Textbook Notes (368,098)
Psychology (9,695)
PSYB01H3 (581)
Nussbaum D (52)
Chapter 10

# Chapter 10 - Quantitative Data Analysis

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Department
Psychology
Course
PSYB01H3
Professor
Nussbaum D
Semester
Fall

Description
Chapter 10Quantitative Data AnalysisDoes Spending Money On Others Promote HappinessAccording to a March 008 article social psychologist Elizabeth Dunn and colleagues found an interesting association bw increased happiness and spending money on othersThey performed 3 different types of research a crosssectional national representative survey longitudinal field study and experimental laboratory investigationThe researcher reported statistics that supported their hypothesis that spending money on other people has moreimpact on happiness than spending money on oneselfProvides platform for us to introduce several common statistics used in psych Research 60 participants rate their happiness in morning and then we give each participant an envelope of 5 or 20which they need to spend 500PM randomly assign participants to personal spending condition for themselves or prosocial spending conditionon others2 ind Variables each w 2 levels amount of money given and spending 15 participants in each groupInferential statistics are used to estimate characteristics of a population form those we found in random sample of that population can be used for another purpose to test hypotheses about the relationship bw variablesHow confident can we be that the effect we observed was not simply due to chanceStatistical Approach Levels of Measurement Matters There are 4 levels of measurement nominal ordinal interval and ratioIn Dunn example indp Variable of spending personal vs presocial reflects a nominal scale of measurement They are categorical variable where participants are assigned to spend on themselves or others The dep Variable of happiness asks participants to rate their happiness on 1to10 scale using an ordinal scale involves minimal arithmetic distinctions y At interval and ratio levels of measurement that the value of variable reflect actual numbers on scale w fixed interval y Ratio and interval measures can be analyzed w same statistical procedurelevel of variables are important factors to consider when designing experiments and other types of research and where planning statistical analyses of resulting dataUnivariate DistributionsBoth frequency distributions and graphs are used to describe the distributions or variables 1 at a timeFrequency Distributions Frequency distributionof cases andor theof cases who receive each possible score on a variableConstruction and reading frequency distribution for variables w few values is not difficult Political ideology was measured with a question having 7 response choices resulting in longer but still relatively simple frequency distributionMany frequency distgraphs require grouping of some values after data are collected there are 2 reasons for grouping y There are 1520 values to begin w a number too large to be displayed in an easily readable table y The dist Of variable will be clearer or more meaningful if some of values are combinedOnce we decide group valuescategories we have to be sure that we dont distort the disty Categories should be logically defensible and preserve the distributions shape y Categories should be mutually exclusive and exhaustive so that every case should be classifiable in one and only 1 category
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