76 terms

Whenever we have data recorded sequentially over time, and considered them to be on an important aspect of data have a?

time series

Are time series spaced at roughly regular intervals ?

Yes

What are the objective of most time series?

provide forecast of future values of the time series

What are the two types of forecasting?

What's the difference?

What's the difference?

Qualitative: when historical data are unavailable

quantitative: when available

quantitative: when available

Two types of quantitative forecasting method?

Time series (extrapolation) and Causal (econometric)

involves forecasting future values based entirely on the past and present values of a variable

time series

involve the determination of factors that relate to the variable you are trying to forecast

causal (econometric)

What does time series assume?

that the factors that have influence activites in the past and present will continue to do so in approximately the same way in the future

What are the four components in time series models?

TISC

time is usually shown on the horizontal axis and the observed values on the vertical axis

time series plot

the value of the observation at time period t

y

denotes the number of historical observations of y

T

observations in this time series are equal

the base series

an overall long term upward or downward movement in a time series

trend

this constant per period change is then the slope of the linear trend line

linear trend

the percentage increase in Yt from period to period remains constant

exponential trend

Product life cycle

S shaped trend

Many time series have seasonal variation? T/F

True

typically seasonal components repeat annually, but the are a few exception?

24 hours

regular cycles in the data with period longer than one year are referred to as?

cyclical variation

What is hard to predict? cyclic or seasonal component why?

Cyclic variation because it's more irregular

What are the factors that determined time series?

Trend, seasonal, and cyclic components.

random variation explains unpredictable behaviors of human beings

random variation explains unpredictable behaviors of human beings

represents random fluctuations in the data due to irregular or unpredictable events

random variation (noise)

The random variation components give most time series graphs their irregular, ____ appearance

zigzag

If noise increases in magnitude, what happens?

it makes it harder to distinguish the other components

many times-series follow a long term trend except for?

random variation

What are the three types of regression based trend models?

linear, quadratic, and exponential

time series models means that the time series variables changes by a constant amount each time period

linear trend

What's the linear trend model

Check

What is the linear trend forecasting equation?

Check

~The interpretation of b in a linear trend model?

~ If b is positive the trend is?

~ If b is negative the trend is?

~ If b is positive the trend is?

~ If b is negative the trend is?

the expected constant change in the time series from one period to the next

Upward

Downward

Upward

Downward

The interpretation of a in a linear trend model?

estimate the expected value of the time series at t = 0

Forecast for future time periods are made via ____

extrapolation

What are more appropriate? Prediction or confidence intervals?

prediction

What is the quadratic trend model?

Check

What is the quadratic trend forecasting equation?

Check

When the quadratic term is significant, the linear term is kept in the quadratic model even if it is not significant? T/F

True

When a time series change at a rate such that the percentage differences from value to value is constant

Exponential trend

Exponential trend model?

Check

~ How do you make the exponential trend model linear?

~ What is the equation?

~ What is the equation?

By taking the logarithm

Check

Check

If a time series exhibits an exponential trend, then a plot of its logarithm should be approximately _____?

linear

What is the exponential trend forecasting equation?

Check

How to find the y intercept in an exponential trend?

You take the antilog a and find the e^x.

How to find the slope coefficient in an exponential trend?

By expressing the b as a percentage

How come you can't use the standard error of the exponential trend?

because it's not in log format

What is the mean square error (MSE) equation?

Check

Do you want a large or a small MSE?

small

What is the root mean square error (RMSE)?

Check

What do you do when the value of MSE and RMSE becomes inflated through the squaring process?

By finding the Mean Absolute Error (MAE) or the Mean absolute deviation (MAD)

MAE equation?

Check

Do you want a small or a large MAE?

small

What is the MAPE equation?

Check

A model that makes any one of these errors measures small tends to make the other three small as well? T/F

True

When trying to find a forecast for time period T+1 we use the model called?

naive forecasting model

Unfortunately, the existence of random variation often makes the task of identifying the other three components (Long term, seasonal, cyclical variation) difficult, so we use which two most widely used smoothing techniques?

moving averages and exponetial smooth

The forecast for the next time period will be computed by dropping the oldest observation and adding in the newest?

moving average

Remember:

~ If L = n, then the entire data set would be used in the average.

~ If L = 1, we have the naive forecast Yt+1 = Yt

~ If L = n, then the entire data set would be used in the average.

~ If L = 1, we have the naive forecast Yt+1 = Yt

Okay

What happens to the moving averages as the length L increases?

The moving averages series with the greater length is smoother because a larger L cannot respond to rapid changes in a time series like a shorter L can

What length should be used?

If you are interested in long term behavior or have a series with random noise, use a longer moving average; however, if it's a short term change use a shorter moving average.

techniques base their forecast on a weighted average of past observations, with more weight on the more recent observations?

Exponential smoothing

The three most widely used methods for exponential smooth are?

Single, Double, Winter's method

It performs best when there is no pronounced trend or seasonality in the series

single (simple) exponential smoothing

Designed for cases when there is a trend in the data, but no seasonal variation

Double (Holt's method) exponential smoothing

Is is appropriate for a series with both trend and seasonal variation

Winters' method

What is a smoothing constant?

a (0<a<1)

Simple Exponential Smoothing

____ smoothing constants provide forecasts that respond slowly to changes in the series. ___ smoothing constants do the opposite

____ smoothing constants provide forecasts that respond slowly to changes in the series. ___ smoothing constants do the opposite

Small;large

Equation for smoothing constant?

check

What is a basic property of moving average forecasts?

the future forecasts tend to be close to the last few values of the series

The larger smoothing constant produces a less smooth forecast curve and?

The larger smoothing constant produces a less smooth forecast curve and slightly better error measures

True or false? The future forecast from simple exponential smoothing are always flat?

True

forecasting method intended to perform best when the time series to be forecast has a tend, but no seasonal component

Hold's method

Lt is?

the level of the series at time t

an estimate of the change in the series from one period to the next?

Tt (trend term)

The a and B in a Holt's method forecast is assumed to be between?

0 and 1

What does the zero smoothing constant for trend mean?

It doesn't mean that there is no trend, it means that the initial estimate of trend is kept throughout

~Often able to react quickly to a sudden upswing or downswing in the data.

~Typically has a delayed reaction to such a change.

~Typically has a delayed reaction to such a change.

Holt's method; Simple