Statistical Method to Predict Agricultural CPI
Yash Kumar Arora1, Santosh Kumar2, Umesh Kumar Tiwari3, Aditi Goswami4, Jasmeet Kalra5
1Yash Kumar Arora, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun (Uttarakhand), India.
2Santosh Kumar, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun (Uttarakhand), India.
3Umesh Kumar Tiwari, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun (Uttarakhand), India.
4Aditi Goswami, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun (Uttarakhand), India.
5Jasmeet Kalra, Department of Mechanical Engineering, Graphic Era Hill University, Dehradun (Uttarakhand), India.
Manuscript received on 15 June 2020 | Revised Manuscript received on 26 June 2020 | Manuscript Published on 04 July 2020 | PP: 59-62 | Volume-8 Issue-12S3 October 2019 | Retrieval Number: L101710812S319/2020©BEIESP | DOI: 10.35940/ijitee.L1017.10812S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The growth of any country depends on its economy and economic growth is nothing but an increase in the inflation i.e. adjusted market value of the goods and services produced by an economy over time. Statisticians conventionally measure such inflation using the price indices. They are mainly WPI (Wholesale Price Index and CPI (Consumer Price Index). WPI is now known to be an older method of computation because the main focus has to be on consumer prices. CPI is a measure of consumer prices over a certain period. Changes in the CPI are used to assess price changes associated with the cost of living. It can be calculated for rural, urban areas as well as for both. In CPI rural, the workers and labourers are benefitted as their daily wages can be predicted by this approach. The CPI by state data represents the inflation of each of the states giving a concise view of the country. The data is collected and analysed using a mathematical approach called linear regression in future prediction for rural labours based on previous data.
Keywords: CPIInflation, Linear Regression, RMS.
Scope of the Article: Encryption Methods and Tools