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PSY302, Week 1 Notes

by: Emma Cochrane

PSY302, Week 1 Notes PSY302

Marketplace > University of Oregon > Psychlogy > PSY302 > PSY302 Week 1 Notes
Emma Cochrane
GPA 3.6
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About this Document

These notes cover class week 1
Statistical Meth Psych
Jordan Pennefather
Class Notes
Psychology, psy302, Statistics




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This 1 page Class Notes was uploaded by Emma Cochrane on Sunday April 3, 2016. The Class Notes belongs to PSY302 at University of Oregon taught by Jordan Pennefather in Winter 2016. Since its upload, it has received 31 views. For similar materials see Statistical Meth Psych in Psychlogy at University of Oregon.


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Date Created: 04/03/16
What are Statistics? Statistics: short for statistical procedures Uses of statistics used to organize and summarize information used to determine exactly what conclusions are justified based on the results that were obtained Goals of statistical procedures accurate and meaningful interpretation provide standardized procedures Population: any complete set of observations; the entire set of individuals, objects, or events a researcher wants to study. Vary in size, often quite large. ex: all UO undergrads ex: all students present for class Sample: a subset of observations from a population, used to infer what is true of the population ex: students in this class ex: 5 cards picked from a shuffled deck Variables and Data Variable: characteristic or condition that changes or has different values for different individuals Data (plural): measurements or observations of a variable Data set: a collection of measurements or observations A datum (singular): a single measurement or observation, commonly called a score or raw score Statistics and Parameters Samples have statistics statistic = numeric value that describes a sample Latin letters (M, s) Populations have parameters parameter = numeric value that describes a population Greek letters Descriptive Statistics Techniques to summarize and organize observations (data). Concerned with describing the actual data you have collected. numbers and visuals central tendency (mean, median, mode) and variability (range, standard deviation, variance) Examples: Distribution of statistics stress in this class Average number of traumatic events experienced Distribution of cards in a playing card deck % adults/children, males and females on board Inferential Statistics: Techniques that use data from a sample to generalize a population. Allows us to make conclusions that go beyond the data we have. Examples: From a sample of people polled, infer support for universal health care March 30 Statistics vs. Parameters statistics describe a sample parameters describe a population a sample statistic helps us to estimate a population parameter Constructs internal attributes or characteristics that cannot be directly observed useful for describing and explaining behavior Operational definitions identifies a measurement procedure for measuring an external behavior definition and measurement of a hypothetical construct Variables discrete variables: (ex: # siblings, major, biological sex) separate, indivisible categories no values can exist between two categories continuous variables: (ex. time, weight, height) infinite number of possible values between each point measured Sampling Error sample is never identical to population sampling error: the discrepancy, or amount of error, that exists between a sample statistic and the corresponding population parameter. Data Structures, Research Methods, and Statistics correlation method two variables for each subject in a group purpose is to determine whether there is a relationship between the variables ex: SAT score and first year college GPA, height and weight Comparing Graphs of Scores one variable defines the group (independent variable) scores are measured on second variable (dependent variable) Experimental Method goal of experimental method: demonstrate cause-and-effect relationship manipulation: level of one variable is determined by experimenter control rules out the influence of other variables participant variables environmental variables Variable Roles independent variable is deliberately manipulated by researcher dependent variable is allowed to vary and is observed quasi-independent variable is not manipulated and is used to define groups age, sex, etc. Measurement Scales (NOIR) Nominal (categories) Ordinal (in order) Interval (equal intervals) Ratio


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