Uses trends from historical data to forecast the future.
A moving average takes a data series and “smoothes” the fluctuations in data to show an average. The aim is to take out the extremes of data from period to period.
Extrapolation is not just drawing a straight line and assuming that conditions will all remain stable or equivalent to historial data. It requires attention to be paid to the various different internal and exterenal factors.
- product life cycle
- pace of technological innovation
- market saturation
Pros and Cons of Extrapolation
- A simple method
- Not much data required
- Quick and cheap
- Assumes the continuation of past trends
- Ignores many qualitative factors (changes in fashion or taste for instance)
Correlation is the strength of the relationship between two variables.
The factor that causes the dependent variable to change.
The variable that is influenced by the indepedent variable. Y axis
Types of correlation
A positive relatioshiop, when the independent increases so does the dependent.
A negative relationship, when the independent decreases so does the dependent.
There is no obvious relationship between the two variables.
Strong correlations are very definite, whereas a weak correlation means the data is quite spread.