Download presentation

Presentation is loading. Please wait.

Published byAlfonso Flash Modified over 3 years ago

1
Hypothesis Testing with Categorical Variables 5th - 9th December 2011, Rome

2
A hypothesis Is the prevalence within each food consumption group significantly different between male-headed and female-headed households? Both variables are categorical… How can we test this hypothesis?

3
Pearsons chi-square test

4
Limitations While Pearsons chi-square test will tell you if there is a significant difference, it cannot test the strength or direction of the difference For this reason, we often recode one of the categorical variables into a continuous variable and use a different test

5
Recoding To use an ANOVA or a t-test, we need one of the variables to be continuous This is simply done by recoding a dichotomous variable to a value of 0 or 1

6
Returning to our example… Is the prevalence within each food consumption group significantly different between male-headed and female-headed households? Food consumption groups have a value of: 1. Poor food consumption 2. Borderline food consumption 3. Acceptable food consumption Sex of household have a value of: 1. Males 2. Females Recode each food consumption group into a bivariate: 0 = no; 1 = yes Run an ANOVA to test the hypothesis

7
ANOVA output for poor food consumption and sex of household head Descriptives Poor FCG NMean Std. DeviationStd. Error 95% Confidence Interval for Mean MinimumMaximum Lower Bound Upper Bound Male3803.0587.23504.00381.0512.06610.001.00 Female1068.0893.28526.00873.0721.10640.001.00 Total4871.0654.24723.00354.0584.07230.001.00 ANOVA Poor FCG Sum of Squaresdf Mean SquareFSig. Between Groups.7811 12.802.000 Within Groups 296.9064869.061 Total297.6874870 What can we say about our hypothesis?

8
ANOVA output for borderline food consumption and sex of household head Descriptives Borderline FCG NMean Std. DeviationStd. Error 95% Confidence Interval for Mean MinimumMaximum Lower Bound Upper Bound Male3803.3859.48688.00789.3704.40140.001.00 Female1068.3810.48585.01486.3518.41010.001.00 Total4871.3848.48660.00697.3712.39850.001.00 ANOVA Borderline FCG Sum of Squaresdf Mean SquareFSig. Between Groups.0211.087.768 Within Groups 1153.2334869.237 Total1153.2544870 What can we say about our hypothesis?

9
ANOVA output for acceptable food consumption and sex of household head Descriptives Acceptable FCG NMean Std. DeviationStd. Error 95% Confidence Interval for Mean MinimumMaximum Lower Bound Upper Bound Male3803.5554.49699.00806.5396.57120.001.00 Female1068.5298.49935.01528.4998.55980.001.00 Total4871.5498.49757.00713.5358.56380.001.00 ANOVA Acceptable FCG Sum of Squaresdf Mean SquareFSig. Between Groups.5481 2.213.137 Within Groups 1205.2484869.248 Total1205.7964870 What can we say about our hypothesis?

10
Your turn Propose a hypothesis to test that uses data from 2 categorical variables State your hypothesis How will you recode the variable to answer your hypothesis?

Similar presentations

OK

Testing Your Hypothesis In your previous assignments you were supposed to develop two hypotheses that examine a relationship between two variables. For.

Testing Your Hypothesis In your previous assignments you were supposed to develop two hypotheses that examine a relationship between two variables. For.

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google

Ppt on global warming with sound Ppt on indian politics latest Ppt on bank lending ratios Ppt on law against child marriage in islam Ppt on alternative fuels for i.c engine Elementary ppt on cells Ppt on conservation of mass Presentation ppt on motivation theories Revising vs editing ppt on ipad Ppt on 7 wonders of the world 2013