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 visit South Africa in quarter 4 of 2024 is 332 825. C. 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 312 825. D. 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 372 825. QUESTION 25 (4 marks) The data utilised for the 3-Month Moving Average Forecasting in the table below represents the number of EU tourists who visited South Africa during the twelve quarters of the 2021-2023 period, extracted from the time series graph provided above. Quarter Actual number of EU tourists to South Africa Year 3-Month Moving Average Forecasts of the number of EU tourists Absolute Deviation 2021 Q1 183 160 2021 Q2 224 510 2021 Q3 234 360 2021 Q4 194 389 214 010 19621 2022 Q1 182 900 217 753 34 853 2022 Q2 234 880 W Y 2022 Q3 269 530 204 056 65 474 2022 Q4 237 201 229 103 8 098 2023 Q1 264 970 247 204 17 766 2023 Q2 321 000 x Z 2023 Q3 331 200 274 390 56 810 2023 Q4 280 013 305 723 25 710
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 visit South Africa in quarter 4 of 2024 is 332 825. C. 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 312 825. D. 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 372 825. QUESTION 25 (4 marks) The data utilised for the 3-Month Moving Average Forecasting in the table below represents the number of EU tourists who visited South Africa during the twelve quarters of the 2021-2023 period, extracted from the time series graph provided above. Quarter Actual number of EU tourists to South Africa Year 3-Month Moving Average Forecasts of the number of EU tourists Absolute Deviation 2021 Q1 183 160 2021 Q2 224 510 2021 Q3 234 360 2021 Q4 194 389 214 010 19621 2022 Q1 182 900 217 753 34 853 2022 Q2 234 880 W Y 2022 Q3 269 530 204 056 65 474 2022 Q4 237 201 229 103 8 098 2023 Q1 264 970 247 204 17 766 2023 Q2 321 000 x Z 2023 Q3 331 200 274 390 56 810 2023 Q4 280 013 305 723 25 710
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text: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 visit South Africa in quarter 4 of
2024 is 332 825.
C. 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 312 825.
D. 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 372 825.
QUESTION 25
(4 marks)
The data utilised for the 3-Month Moving Average Forecasting in the table below represents the number of EU tourists who
visited South Africa during the twelve quarters of the 2021-2023 period, extracted from the time series graph provided
above.
Quarter
Actual number of EU
tourists to South Africa
Year
3-Month Moving Average
Forecasts of the number of EU
tourists
Absolute Deviation
2021
Q1
183 160
2021
Q2
224 510
2021
Q3
234 360
2021
Q4
194 389
214 010
19621
2022
Q1
182 900
217 753
34 853
2022
Q2
234 880
W
Y
2022
Q3
269 530
204 056
65 474
2022
Q4
237 201
229 103
8 098
2023
Q1
264 970
247 204
17 766
2023
Q2
321 000
x
Z
2023
Q3
331 200
274 390
56 810
2023
Q4
280 013
305 723
25 710
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