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by: Anna Ballard

61

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3

# Statistics Wk 1 (Lectures 1&2) Notes Psy 202

Marketplace > University of Mississippi > Psychology > Psy 202 > Statistics Wk 1 Lectures 1 2 Notes
Anna Ballard
OleMiss
GPA 3.33

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These notes cover the introduction, types of studies, and types of sampling.
COURSE
Elementary Statistics
PROF.
Mervin R Matthew
TYPE
Class Notes
PAGES
3
WORDS
CONCEPTS
Statistics
KARMA
Free

## Popular in Psychology

This 3 page Class Notes was uploaded by Anna Ballard on Tuesday August 30, 2016. The Class Notes belongs to Psy 202 at University of Mississippi taught by Mervin R Matthew in Fall 2016. Since its upload, it has received 61 views. For similar materials see Elementary Statistics in Psychology at University of Mississippi.

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Date Created: 08/30/16
Lecture 1 8/24 Chapter 1 ––> Intro & Background ** Study tip: read before class and identify what’s hard then; ask questions in class! Why do people need a stats class? • Technical – some people may need to analyze data eventually  • ex: Florida Man http://floridamanandwoman.tumblr.com/ (Question: what in the world is  wrong with FL) ­ 1st question when you see a pattern: Does the pattern really exist?  Statistics helps us figure out if a pattern is real or an illusion ­ our human brains are trained to recognize patterns  The Nature of Reality • EVERYTHING is probabilistic –> in stats class especially, think in probabilities Science and Research in the Social Sciences *natural* sciences –> physics, biology etc… physical data social sciences –> psychology, sociology, etc… figuring out patterns of human behavior ­ more difficult  Observation —  create or modify  a theory Experiment  – perform  Theory — use  experiment and take  theory to make a  prediction WHERE STATS  note of new  Scientific Method observations COMES IN! Prediction  – design  experiment to test prediction  • Scientific Method cycle repeats/never ends ­ result of one experiment leads to another  We are working w/ Quantitative Research • Structured Data • Statistical Analysis • Objective Conclusions • Surveys; Experiments What is Research: Experiments • Random assignment –> researcher chooses who will be in which group  ­ gives researcher control to determine cause and effect ­ however, lose some external validity – cannot generalize results to real world  ­ ex: lab vs. home for sleep studies ­ sacrificing external validity is only sometimes ok when justifiable  Quasi­Experiments • Gain external validity but harder to determine cause and effect • No random assignment so no control over what causes changes Observational Studies • Opposite of experimental design ­ no control over anything  ­ lots of external validity but does NOT allow you to determine cause and effect Designing a Study ** Need to know which design you are using to determine what kind of analysis is needed • There is a variable you’re checking on in experiment or research  • Think about which populations you are generalizing to  ­ state­wide, country­wide, university­wide, etc.  Populations, Samples, and Sampling Technique • Population –> group you are interested in  • Subset –> group to represent your population  ­ looking at individual people will not help you figure out a cause/effect ­ looking at a representative group –> random variation  ­ draw a sample from the population –> subset  • If characteristics of sample are similar to population, sample is good  Simple Random Sample • If you want sample to representative of population everyone has an equal chance of being in  the sample  – 60% of population is blue so nearly 60% of sample should be blue Stratified Sampling • Smaller samples • More control of who goes into sample ­ recruiting your % to match population characteristics  ­ race, gender, etc  Cluster Sampling • Break large population that has subgroups into “clusters”  ­ sample within subgroups and pull into an overall sample Systematic Sampling • “Every 5th Person” –> mess up what sample looks like compared to population  ­ sample less representative of population  Deliberate/purposive sampling • If you have a lot of info on one subset, you pull people from the other subset to learn about  them as much as you know about the other Convenience Sampling • Using people that are easiest to recruit ­ not very representative of population  ­ people easiest to recruit may be systematically different than general public –> makes it hard  to generalize

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