xlminer forecasting | Science homework help
Instructions and data attached
The Excel file “CentralEnglandTemp2017” shows the 3216 monthly mean (surface air) temperatures for the Midlands region of England between 1750 and 2017. (The shown temperatures are in Celsius degrees measured with a precision of 0.1 °C.) The data set represents the longest reliable series of monthly temperature observations in existence, and hence is the most valuable source of information for meteorologists and climate scientists. It was originally published by Professor Gordon Manley in 1953, and has been subsequently updated until today.
It is quite obvious that the monthly temperatures for Midlands must have a seasonal pattern. However, the main purpose of the assignment is to examine the trend existence and its consequences.
1. Using XLMiner (Transform > Transform Categorical Data > Create Dummies), create 12 dummy variables corresponding to the 12 months (Jan, Feb,…,Dec). Since the categorical variable Month has 12 levels (categories), delete the dummy variable Jan; you will assume later the linear regression model with linear trend and seasonality:
Note. XLMiner shows the created dummy variables in the alphabetical order, so rename and rearrange them properly.
2. Create two separate data sets for the time periods 1750 – 1949 (2400 observations) and 1950-2017 (816 observations) on which you could run regression for the assumed regression model. For this purpose, you should create an additional independent variable t with values 1,2,…,2400 and 1,2,…,816, respectively.
3. Use the first data set (created for 1750-1949).
