10 Bivariate Analysis V2.1
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Transcript of 10 Bivariate Analysis V2.1
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Research Methods: Level 6Final Year Project Toolkit
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The story so far...
Developing research questions
Critical thinking and literature reviews
Research design Data collection methods
Resourcing
Collecting and coding data
Now...analysis!
The ResearchThe Research
ToolkitToolkit
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Bivariate analysis techniques for describingand exploring relationships between twovariables.
Explore everything? No! Choice over what todescribe and explore should be theory driven.
When examining causality:
Independent and dependent variables
Bivariate analysisBivariate analysis
Independentvariable (X)
DependentVariable(Y)
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Common technique for categorical variables(nominal & ordinal) is contingency tables or crosstabulation
Exploring variable responses by differentrespondent groups or exploring hypotheses aboutrelationships between two variables
Cross tabulations placing one variable in thecolumn and one in the row.
Convention is usually:
Column independent Row -de endent
variables:variables:
contingencycontingency
tablestables
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Cross tabulationsCross tabulations
How often do you go food shopping?
Gender
Count Male Female Total
Daily 40 55 95
Several times a week 56 58 114
Several times a month 20 36 56
Several times a year or less 5 2 7
Total 121 151 272
Example of a cross tabulation frequency of foodshopping by gender, count (n=272)
Column totals
(marginals)
Row totals(marginals)
Grand total
C b l i
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Cross tabulations:Cross tabulations:
columncolumnExample of a cross tabulation food shopping by gender,percentage (n=272)
Gender
Percentage Male Female
Daily 33.1 36.4Several times a week 46.3 38.4
Several times a month 16.5 23.8
Several times a year or less 4.1 1.3
Total 100.0 100.0
n = 121 151
C b l i
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Cross tabulations:Cross tabulations:
rowrowExample of a cross tabulation food shopping by gender,percentage (n=272)
Gender Total n
Percentage Male Female
Daily 42.1 57.9 100.0 95
Several times a week 49.1 50.9 100.0 114
Several times a month 35.7 64.3 100.0 56
Several times a year or less 71.4 28.6 100.0 7
Total 44.5 55.5 100.0 272
b l iC t b l ti
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Cross tabulations:Cross tabulations:
totaltotalExample of a cross tabulation food shopping by gender,percentage (n=272)
Gender
Percentage Male Female
Daily 14.7 20.2
Several times a week 20.6 21.3
Several times a month 7.4 13.2
Several times a year or less 1.8 0.7
Total 44.5 55.5
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Presenting crossPresenting cross
tabulationstabulations
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Further analysis with categorical variables:
Why does the relationship exist?
How are the variables associated?
Are there any other variables thatimpact on the relationship?
More analysis withMore analysis with
categorical datacategorical data
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Elaboration and spurious relationship analysis...
the extent to which a relationship is affected bythe introduction of other variable.
Is the relationship still exist and to what extentwhen another variable is introduced?
In example is the frequency of food shoppingaffected by the same degree when anothervariable such as employment status isintroduced?
ElaborationElaboration
analysisanalysis
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Mindful of spurious false relationships
Spurious when an association made betweentwo variables is not due to a direct cause-and-effect relationship due to a third known orunknown variable.
Elaboration analysis adding a 3rd variable :
allows more building of a more complexpicture of the data
allows consideration of possible spurious
relationships
SpuriousSpurious
relationshipsrelationships
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Example crossExample cross
tabulationtabulation Gender
Male Female Total
Employed full-time Daily count 10 20 30
% within gender 15.4 22.2 19.4
Several times a week count 36.0 40.0 76.0
% within gender 55.4 44.4 49.0
Several times a month count 15 30 45
% within gender 23.1 33.3 29.0
Several times a year or less count 4 0 4
% within gender 6.2 0.0 2.6
Total count 65 90 155
% within gender 100.0 100.0 100.0
Employed part-time Daily count 30 35 65
% within gender 53.6 57.4 55.6
Several times a week count 20 18 38
% within gender 35.7 29.5 32.5
Several times a month count 5 6 11
% within gender 8.9 9.8 9.4
Several times a year or less count 1 2 3
% within gender 1.8 3.3 2.6
Total count 56 61 117
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Bryman, A. (2008) Social Research Methods. 3rd Ed.Oxford: Oxford University Press.
David, M. and Sutton, C. (2011) Social Research : An
Introduction. 2nd ed. London: Sage.
ReferencesReferences
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This resource was created by the University of Plymouth, Learning from WOeRk project. Thisproject is funded by HEFCE as part of the HEA/JISC OER release programme.
This resource is licensed under the terms of the Attribution-Non-Commercial-ShareAlike 2.0 UK: England & Wales license (http://creativecommons.org/licenses/by-nc-sa/2.0/uk/).
The resource, where specified below, contains other 3rd party materials under
their own licenses. The licenses and attributions are outlined below:
1. The name of the University of Plymouth and its logos are unregistered trade marks of the University. TheUniversity reserves all rights to these items beyond their inclusion in these CC resources.
2. The JISC logo, the and the logo of the Higher Education Academy are licensed under the terms of the CreativeCommons Attribution -non-commercial-No Derivative Works 2.0 UK England & Wales license. All reproductions
must comply with the terms of that license.
Author Laura Lake
Institute University of Plymouth
Title Research Methods: Level 6Final Year Project Toolkit
Description Bivariate AnalysisDate Created May 2011
Educational Level Undergraduate
Keywords Independent variable, dependent variable, causation, crosstabulation, elaboration analysis, UKOER, LFWOER, CPD,Learning from WOeRK, UOPCPDRM, Continuous professionaldevelopment, Quantitative , Qualitative, HEA, JISC, HEFCE
Back page originally developed by the OER phase 1 C-Change project
University of Plymouth, 2010, some rights reserved
http://cpdoer.net/http://creativecommons.org/licenses/by-nc-sa/2.0/uk/http://creativecommons.org/licenses/by-nc-sa/2.0/uk/http://creativecommons.org/licenses/by-nc-sa/2.0/uk/http://cpdoer.net/