About this Document

These are notes taken while listening to the TED lecture recordings rather than the powerpoints he gives, and as such there is more material/explanations in my notes that the powerpoints alone do n...
Quantitative Statistics
Dr. Edlin
Class Notes
Statistics, Psychology, Excel, Math
25 ?




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This 2 page Class Notes was uploaded by Samantha Melton on Wednesday July 6, 2016. The Class Notes belongs to PSYC 301 at University of Louisville taught by Dr. Edlin in Summer 2016. Since its upload, it has received 3 views. For similar materials see Quantitative Statistics in Psychlogy at University of Louisville.


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Date Created: 07/06/16
Module 2­ Week 1 Variables: Variable­ property of an object/event that can take on different values - Continuous variables­ variables that can take on any value o quantitative data; any kind of number.  o Percentage Score on Exam o Number of food dish visits - Discrete variables­ can only take on a small set of possible values o Categorical data; frequency/count data (no number) o Letter grade on Exam o Sex/gender - BOTH Variables­  o Hungry Mice­ Number of food visits (continuous) vs. classify hungry or full  based on visits (discrete) o Age­ number of years (continuous) vs. adolescent, young adult, senior categories  (descrete) **** Almost any continuous variable can be “chopped up” into discrete categories. Use ranges  to divide into categories. - Type of variables determine what type of tests to use to.  - How we measure data = how we can analyze it. Dependent Variables­ response variables - Accident or No accident (Road Rage) // Discrete Variable Independent Variables­ explanatory/predictor variables - Anger inoculation/no anger inoculation (Road Rage) // Discrete Variable Types of Studies: Observational Studies­ researcher just watches, doesn’t manipulate any variables. Just takes  data and looks at it - Cant infer causality from observational studies, have to do an actual expiement o Icecream & Sharks Example  Third Variable Problem - Independent variable might influence dependent, or there may be a third variable  influencing both.. we don’t know, we don’t have any contorl - Hungry Mice Example - Facebook Study­ Collected Data & Observed it Causality Study­ Manipulation participants Third Variable Problem: - How to Eliminate: o Control­ manipulate independent variable & try to keep everything else constant o Random Assignment­ Use to equalize the things we cant control. randomly  assigning participants so each person has an equal chance of being in a condition,  because some things are impossible to keep constant.  Example: Can’t control GENDER or IQ Data Collection: Population­ Entire collection of events in which you are interested Sample­ Data collected from a subset of the population - If population = students in this PSYC 301 course…. Then a random sample of  students in this PSYC 301 course is a GOOD SAMPLE. - If population = students in ALL online courses… Then a random sample of students  enrolled in any online course is a GOOD SAMPLE. ****** Important to keep in mind what you’re looking at when using these terms, because one  person’s sample might be another person’s population Random Sampling­ Use for inferential statistics


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