Your browser doesn't support the features required by impress.js, so you are presented with a simplified version of this presentation.

For the best experience please use the latest Chrome, Safari or Firefox browser.

DATA ANALYSIS FOR CLIMATE CHANGE

Absalom Carlisle
Statisticians and data scientists alike use basic analytical concepts to make credible inferences from their data.

columns: Date (year and month) and Monthly Anomaly in Celcius. The datapoints range from January 1850 to December 2014
First four variables: Mean, standard deviation, quantiles, and variance.

print(‘Mean: ‘ ,round(df.Monthly_Anom.mean(),3))
print(‘Variance: ‘, round(df.Monthly_Anom.var(),3))
print(‘Standard Deviation: ‘, round(df.Monthly_Anom.std(),3))

Mean:  -0.093
Variance:  0.119


Standard Deviation:  0.345

Absalom Carlisle