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QMB 3250 EXAM 3 Modules(17-24) With Questions And 100% ALL CORRECT ANSWERS
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JACKLINEQMB 3250 EXAM 3 Modules(17-24) With Questions And 100% ALL CORRECT
ANSWERS
Practice questions for this set
, Terms in this set (228)
If there is no direction in the time series trend, this is Stationary to the mean.
called...
Seasonal Component (time series) Fluctuation occurs at roughly the same time each year (or day of the week or part of the month).
The time between two peaks is called... Period
1. Trend
2. Seasonal
Components of a Time Series
3. Long Term Cycles
4. Irregular Components
1. Simple Moving Average
Types of smoothing methods
2. Single Exponential Smoothing Average (SES)
- this method creates a new time series from the original data by averaging adjacent values.
Simple Moving Average - the number of values that are averaged is called the length (L).
- the purpose is that it helps illuminate how the data is varying over time.
-The moving average values can be affected by outliers (sharp peaks or falls).
Disadvantages of simple moving average
- Doesn't work well when there are strong seasonal, trend or cyclical components.
A more sophisticated type of moving averages gives different weights to the values being averaged.
Weighted Moving Averages
Values that are further away get less weight.
1. simple exponential smoothing
Types of weighted moving averages
2. auto regressive moving averages
values that are closest to the estimated value get the most weight in the moving average and values
Simple Exponential Smoothing that are further away get less.
* doesn't usually work well when seasonal components are present.s
- Alpha is close to 0.5, the most recent value and historic values are weighed the same .
- Alpha is close to 1, the most recent value is given more weight. this is used if you want the series to
Alpha for Weighted Exponential Smoothing react more quickly to irregular components.
- Alpha is close to 0, the most recent value is given less weight than historic valleys. you want to use
QMB 3250 EXAM 3 Modules(17-24)
Data collected overtime at regular intervals, we time series (daily, weekly, monthly, quarterly, yearly).
have a...
this if you want the series to react more slowly, creating a more stable series.
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