Weather-And-Global-Warming-Analysis
An analysis of the Influence of Global Warming on the weather.
Introduction:
Knowing accurate weather conditions is an important element for individuals and organizations. Many businesses rely on weather conditions. It is necessary to have the correct data to make accurate decisions. One type of data that's easier to find on the internet is Weather Data. Many sites provide historical data on many meteorological parameters.
Objective:
The main focus of the project is to perform an analysis for testing the Influences of Global Warming.
Hypothesis
A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.
The Null Hypothesis H0 "Has the Apparent temperature and humidity compared monthly across 10 years of the data indicate an increase due to Global Warming" -- That means, it is needed to find the Apparent average temperature for the month of a month says April starting from 2006 to 2016, and the average humidity for the same period have increased or not.
What is this "Apparent Temperature", and Humidity in the "Null Hypothesis (HO)?
These are called Terminologies, also known as column names or criteria used to contain the data to different specifications or classes. To know that, looking up basic terminologies used in the data is a must.
Terminologies
Meteorological Data, which refers to the data consisting of physical parameters that are measured directly by instrumentation, and include temperature, dew point, wind direction, wind speed, cloud cover, cloud layer(s), ceiling height, visibility, current weather, and precipitation amount.
Apparent temperature is the temperature equivalent perceived by humans, caused y the combined effects of air temperature, relative humidity, and wind speed. The measure is the most commonly applied to the perceived outdoor temperature.
Humidity is the amount of water vapor in the air. If there is a lot of water vapor in the air, the humidity will be high. The higher the humidity, the wetter it feels outside.
Dataset
The dataset has hourly temperature recorded for the last 10 years starting from 2006–04–01 00:00:00.000 +0200 to 2016–09–09 23:00:00.000 +0200. It corresponds to Finland, a country in Northern Europe.
