Title: COMPARISON OF FOUR SEASONS OF INDIA
Author: DHARA GALA
Introduction:
Seasons remind us that change is the law of nature and a sign of progress. In India, there are mainly six seasons as per the ancient Hindu calendar (the Lunisolar Hindu). The twelve months in a year are divided into six seasons of two-month duration each. These seasons include Vasant Ritu (Spring), Grishma Ritu (Summer), Varsha Ritu (Monsoon), Sharad Ritu (Autumn), Hemant Ritu (Pre-Winter) and Shishir Ritu (Winter). However, as per the India Meteorological Department (IMD), there are four seasons in India like other parts of the world.
Objective: To compare the Seasons & test the Hypothesis.
Literature:
1. Seasonal Adjustment
The primary goal of creating seasonally adjusted time series is to provide simple access to a common time series data set that has been cleaned of what is seen as seasonal noise. Although using officially seasonally adjusted data may save money, it may also result in a less effective use of the information at hand and the application of a skewed set of statistics. As a result, it may be necessary in many situations to incorporate seasonality as an integral component of an economic analysis. In addition to using data adjusted by the two most used adjustment methods, we describe numerous additional ways to incorporate seasonal adjustment into the econometric analysis in this article. (Svend Hylleberg,2006)
2. On the role of seasonal intercepts in seasonal cointegration
The primary goal of creating seasonally adjusted time series is to provide simple access to a common time series data set that has been cleaned of what is seen as seasonal noise. Although using officially seasonally adjusted data may save money, it may also result in a less effective use of the information at hand and the application of a skewed set of statistics. As a result, it may be necessary in many situations to incorporate seasonality as an integral component of an economic analysis. In addition to using data adjusted by the two most used adjustment methods, we describe numerous additional ways to incorporate seasonal adjustment into the econometric analysis in this article. (Franses, Philip Hans, Kunst, Robert M.,1995)
Data Collection:
To analyze the views of students about 4 Seasons of India were taken for study. Students are asked to rate the 4 Seasons of India using scale of 1 to 10 through Google form. Then Calculate ANOVA (oneway) using Excel and Data analysis.
H0 stands for All are the same
H1 stands for Anyone of them is different
Data Analysis:
Anova: Single Factor
SUMMARY
Groups Count Sum Average Variance
Column 1 45 199 4.422222 9.022222
Column 2 45 337 7.488889 6.846465
Column 3 45 283 6.288889 7.80101
Column 4 45 328 7.288889 5.891919
ANOVA
Source of Variation SS df MS F P-value F crit
Between Groups 265.35 3 88.45 11.96822 3.61E-07 2.655939
Within Groups 1300.711 176 7.390404
Total 1566.061 179
Where,
SS stands for sum of squares
Df for Degree of Freedom
MS stands for Mean Squares
The above table tells us between groups.
f(11.96822) > F critical (2.655939). Reject H0, Accept H1 which means anyone of them is different.
Conclusion:
Anyone of the season is different.
Reference:
Philip Hans Franses, Robert M. Kunst, 1995, Economics Series No. 15, Septerber 1995
Svend Hylleberg, 2006, New Palgrave Dictionary of Economics, 2nd edition, Working Paper No. 2006-4, February 22, 2006