# Assignment 2-3

In previous assignments I’ve been looking into the association between union membership and political participation (both categorical variables), using the Outlook On Life surveys. For our present assignment we’re to generate a correlation coefficient, so I had to use other variables. I decided to test whether younger respondents tend to have more positive views of Occupy Wallstreet.

Here’s the code:

# Import relevant libraries

import pandas

import numpy

import seaborn

import scipy

# Read data & print size of dataframe

data = pandas.read_csv('../../Data Management and Visualization/Data/ool_pds.csv', low_memory = False)

print (data.shape)

# Only variable W1_D16 contains missing values that need to be recoded

data['W1_D16'] = data['W1_D16'].replace(-1, numpy.nan).replace(998, numpy.nan)

sub = data[['PPAGE', 'W1_D16']].dropna()

scat = seaborn.regplot(x="PPAGE", y="W1_D16", fit_reg=True, data=sub)

print ('Association between age and opinion of OWS')

print (scipy.stats.pearsonr(sub['PPAGE'], sub['W1_D16']))

And here’s the output:

Association between age and opinion of OWS

(-0.050642104468121348, 0.030560880228248256)

There’s a negative and statistically significant (`p ) correlation between age and opinions on OWS, so yes, younger people do seem to be likely to have a more positive view of OWS. However, the correlation coefficient is very small, -.05, which implies that age could explain a mere 0.25% of variation in opinions on OWS.`