Consider the following time series data. (a) Construct a time series plot. ® 30 25+ 20- 15- 10- 5 1 Month 12 3 4 5 Value 24 13 20 12 19 Month 2 3 4 5 0- C 1 2 3 What type of pattern exists in the data? The data appear to follow a horizontal pattern. O The data appear to follow a seasonal pattern. O The data appear to follow a trend pattern. O The data appear to follow a cyclical pattern. 6 7 30 T 30 25- 25 20- 20 15- mimi ww 15- 10- 10 5 0 0 1 2 3 4 5 6 Month (b) Develop the three-month moving average forecasts for this time series. Time Series Value Compute MSE. MSE=18.09 24 13 20 12 4 Month 19 23 15 19 5 17.25 17.6 Forecast 6 18.50 x What is the forecast for month 8? 126 |x 23 15 6 ]✓ x 7 x x 7 8 0 1 2 3 4 5 Month 6 7 8 ⓇO 30 23 20- 15 10- 5 0 0 1 2 3 4 5 Month 7 8 O 7 8 Ⓡ

Ta Mete a lan Mlaa Ma t Cun hane 15 tradeshare This graph is an example for a. time-series data b. panel-data c. experimental data d. cross-sectional data

The values of Alabama building contracts (in millions of dollars) for a 12-month period follow. (a) Construct a time series plot. 400 350 300 250 200+ O 1 2 3 4 Month 5 6 What type of pattern exists in the data? 7 240 340 220 260 280 310 8 9 150- 100 The data appear to follow a seasonal pattern. The data appear to follow a cyclical pattern. The data appear to follow a trend pattern. O The data appear to follow a horizontal pattern. 10 50 0 11 12 01 2 400 350 300 250 200- 150 100 50 0 0 1 2 3 4 5 34 5 6 7 8 9 10 11 12 13 Month Time Series Value (in $ millions) 240 340 (b) Compare the three-month moving average forecast with the exponential smoothing forecast using a = 0.2. (Round your answers to two decimal places.) 220 260 280 310 210 320 250 6 320 7 Month 230 220 210 320 250 320 230 220 de 8 9 10 11 12 13 r 3-Month Moving Average Forecast (in $ millions) 400 350+ 300 250 200+ 150- 100+ 50+ 0 01010101000 400 T 350 300 0 1 2 3 4 250+ 200+ 150+ 100+ α = 0.2 Forecast (in $ millions) 50…

Find text or tools Use the information provided below to answer questions 24-25. INFORMATION The times series graph below shows information about the quarterly number of tourists from the European Union (EU) to vh Africa over the 2021-2023 period. The underlying trend line indicated by the dotted line is defined by the equation, y 703x-176 577. Time ones graph of quarterly number of tourists for EU to South 40000 REANDDIC 300000 2240 2010 200000 150000 18390 1000 0 2 --T Arica (2021-2023) 12920 30000 2013 8 10 1999 18 QUESTION 24 (4 marks) Using data from the graph, estimate the mean seasonal variation (or average seasonal effect) for quarter 4 (Q4) and use it to predict the number of tourists from the EU expected to visit South Africa in quarter 4 of 2024. A. The mean seasonal variation is -25 000; the number of tourists from the EU expected to visit South Africa in quarter 4 of 2024 is 322 825. B. The mean seasonal variation is 25 000, the number of tourists from the EU expected to…