Construct the time series plot. Explain the type of pattern.

Question

The following table gives the average monthly exchange rate between the U.S. dollar and the euro for 2009. It shows that 1 euro was equivalent to 1.289 U.S. dollars in January 2009. Develop a trend line that could be used to predict the exchange rate for 2010. Use this model to predict the exchange rate for January 2010 and February 2010. MONTH ______________________ EXCHANGE RATE January ....................................... 1.289 February ...................................... 1.324 March ......................................... 1.321 April .......................................... 1.317 May ........................................... 1.280 June ........................................... 1.254 July ........................................... 1.230 August ....................................... 1.240 September ................................... 1.287 October ..................................... 1.298 November .................................. 1.283 December…

Answer 1

Question

Chapter 17.4, Problem 27E

a.

To determine

Construct the time series plot.

Explain the type of pattern.

b.

To determine

Calculate the quadratic trend equation for the data.

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The following table gives the average monthly exchange rate between the U.S. dollar and the euro for 2009. It shows that 1 euro was equivalent to 1.289 U.S. dollars in January 2009. Develop a trend line that could be used to predict the exchange rate for 2010. Use this model to predict the exchange rate for January 2010 and February 2010. MONTH ______________________ EXCHANGE RATE January ....................................... 1.289 February ...................................... 1.324 March ......................................... 1.321 April .......................................... 1.317 May ........................................... 1.280 June ........................................... 1.254 July ........................................... 1.230 August ....................................... 1.240 September ................................... 1.287 October ..................................... 1.298 November .................................. 1.283 December…

In retail, a store manager uses time series models to understand shopping trends. Review the scatter plot of the store’s sales from 2010 through 2021 to answer the questions. See attached as image. Here is the data for Fiscal Year and Sales: Fiscal Year Sales 2010 $260,123.00 2011 $256,853.00 2012 $274,366.00 2013 $290,525.00 2014 $322,318.00 2015 $380,921.00 2016 $541,925.00 2017 $909,050.00 2018 $1,817,521.00 2019 $3,206,564.00 2020 $4,921,005.00 2021 $5,686,338.00 Time series decomposition seeks to separate the time series (Y) into 4 components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference between these components? The model can be additive or multiplicative. When do you use each? Review the scatter plot of the exponential trend of the time series data. Do you observe a trend? If so, what type of trend do you observe? What predictions might you make about the store’s annual sales over the next few years?