WEEK 9: BIVARIATE ANALYSIS II
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Transcript of WEEK 9: BIVARIATE ANALYSIS II
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Office Hours: Thursday 1.30-2.30pm FW102
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• Null Hypothesis is a hypothesis which the researcher
tries to disprove, reject or falsify
• Example: Does gender influence the salary of a British worker?
• What is the Null Hypothesis?There is no association between
gender and salary in UK.
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Men%
Women%
Labour 75 75
BNP 25 25
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To find out if there is a significant association between the variables
Calculates Expected frequencies (when Null Hypothesis is true) and compares them with the data we have (Observed Frequencies)
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Chi-Square Tests
95.952a 3 .000
97.623 3 .000
11.267 1 .001
2936
Pearson Chi-Square
Likelihood Ratio
Linear-by-LinearAssociation
N of Valid Cases
Value dfAsymp. Sig.
(2-sided)
0 cells (.0%) have expected count less than 5. Theminimum expected count is 67.56.
a.
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Same logic with Chi square test:
Find the expected values when there is no association between the variables and compare them with the actual data we have.
But use t-test when we have continuous variables (real numbers)
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Shows difference between expected values when null hypothesis is true & the observed values
If the t-value is close to or greater than +/-2, then the relationship is usually significant at what is called the .05 level.
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R2 ranges from 0 to 1 0explains nothing 1perfect association
So if R2 is 0.50, we can say that 50% of the variance in Y can be explained by the variance in X
Or, you make 50% less errors when guessing Y by knowing X, as compared to guessing Y when not knowing X
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(Simple regression equation)
Y= a + b X
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Y = a + bX
Intercept or a, the point where the line cuts the Y axis
Slope of the line or b, the amount of change in Y that you get if X increases by one unit
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Possible reasons for voting for Far-right parties (BNP)
racist sentiments political alienation (public dissatisfaction
with the working of democracy) social alienation
What do you think? Which one is the main reason?
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How much do you trust the Parliament at Westminster?
political alienation
On balance, would you say that most people can't be trusted or that most people can be trusted?
Social alienation
how do you feel about black and white people? Racist sentiment
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political alienationThere is no association between voting for
BNP and the level of trust in the parliamentSocial alienationThere is no association between voting for
BNP and trusting peopleRacist sentimentThere is no association between voting for
BNP and feelings about black and white people
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N Minimum Maximum MeanStd. Deviation
Feelings_BNP2829 .00 10.00 1.5695 2.22239
Trust-Parliament at Westmister
3011 .00 10.00 4.4915 2.30127
Most People Can Be Trusted 3059 .00 10.00 6.0530 2.15318
Feelings-Whites 2992 .00 10.00 7.4081 1.93979
Feelings-Blacks2992 .00 10.00 6.3961 2.21780
Valid N (listwise) 2721
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B coefficient Std. Error P Value
(Constant) 2.983 0.127 0.000
Feelings-Blacks -0.219 0.019 0.000
a Dependent Variable: Feelings_BNP
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THREE STEPS1-SIGNIFICANCE OF THE ASSOCIATION The relationship between X (feelings for
blacks) and Y (support for BNP) is significant at the 0.05 level (we can reject the null hypothesis of no association).
2-DIRECTION OF THE ASSOCIATION The b coefficient of -0.219 is negative,
indicating that the people who have positive feelings towards black people tend to have lower levels of support for BNP.
3- MAGNITUDE
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3-MAGNITUDE OF THE “X” EFFECT For every percentage point increase in X
(positive feelings towards black people), the level of support for BNP (Y) will decrease by 0.219 points on the 0-10 scale.
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Dependent variable: Feeling BNP
B coefficient Std. Error P Value
(Constant) 1.736 0.094 0.000
Trust-Parliament at Westminster
-0.037 0.018 0.044
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Dependent variable: Feeling BNP
B coefficient Std. Error P Value
(Constant) 2.542 0.127 0.000
Most People Can Be Trusted
-0.158 0.020 0.000
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B coefficient
Std. Error P Value
(Constant) 1.245 0.252 0.000
Feelings-Whites
0.059 0.033 0.075
Dependent Variable: Feelings_BNPDependent Variable: Feelings_BNP
Dependent Variable: Feelings_BNP
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Multivariate Analysis: Testing Hypotheses
Testing hypotheses with OLS regression Modelling in political science, multiple relationships between variables, interpreting OLS regression analysis
Check out the moodle for readings
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