Time Series Analysis of Alcoholic Beverages

Time Series Analysis of Alcoholic Beverages
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Time Series Graph

Based on research, drinking small quantities of alcohol could help people decrease risk of heart disease, stroke, diabetes mellitus and early death. Additionally, in our daily life, even though people do not know these merits of liquor, a number of people still love alcohol. Sometimes, people regard drinking alcohol as a pattern of life. Therefore, liquor, as one of the most popular consumptions of daily life, possesses both the trading potential and collection value. In order to obtain a more comprehensive understanding of the liquor market, we analyzed the data of merchant wholesalers of beer, wine, and distilled alcoholic beverages sales. Through such a indepth research, we aim at constructing a time series model, by using R software, to predict the future liquor market growth, which acts as valuable investment references.


Merchant Wholesalers of Alcoholic Beverages Dataset

Data Description

Dataset for Alcoholic Beverages

We select data from the FRED website that includes two variables. The x-axis is monthly dates from Jan 1st, 1992 to Aug 31th, 2018. The y-axis is Merchant Wholesalers of Non Durable Goods (beer, wine, distilled alcoholic beverages) Sales in millions of dollars. We originally have 320 observations, but we eliminate the last 20 values in order to compare our forecast data with the real data later.