where the intercept 0 β and the slope 1 β are unknown constant and ε is a random error. The errors are
assumed to have mean zero and unknown variance
2 σ . The parameters 0 β and 1 β are unknown and
must be estimated using sample data. The simple linear regression equation is also called the least
squares regression equation. It tells the criterion used to select the best fitting line, namely the sum of the
squares of the residuals should be least. That is, the least squares regression equation is the line for which
the sum of squared residuals ( ) Σ=
−
n
i
i i y y
1
2 ˆ is a minimum.
2. Data and Methods
2.1 Latitude and climate of Perlis, Northern Malaysia
Based on Malaysia Meteorological Department [10], Malaysia naturally has abundant sunshine and
thus solar radiation. However, it is extremely rare to have a full day with completely clear sky even in
periods of severe drought. The cloud cover cuts off a substantial amount of sunshine and thus solar
radiation. On the average, Malaysia receives about 6 hours of sunshine per day. Based on Meteorological
Station in Chuping, Perlis (60 29’ N , 1000 16’ E) as shown in Fig.2 has about 795 square kilometers land
area, 0.24% of the total land area of Malaysia, with a population about 204450 people [10]. Perlis's
climate is tropical monsoon. Its temperature is relatively uniform within the range of 21°C to 32°C
throughout the year. During the months of January to April, the weather is generally dry and warm.
Humidity is consistently high on the lowlands ranging 82% to 86% per annum. The average rainfall per
year is 2,032 mm to 2,540 mm and the wettest months are from May to December. In this research, the
data are presented in daily averaged maximum and minimum temperature, and daily averaged solar
radiation.