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## Study Guide 1

by: Summer Stevens

9

1

3

# Study Guide 1 PSYC 204

Summer Stevens
Texas A&M

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Yay statistics
COURSE
Experimental Psychology
PROF.
Dr. Winfred Arthur
TYPE
Class Notes
PAGES
3
WORDS
CONCEPTS
Statistics
KARMA
25 ?

## Popular in Psychology (PSYC)

This 3 page Class Notes was uploaded by Summer Stevens on Saturday August 13, 2016. The Class Notes belongs to PSYC 204 at Texas A&M University taught by Dr. Winfred Arthur in Fall 2016. Since its upload, it has received 9 views. For similar materials see Experimental Psychology in Psychology (PSYC) at Texas A&M University.

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### What is Karma?

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Date Created: 08/13/16
Study Guide In addition to practice, practice, practice…Here’s a list of the topics we’ve covered so far that will appear on the first test to help you organize your studying. It is not meant to be exhaustive but to give you a handy list of the main points we’ve talked about. Chapter 1 Defining Statistics Goals of science and how statistics help achieve those Descriptive statistics Inferential statistics Samples Populations Variable Data Continuous Vs. Categorical Data Chapter 2 Central Tendency Mean Median Mode When to use which measure of central tendency Influence of extreme values on each? Chapter 3 Variability Why is it important Measures of variability Range Standard Deviation Variance Identifying Extreme Values Chapter 4 Journal article sections (material covered in lab) Histograms Distinguishing distributions from each other and describing what that means Central tendency Variability Skewness Kurtosis Bar graphs vs histograms Misleading graphs ** You will be expected to APPLY what you know to pictures and/or data so be sure you really understand what these concepts mean—simple memorization will not cut it*** Chapter 5: correlations What are correlations and when do you use them? Scatterplots Strength Direction Limitations of the correlation coefficient Computing a correlation coefficient Reporting correlations Correlation Matrix 2 R Correlation vs. causation Chapter 6 Measures Measurement Scales Independent Variables vs. Dependent Variables Observed vs. true scores Error Score Reliability Test-Retest Parallel Forms Internal Consistency/Cronbach’s Alpha Inter-rater Validity Content Validity Criterion Concurrent Predictive Construct Convergent Discriminant

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