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For this particular assignment, the data of different types of wine sales in the 20th century is to be analysed. Both of these data are from the same company but of different wines. As an analyst in...

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For this particular
assignment, the data of different types of wine sales in the 20th century is to
be analysed. Both of these data are from the same company but of different
wines. As an analyst in the ABC Estate Wines, you are tasked to analyse and
forecast Wine Sales in the 20th century.



Data set for the
Problem:
Sparkling.csvandRose.csv



Please do perform the
following questions on each of these two data sets separately.




  1. Read
    the data as an appropriate Time Series data and plot the data.

  2. Perform
    appropriate Exploratory Data Analysis to understand the data and also
    perform decomposition.

  3. Split
    the data into training and test. The test data should start in 1991.

  4. Build
    all the exponential smoothing models on the training data and evaluate the
    model using RMSE on the test data. Other additional models such as
    regression, naïve forecast models, simple average models, moving average
    models should also be built on the training data and check the performance
    on the test data using RMSE.

  5. Check
    for the stationarity of the data on which the model is being built on
    using appropriate statistical tests and also mention the hypothesis for
    the statistical test. If the data is found to be non-stationary, take
    appropriate steps to make it stationary. Check the new data for
    stationarity and comment.
    Note: Stationarity should be checked at alpha = 0.05.

  6. Build
    an automated version of the ARIMA/SARIMA model in which the parameters are
    selected using the lowest Akaike Information Criteria (AIC) on the
    training data and evaluate this model on the test data using RMSE.

  7. Build
    ARIMA/SARIMA models based on the cut-off points of ACF and PACFon
    the training data and evaluate this model on the test data using RMSE.

  8. Build
    a table with all the models built along with their corresponding
    parameters and the respective RMSE values on the test data.

  9. Based
    on the model-building exercise, build the most optimum model(s) on the
    complete data and predict 12 months into the future with appropriate
    confidence intervals/bands.

  10. Comment
    on the model thus built and report your findings and suggest the measures
    that the company should be taking for future sales.

Answered 1 days After Sep 21, 2022

Solution

Aditi answered on Sep 21 2022
64 Votes
SOLUTION.PDF

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