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PSY 211

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Study Guide for chapters 1-2. Concise notes and formulas for the test. Good luck!
Elem Statistics Business
Andre Souza
Study Guide
Psychology, Statistics
50 ?




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This 3 page Study Guide was uploaded by KhloNotes on Monday September 5, 2016. The Study Guide belongs to Psych 2110 at University of Alabama - Tuscaloosa taught by Andre Souza in Fall 2016. Since its upload, it has received 19 views. For similar materials see Elem Statistics Business in Psychology (PSYC) at University of Alabama - Tuscaloosa.

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Date Created: 09/05/16
From 211 Elementary Statistical Methods (Psychology) ; Professor Souza ; Aron: Statistics  for Psychology, 6e     Vocab to Know:  ○ Statistics ​= Science of learning from data and of measuring, controlling, and  communicating u ​ ncertainty   ○ Values​ = possible number or category that a score can have; each variable has a  score  ○ Variables​ = characteristic that can have different values; what is being measured   ○ Scores​ = the actual value chosen   ○ Outliers​ = extreme observation that falls far from the other data, thus causes  exaggerated estimates, multiple explanations, and instability  ○ Population​ = entire group of people to which a researcher intends the results of a  study to apply  ○ Sample​ = scores of the particular group of people studied, usually considered to  be representative of the scores in some larger population   ○ Central Tendency = ​the typical observation for a given variable        Descriptive Statistics​ = procedures for summarizing a group of scores or otherwise making  them more understandable   Ex: The average age of the class is 18.5    Inferential Statistics​ = procedures for drawing conclusion based on the scores collected in a  research study but going beyond them; creates an educated guess for studies where it is  impossible to question the entire population    Ex: The average of all college classes is 18.5     Discrete Variable​ = variable that has specific values and that cannot have values between these  specific values   Explanation: Whole numbers instead of fractions or decimals     Continuous Variable ​= variable for which, in theory, there are an infinite number of values  between any two values   Ex: Travel time can be 5.5 hours or 5.567 hours.      Categorical Variable (Nominal Variable)​ = variable with values that are categories (names  rather than numbers); listing of categories and count of frequency   Ex: Survey to find most popular cell phone brand     Numeric Variable (Quantitative Variable)​ = variable whose values are numbers as opposed to  a nominal variable; can be sorted into a set of intervals divided by a measurement scale     Three Types of Numeric Variables:   1. Equal­interval = variable in which the numbers stand for approximately  equal amounts of what is being measured   2. Ratio Scale = variable measured on a ratio scale if it has an absolute zero  point, meaning that the value of zero on the variable indicates a complete  absence of the variable   3. Rank Order (Ordinal Variable) = numeric variable in which he values are  ranks      Frequency Distribution​ = pattern of frequencies over the various values  Ex: frequency table, histogram, or frequency polygon      Relative Frequency​ = proportion or percentage of observations that fall into that category   Equation: Frequency/Total = Proportion x 100 = %   Note: All proportions should add up to 1. All percentages should add up to 100%.     Formulas to Know:   ○ Arithmetic Mean = ​Formula: x̄  = (Σx)/n; Sensitive to outliers    ○ Properties of Mean = ​Formula: Σ(xi ­ x̄  ) = 0; Best estimate for the value of a  group of numbers   n ○ Geometric Mean = F ​ ormula​: x =  Πx  ; ​ Good for numbers that are not  independent of each other    ○ Median = ​Middle value in the dataset; ​Formula:​ Arrange values low to high and  cross outside numbers off  until you reach the middle term OR take number of  terms and add by 1 then divide by 2, ​Not sensitive to outliers    ○ Mode = ​frequency; ​Can be used for categorical and numerical variables    ○ Range = F ​ ormula: Z (xi ­ x) / n   ​ ​ ̄ ○ Residuals = Σ |  xi − x ̄|  or  ​ Σ (​ xi ­ x)  to get rid of negatives     Variance    2 ­ Formula:  Σ (xi − x)̄    n ­ Computational Formula:  Σ x   − (Σx)  ÷ n  ­ Measured in squared units     Degrees of Freedom   ­ “n­1”   ­ Allows us to make inference w/ room for error   2 ​ ­ ​ est requires  Σ (xi − x)̄  for variance   n − 1    ​Squared Deviation   Σ (xi − x)̄  ​ ­ Formula:  √ n − 1    Σ x   − (Σx)  ÷ n  ​ ­ Computational Formula:  √           


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