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# PSCH 343; Statistical Methods In Behavior Science PSCH 343

Marketplace > University of Illinois at Chicago > Psychlogy > PSCH 343 > PSCH 343 Statistical Methods In Behavior Science
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UIC
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These notes cover the first week of notes from class.
COURSE
Statistics Methods In Behavioral Science
PROF.
Liana Peter-Hagene
TYPE
Class Notes
PAGES
8
WORDS
CONCEPTS
Statistics, Psychology
KARMA
25 ?

## Popular in Psychlogy

This 8 page Class Notes was uploaded by Katie on Sunday January 17, 2016. The Class Notes belongs to PSCH 343 at University of Illinois at Chicago taught by Liana Peter-Hagene in Spring 2016. Since its upload, it has received 32 views. For similar materials see Statistics Methods In Behavioral Science in Psychlogy at University of Illinois at Chicago.

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Date Created: 01/17/16
Instructor: Liana Peter-Hagene PSCH 343 Statistics Methods In Behavioral Science Week One Measuring Variables Descriptive statistics -Summarize and describe data -Examples: How many IPhone vs. Android users do we have in the class? *On average, how enthusiastic about statistics are people in this class? Inferential statistics Examples: 1. Is the enthusiasm for statistics experienced by people in this classroom representative of all UIC students? 2. A survey of 100 jurors shows more men than women voted guilty. Can we say these results represent jurors who were not in the study? Descriptive Statistics Variables: -We can measure variables by assigning them values Examples: -We can manipulate variables by assigning people to different conditions Instructor: Liana Peter-Hagene Values: Examples: 1. Variable: Age Values: 0 – 100 (and beyond…) 2. Variable: How emotional did you get when you watched The Notebook? Values: 0 (Not at all emotional) to 10 (Extremely emotional) 3. Variable: Were people interviewed on a sunny or a rainy day? Values: Sunny day or Rainy day Scores: An individual’s particular value on a variable Examples 1. Variable: age (0-100) Score: 68 2. Variable: How emotional did you get when you watched The Notebook? Score: 3 0, not at all, 10, very emotional 3. Variable: They were interviewed on a sunny day, sunny is their score Score: Sunny Measurement Instructor: Liana Peter-Hagene Measurement is how we assign values to variables. -You’ve all just come up with ways to measure variables! -We have some choice in how we measure variables -Right and wrong ways Example: Dr. Sob is studying emotional reactions to The Notebook How emotional were you? Scale from 0 (Not at all) to 10 (Extremely) Did you get emotional? Yes/No In general, the more specific the measurement the better TIP: you can always turn more specific into less specific, but not the other way around. Levels Of Measurement (Types Of Variables) 1. Nominal or Categorical Variables -Values and Categories If numbers are assigned, they are arbitrary. Numbers have no intrinsic meaning – there is no “more”, “less”, “higher” or “lower” Examples; -Favorite tea flavor- values are jasmine, chamomile 2. Ordinal or Rank Variables -Values are numerical and they represent relative rank, or order Examples: st nd rd 1.Place kitten cuteness contest – values are 1 , 2 , 3 , etc. 2. Preference for presidential candidates- values are 1 , st nd 2 , 3rd Instructor: Liana Peter-Hagene *Numbers have intrinsic meaning – there is more, less, higher, or lower st nd We can say 1 > 2 , but not by how much Numbers do not tell us how large these differences are 3. Interval Variables -Values are numerical -- they represent equal intervals (distance) between scores Examples: 1.Temps- values are degrees Fahrenheit We can say 25 degrees <26 degrees <27 degrees The distance between 25 and 26 is the same as distance between 26 and 27 2. Negative mood before lunch on a scale from 1- 7 *Numbers also tell us how large these differences are, because it is known or assumed the distance between successive values are equal. There is no true 0, or complete absence of the variable 4. Ratio Variables -Values are numerical -- they represent equal intervals (distance) between scores -There is a true or absolute zero, or complete absence of the variable Examples: 1.Number of times you check your phone in a day Theoretically, at least, the number could be 0 Instructor: Liana Peter-Hagene Checking the phone 10 times is twice as much as checking it 5 times 2. Number of correct questions on an IQ test *We can talk about differences in magnitude between values Usually count variables Order In A Group Of Numbers 1. What are the possible values of a specific variable? 2. How many people’s scores does each value represent? (How frequent is the value?) 3. What is the percentage of scores for each value? *Knowing the range of your possible scores, color of shirt, number of people on their phone How many people in this class wearing a black shirt, how many people in this class are wearing a pink shirt? Frequency Tables (Jury Example) -10 jurors indicated how angered they were by gruesome evidence presented in court (i.e., post-mortem photographs). 1 2 3 4 5 Not at all Extremely Their scores: 4 2 2 3 1 4 4 3 5 Frequency 1 2 2 4 1 Instructor: Liana Peter-Hagene Percentage 10% 20% 20% 40% 10% Frequency: Number of scores of that value Percentage: Out of all the scores, what percentage have that value? Total number of scores = 10 Histogram A graph that represents the information in a frequency table *Frequency is always on the Y-axis. Each number is on the X-axis Possible Test Question Review Sergio carried out a study to investigate whether consuming caffeine had an effect on peoples’ academic performance. He assigned 20 participants to drink 1 cup of coffee, 20 to drink 3 cups of coffee, and 20 to drink 5 cups. Participants were then given a stats exam and their percentage of correct answers was calculated. Bob got a 75% and Ted got a 90%. Identify the: IV How the IV was operationalized The values of the IV The dependent variable How the DV was operationalized The values of the DV The scores that are noted in the description Instructor: Liana Peter-Hagene Instructor: Liana Peter-Hagene

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