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Exam 3 QMB3250 questions with correct answers $14.99   Add to cart

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Exam 3 QMB3250 questions with correct answers

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  • QMB 3250
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  • QMB 3250

Exam 3 QMB3250 questions with correct answers

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  • August 15, 2024
  • 12
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • QMB 3250
  • QMB 3250
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Fordenken
Exam 3 QMB3250 questions with correct
answers

Time Series - ANSWER: ➡ when we collect data over time to determine patterns for future
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outcomes
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ex: Daily, weekly, monthly, quarterly, yearly.
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Multiple Regression Models (for time series) - ANSWER: ➡ 'Predicting' a quantitative
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response based on multiple inputs of quantitative variables
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(and possible categorical = indicator variable, or variables multiplied = interaction terms)
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Additive - used for simple linear model.
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Exponential - logarithm is taken o o o o




Quarters - adding indicator variables
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Random walks - ANSWER: ➡ the best prediction is the most recent point.
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Moving averages - ANSWER: ➡ • creates a time series by averaging adjacent values.
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MA(L) = Sum of L consecutive series values)/L
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• Longer periods have MA that respond slower, while shorter periods respond faster
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• Predicting the next unknown value in the time series is equal to the last predicted value.
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Simple Exponential Smoothing - ANSWER: ➡ Effective technique if time series shows little or
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no trend and no seasonal variation.
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Simple Exponential Smoothing [Equation] - ANSWER: ➡ Equation is "~yt"=alpha"y"t + (1-
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alpha) "~yt-l" o o

, --> alpha is the smoothing constant which is typically between 0 and 1
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--> The closer alpha is to 1 the more weight is given to the more recent value and will 'react'
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faster to irregular components.
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--> The closer alpha is to 0 the more weight is given to the historic value and will 'react' slower
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and be more of a stable time series.
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--> Predicting the next unknown value in the time series is equal to the last predicted value.
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MAPE - ANSWER: ➡ how much error there is proportional to the original value
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[Mean Absolute Percentage Error]
o o o




Auto regressive Model - ANSWER: ➡ uses regression by using lagged variables. Each lag will
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move all the data forward a
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time period. Is a good model when you have seasonal components.
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Auto regressive Model [equation] - ANSWER: ➡ "~y"= b0 + b1(lag1) + b2(lag2) +...+ bp(lag
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p)
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Observational Studies - ANSWER: ➡ researchers do not try to change or manipulate anything,
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just observe.
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[You can find an association, but not causation]
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Experiments - ANSWER: ➡ A design in which the treatments are being actively imposed on
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the experimental units.
o o o




Explanatory variables (factors) - ANSWER: ➡ - The variables that we suspect affect the
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response variable.
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Levels - ANSWER: ➡ The ______ are the subcategories of the factors.
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Treatments - ANSWER: ➡ the combination of factors and levels
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