# Computer Science Questions

## Question

# Question 1:
# After plotting a timeseries, you notice there are several dramatic outliers in the data.
# What type of time series component do these outliers represent?

# Question 2:
# The dataset below contains monthly debit card usage in Iceland
# from January 2020 - August 2013. You are tasked with describing the
# time series data and evaluating which Moving Average Model can be best used to
# predict future values (MA-2, MA-5, MA-10).
# Load packages and save dataset as 'debit'
install.packages("fpp2")
library(fpp2)
library(TTR)
debit = debitcards

# A) plot this time series

# B) using a decomposing method/plot, describe the SEASONAL and TREND compositions of this dataset.

# C) Compile a moving average model for each of the three models (MA-2, MA-5, MA-10).

# D) Plot the models' values along with the real values from the dataset, in 1 graph.

# E) Calculate the MSE for each of the three models.
# (Hint: Use the 'Environment' pane on the right to get a sense of sample size for
# each model.)

# F) Based on your answer in E), which model would you recommend using to predict
#    future debit card usage in Iceland?

## Solution Preview

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# Question 1:
# After plotting a timeseries, you notice there are several dramatic outliers in the data.
# What type of time series component do these outliers represent?

# irregular component

# Question 2:
# The dataset below contains monthly debit card usage in Iceland
# from January 2020 - August 2013. You are tasked with describing the
# time series data and evaluating which Moving Average Model can be best used to
# predict future values (MA-2, MA-5, MA-10).
# Load packages and save dataset as 'debit'
install.packages("fpp2")
library(fpp2)
library(TTR)
debit = debitcards
# A) plot this time series
autoplot(debit)

# B) using a decomposing method/plot, describe...
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