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Holiday-park guest nights in a North Island town

Trend, seasonality and additive-model forecasts

tourism
Table 1 shows the number of guest nights (in thousands) at holiday parks in a North Island town for each quarter from 2021 Q1 to 2024 Q4 (Q1 = Jan–Mar). An analyst fitted a least-squares linear trend, with time t=1t = 1 for 2021 Q1 up to t=16t = 16 for 2024 Q4: $T^=53.33+0.478t\hat{T} = 53.33 + 0.478tTheseasonaleffectsarethemeanresidualsforeachquarter:Q1 The seasonal effects are the mean residuals for each quarter: Q1 +13.1,Q2, Q2 -6.33,Q3, Q3 -10.13,Q4, Q4 +3.36(thousandguestnights).Figure1showstheserieswiththefittedtrendline.Figure2shows,foreachquarter,theresidualsfromthetrend(data−trend)foreachyear,togetherwiththeirmean,whichistheseasonaleffect.Table1:Guestnights(thousands)∣Quarter∣ (thousand guest nights). Figure 1 shows the series with the fitted trend line. Figure 2 shows, for each quarter, the residuals from the trend (data − trend) for each year, together with their mean, which is the seasonal effect. Table 1: Guest nights (thousands) | Quarter | t$ | Guest nights | |---|---|---| | 2021 Q1 | 1 | 68.1 | | 2021 Q2 | 2 | 47.0 | | 2021 Q3 | 3 | 42.0 | | 2021 Q4 | 4 | 58.3 | | 2022 Q1 | 5 | 66.6 | | 2022 Q2 | 6 | 49.0 | | 2022 Q3 | 7 | 46.3 | | 2022 Q4 | 8 | 57.7 | | 2023 Q1 | 9 | 70.9 | | 2023 Q2 | 10 | 53.0 | | 2023 Q3 | 11 | 48.8 | | 2023 Q4 | 12 | 64.6 | | 2024 Q1 | 13 | 73.5 | | 2024 Q2 | 14 | 54.3 | | 2024 Q3 | 15 | 52.9 | | 2024 Q4 | 16 | 65.3 |
Line graph of quarterly guest nights (thousands) from 2021 Q1 to 2024 Q4, with a peak every Q1 and a low every Q3, together with the fitted linear trend line rising from about 54 to 61 thousand.
Line graph of residuals from the trend (data − trend, thousands) for Q1 to Q4, one line per year 2021–2024, with the mean residual for each quarter in red: Q1 +13.1, Q2 −6.33, Q3 −10.13, Q4 +3.36. Q3 residuals are −12.76 (2021), −10.38 (2022), −9.79 (2023) and −7.60 (2024), so the 2024 winter dip is the shallowest.
Facts you may need

(a)

Use Figures 1 and 2, the table and the model to describe the features of the guest-night data over 2021–2024. Use numbers in your answer.

(b)

Use the model to forecast guest nights for 2025 Q1 and 2025 Q3.

(c)

Give TWO reasons why these forecasts may not be reliable.