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Psych 210, Week 1 - Ch.1 Notes

by: Eliza Gonzalez

Psych 210, Week 1 - Ch.1 Notes PSYC 210

Eliza Gonzalez
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About this Document

Complete, detailed notes on Ch.1
Statistical Principles of Psychological Research
Patrick Harrison
Class Notes
Statistics, Descriptive, inferential, measurements, Scales, variables, constants, real, Limits, summation, sigma




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This 4 page Class Notes was uploaded by Eliza Gonzalez on Sunday September 4, 2016. The Class Notes belongs to PSYC 210 at University of North Carolina - Chapel Hill taught by Patrick Harrison in Fall 2016. Since its upload, it has received 50 views. For similar materials see Statistical Principles of Psychological Research in Psychology (PSYC) at University of North Carolina - Chapel Hill.


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Date Created: 09/04/16
Psych Statistics – Book Notes Chapter 1  Statistics consists of a set of procedures for organizing, describing, and interpreting quantitative  information and for drawing conclusions/making inferences about what is generally true for an  entire group. Scientific Use  Almost all numerical information, or data, in the social/behavioral sciences contain variability. o Variability­ refers to the fact that the scores/measurement values obtained in a study  differ from one another, even when all subjects are assessed under the same  circumstances.  1) Individual Differences­ The units (usually people) are rarely identical to one  another  2) Measurement Error­ scientists cannot always measure the behavior they  wish to study as accurately as they would like.  This error favors some more than others, adding to variability.  3) Unreliability­ a single unit (person, animal) usually will not respond exactly  the same way on two different occasions. Descriptive & Inferential Statistics   Statistics­ the study of methods for describing and interpreting quantitative information, called  data. o Descriptive Statistics­ refers to procedures for organizing, summarizing, and describing  data.  Ex: batting averages, visuals, degrees of relationships  o    Inferential Statistics­ includes methods for making inferences about a larger group of  individuals on the basis of data actually collected on a much smaller group.   Does is more general than did. Measurement  Measurement­ the orderly assignment of a numerical value to a characteristic  Scale of Measurement­ the ordered set of possible numbers that may be obtained by the  measurement process o Ex: the possible values of a tape measurer o Properties of Scales­   Rank Order­ lining people up tallest to shortest and assigning them a number 1,  2, and so on.  Categorization (rating)­ fitting people into 5 categories of tallness  When a scale has magnitude, one instance of the attribute being  measured can be judged greater, less, or equal to another instance. o Jane has a lv 8 aggression > Harry has a lv 5 aggression  When a scale has equal intervals, the magnitude of the attribute  represented by a unit of measurement on the scale is the same regardless  of where on the scale the unit falls. o Ex: 60in to 61in versus 57 to 58in is an equal interval WHILE  the number one basketball team may be WAY better than  number 2, and 2 being slightly better than 3 would not be.  An absolute zero point is a value indicating that nothing at all of the  attribute being measured exists. o Height measured in inches has an AZO. o In rank­order scale of height (i.e. first height = 1, second height  = 2, etc.) an absolute zero point does not exist. o Types of Scales­  Ratio Scale­ any scale of measurement that possesses magnitude, equal intervals,  and an absolute zero point.  Ex: Height in inches, weight in ounces/grams, time in minutes/seconds  Ratio Statements can be made – adult is 70in, child is 35in = adult is 2x  taller than child o Ratio statements can only be made when all 3 properties exist  Interval Scale­ possesses the properties of magnitude and equal intervals but not  an absolute zero point.  Ex: Temperature scales in Fahrenheit (or Celsius) o 0 degrees denotes an actual degree of temperature, not a lack of  one.  Ordinal Scale­ reflects only magnitude and does not possess equal intervals or an absolute zero point.  Ex: When ranking children in height (child 1 being rank 1, child 2 being  rank 2, etc.) magnitude is present but nothing more.  Nominal Scale­ results from the classification of items into mutually exclusive  groups that do not bear any magnitude relationships to one another.  Ex: Categorizing the Make of Car (i.e. Honda, Chevy, BMW), no make  is more or less than the make of another.  Because there is no magnitude it is not considered a scale, but simply  categories of a variable. Variables  Variable­ the general characteristic being measured on a set of people, objects, or events, the  members of which may take on different values. o Ex: Height, gender o Discrete vs Continuous Variables  Discrete Variable­ one that can assume only a countable number of values  between any two points  Ex: A basketball game score OR the number of children  no halves  Continuous Variable­ one that theoretically can assume an infinite number of  values between any two points on the measurement scale.  Ex: Weight; time  ** Discrete & Continuous Variables are almost always measured in discrete  scores.  Ex: Weight is rounded  Can also be measured with ratio, interval, or ordinal scales. o Ex: Intelligence tests use an ordinal scale.  Constant­ a quantity that does not change its value within a given context o Ex: Average height of children in one particular class; 3.1416... Real Limits  An actual discrete measurement of a continuous variable represents all those theoretical values  that would be rounded off to that particular score. o Ex: 33 seconds represents the theoretical scores between 32.5 and 33.5 seconds.  Lower Real Limit­ 32.5 – because anything lower would lead to a diff. score  Upper Real Limit­ 33.5 – because anything higher would lead to a diff. score o Real Limits of a number are those points falling one­half measurement unit about and/or  below that number.  Ex: Measured in 10  of a second  32.95 and 33.05  Ex: Measured in 100  of a second  32.995 and 33.005 Rounding 1. If the remaining decimal fraction is less than .5 units, drop the remaining decimal fraction. 2. If the remaining decimal fraction is .5 unit or greater, increase the preceding digit by 1. Summation Sign Notation for Scores and Summation o Capitalized letters (X) represent known variables.  Each X variable is distinguished with a subscript corresponding to the number of  the participant who made that score (i.e. 1, 2, 3, 4, 5).  Subscripts run from 1 to N o Lower case letters (k) represent unknown values of a constant. o X with subscript I  represents all the scores on Variable X (containing 5/5 scores)  Particular scores will still be represented by X1, X2, X3, etc. o Average  Σ X / N  Sigma Σ, represents the operation of summing  X represents the variables  N represents the total number of scores   i = 1 represents the limits of the summation  This equation reads: The summation (Σ) of all the X’s (Xi) from i=1 to N o If N were replaced with a number (i.e. 5) it would represent the  summation of the first 5 X’s beginning at 1. Operations with the Summation Sign o 1) The sum of a constant times a variable equals the constant times the sum of the  variable. If c is a constant and Xi is a variable.  5, 7, and 8 minute times. How many seconds?  Multiply the times (Xi) by 60seconds ( c ) or  Multiply the total number of minutes (Σ Xi) by 60 ( c ) o 2) The sum of a constant taken N times is N times the constant. If c is a constant.  c + c + c.. (N times) = Nc o 3) The summation of a sum of variables is the sum of each of these variable sums.  The summation (Σ) of Xi + Yi = Σ of Xi + Σ of Yi Important Distinctions 2   2 o Σ Χ  does not equal(Σ Χ) o Σ (XiYi) does not equal Σ (Xi + Yi) o (ΣXi) (ΣYi) does not equal Σ (XiYi)


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