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Psych 280 Week one

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by: Melliso2

Psych 280 Week one PSY 280

SUNY Oswego
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About this Document

First week of getting to know basic materials
Analysis of Psychological Data
Paul Stewart (P)
Class Notes




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1 review
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"I'm really struggling in class and this study guide was freaking crucial. Really needed help, and Marissa delivered. Shoutout Marissa, I won't forget!"
Adonis Olson

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This 4 page Class Notes was uploaded by Melliso2 on Thursday January 28, 2016. The Class Notes belongs to PSY 280 at State University of New York at Oswego taught by Paul Stewart (P) in Fall 2015. Since its upload, it has received 25 views. For similar materials see Analysis of Psychological Data in Psychlogy at State University of New York at Oswego.

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Reviews for Psych 280 Week one

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I'm really struggling in class and this study guide was freaking crucial. Really needed help, and Marissa delivered. Shoutout Marissa, I won't forget!

-Adonis Olson


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Date Created: 01/28/16
What are “Data” and how are they used? We used treating depression to explain this concept. The types of treatments were using the medication Prozac and using Psychotherapy as the other.  In each treatment there were 10 subjects or participants.  A. Defining our variables: 1. Independent Variable­ this is the variable you manipulate and it has two or more  conditions. In our example types of treatment is our independent variable and our  conditions are Prozac and Psychotherapy. Independent variable will be seen as IV  throughout the rest of the notes. 2. Dependent Variable­ this is the variable that is affected by the IV. Our depended  variable is depression in the example. This variable will be seen as DV in the rest of  the notes. 3. Extraneous Variables­ these are all the variables that could affect your DV but you  are not studying it. This will be seen as EV. B. Measure our outcomes 1. Make a sum up of symptom checklist a. Some symptoms include; excessive sleeping, changes in living, suicidal thoughts C. Generalize Results­ an attempt to apply results to whole population, Ex. IV­ type of treatment [Prozac, Psychotherapy]  DV­ Depression [0­??]  How to decide on generalizing; could have a sampling error or one option truly is better. I. Summarizing Data How do we explain/summarize the data for any sample variable we study?  All variables are measured but have choices in how we measure them (scales)  Data for all variables can be organized a number of ways (tables, charts, etc...)  II. Four Scales of Measurement 1. Nominal; categorical, usually only a few categories, i.e. gender, nationality,  etc. 2. Ordinal; ranked data, data that is ordered first to last, i.e. place in a marathon  (1 ,2 ,3 , etc.)  3. Ratio; continuous, has an absolute zero point, i.e. height, weight, etc. 4. Internal; NO true absolute zero but is similar to ratio Ratio and Internal will be treat the same as a continuous variable. III. Examples of Scale Measurements Ex. Psych 280 Quiz grades (# of items correct on a 10 item quiz) Ratio Ordinal Nominal Interval 4 6 Fail ­2  9 2 Pass +3 Organizing Data 10 1 Pass +4 6 4 Pass 0 1. Simple frequency distributions 7 3 Pass +1 Frequency= ƒ n= number of score in sample 5 5 Fail ­1 ex. Sample of n=18 Psych 280 quiz scores 5, 7, 7, 8, 6, 9, 7, 8, 8, 9, 8, 10, 4, 7, 6, 7, 6, 5 Score ƒ Percent Percentile  With Ordinal and Nominal you  Simple ƒ data s Rank lose information on the individual  10 1 5.67% 100.00% point polygon 9 2 11.10% 94.30% people and scores because they  8 4 22.00% 83.20% 5 7 5 27.70% 61.20% could be far apart. 6 3 16.70% 33.50% With Interval it is relative to a  5 2 11.10% 16.70% ƒ 4 4 1 5.67% 5.60% passing score (6/10). It is also hard  3 2 1 to tell how well people did. Scores      0          4     5     6     7     8     9     10 Types of Distributions A. Normal Distribution­ the way variables are distributed µ­ myu mean of the whole population Major Characteristics  Symmetrical   Theoretical   Most common in the middle  ƒ declines as you move away from the middle  Far left and far right of distributions are called tails Nominal and Ordinal data  µ   Mean, median and mode are will not take a normal   all at the µ­ middle. distribution, Ratio or Interval will take on normal distribution with enough data Upper Tail 5th 100th       15th     Lower Tail Percentile rank 0   50        100   Frequency Low high        low        IQ Scores Non­Normal Distributions Kinds; Skewed (positive and negative), Bimodal, Rectangular  1. Skewed Distribution; Positively Skewed;  Mode     Median Ƒ       Mean Negatively Skewed;  Median   Mode Ƒ Mean 2. Bimodal;  Mode 1       Mode 2 Median and Mean 3. Rectangular;


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