Practice

15 questions

• Forecasting

  A colleague evaluated a daily passenger forecasting model with shuffled 5-fold cross-validation and reports 3% MAPE. What is wrong, and how would you evaluate it?
  mid8 min

• Forecasting

  A retailer evaluates SKU-store daily demand forecasts with MAPE. Many SKU-days have zero sales. Which metric would you use instead, and why?
  mid8 min

• Forecasting

  You build one global LightGBM model to forecast daily passengers for 300 routes, 14 days ahead. Features include lag1, lag7 and a 7-day rolling mean. Backtest error is excellent.
  senior12 min

• Forecasting

  You are asked to forecast passenger demand for a route to support a decision on adding a second daily flight. Historical passengers are often at capacity on the existing flight.
  senior12 min

• Forecasting

  Airline catering must load meals per flight. Running out of meals costs about 300 per missing meal (compensation, complaints), while an unused meal costs about 100 (hypothetical figures).
  senior12 min

• Forecasting

  In the academy's synthetic airline data, a competitor increases capacity by 25% on three routes from 2024-03-01.
  staff25 min

• Forecasting

  A new daily passenger-demand model has an MAE of 6.0 passengers on the latest validation week, and the dashboard says its error is "71% lower than the naive forecast" (the naive forecast being…
  mid8 min

• Forecasting

  Three teams forecast the same quantity at different levels: network planning forecasts total weekly demand, route managers forecast their own routes, and finance consumes a budget number.
  staff25 min

• Forecasting

  A weekly demand forecast for a route has been reviewed with MAE and it looks acceptable. A planner says "it keeps coming in low".
  mid8 min

• Forecasting

  The airline launches a new route next quarter and the network team needs weekly demand forecasts and a first capacity plan, but the route has no history.
  senior15 min

• Forecasting

  The demand-planning team asks for two months of work to take weekly SKU-store forecast error (WAPE) from 14% to 12%. You are asked to decide whether it is worth it.
  staff25 min

• Forecasting

  You build one model to forecast daily passengers 1 to 14 days ahead. A teammate's feature set contains passengerslag7, passengerslag14, holidayflag, competitorfaretoday and weatheractual.
  mid10 minin review

• Forecasting

  Your model's nominal 80% prediction intervals for weekly route demand cover the actual value only 62% of the time across 500 backtest forecast origins. Planners use the upper bound to set capacity.
  senior15 min

• Forecasting

  Whiteboard case. A retailer wants one forecasting platform for 50,000 SKU-store series (daily, 28 days ahead) that feeds replenishment, with category managers entitled to override numbers.
  staff40 minin review

• Forecasting

  A marketing analyst finds that the weekly "cheap flights" search-interest index and weekly bookings, over 104 weeks, have a correlation of 0.95 (both series are simulated for this exercise).
  mid10 min