Data Analysis for Climate Change

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Statisticians and data scientists alike Absalom Carlisle 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

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Absalom Carlisle
Absalom Carlisle

Written by Absalom Carlisle

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Absalom Carlisle is a specialist in strategic planning, project management, marketing, and business development, dedicated to deliver results.

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