Datathon NSI Solution – Predicting Household Budgets
Version for upload
Version for upload
The National Statistical Institute of Bulgaria (NSI) conducts annually a Household Budget Survey (HBS) with an objective to get reliable and scientifically founded data on the income, expenditure, consumption and other elements of the living standard of the population as well as changes, which have occurred during the years. NSI is considering a change in the periodicity of the Household Budget Survey from yearly to once on every five years,In order to optimize the cost of carrying out the survey. Hence We are creating a model which will predict household expenditure for the next four years using linear regression model and time series. The algorithms that we will be taking help from are linear regression model & Autoregressive integrated moving average(ARIMA). So lets not waste any time and move on with it !
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Problem statement :This data set is regarding time series analysis on failure rate of ravens sending the messages from king’s landing to the north . This case study is an analogy on Telenor telecommunications and Game of Thrones . Due to the obstacles that caused the failure rate , various techniques and schemes are employed in the planning, design and optimization of raven networks to combat these propagation effects.
We have used R-studio for Exploratory Data Analysis.
As per the tasks given to us , we concluded that
1.Brass Raven Birdy has been delayed for the most number of times , followed by Brown raven ruby and Yellow raven Rio,
while Metallic Sunburst Raven Polly has been delayed for the least number of times , followed by Green Sheen raven Azul and Less combative raven zazu.
2. The family with most fails is Targerian , while with least fails is Lannister
3. The family Member with most fails is Petyr Baelish and with least fails is Euron .
We have done further analysis on predicting the fails for the next four days using TIME SERIES ANALYSIS
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