Essay on Apple: Forecasting and Personnel Creates Unity

optimising return from all employees in the interest of the entire enterprise. Successful managers have personal integrity, communicate clearly and base their judgments on regular audits. Their thorough knowledge of personnel creates unity, energy, initiative and loyalty and eliminates incompetence optimising return from all employees in the interest of the entire enterprise. Successful managers have personal integrity, communicate clearly and base their judgments on regular audits. Their thorough knowledge of personnel creates unity, energy, initiative and loyalty and eliminates incompetence optimising return from all employees in the interest of the entire enterprise. Successful managers have personal integrity, communicate clearly and base their judgments on regular audits. Their thorough knowledge of personnel creates unity, energy, initiative and loyalty and eliminates incompetence; optimising return from all employees in the interest of the entire enterprise. Successful managers have personal integrity, communicate clearly and base their judgments on regular audits. Their thorough knowledge of personnel creates unity, energy, initiative and loyalty and eliminates incompetence; optimising return from all employees in the interest of the entire enterprise. Successful managers have personal integrity, communicate clearly and base their judgments on regular audits. Their thorough knowledge of personnel creates unity, energy, initiative and loyalty and eliminates incompetence; optimising return from all employees in the interest of the entire enterprise. Successful managers have personal integrity, communicate clearly and base their judgments on regular audits. Their thorough knowledge of personnel creates unity, energy, initiative and loyalty and eliminates incompetence;
For other uses, see Forecast (disambiguation).

Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term. Both might refer to formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgemental methods. Usage can differ between areas of application: for example, in hydrology, the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period.

Risk and uncertainty are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts. In any case, the data must be up to date in order for the forecast to be as accurate as possible.[1]

Contents

1 Categories of forecasting methods 1.1 Qualitative vs. quantitative methods 1.2 Naïve approach 1.3 Time series methods 1.4 Causal / econometric forecasting methods 1.5 Judgmental methods 1.6 Artificial intelligence methods 1.7 Other methods 2 Forecasting accuracy 3 Applications of forecasting 4 Limitations 4.1 Performance limits of fluid dynamics equations 4.2 Complexity introduced by the technological singularity 5 See also 6 References 7 External links

Categories of forecasting methods
Qualitative vs. quantitative methods

Qualitative forecasting techniques are subjective, based on the opinion and judgment of consumers, experts; they are appropriate when past data are not available. They are usually applied to intermediate- or long-range decisions. Examples of qualitative forecasting methods are[citation needed] informed opinion and judgment, the Delphi method, market research, and historical life-cycle analogy.

Quantitative forecasting models are used

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