uncertainty

Management

(noun)

A state of having limited knowledge such that it is impossible to exactly describe an existing state or future outcomes or to determine which of several possible outcomes will happen.

Related Terms

  • qualitative
  • tactical planning
Chemistry

(noun)

A parameter that measures the dispersion of a range of measured values.

Related Terms

  • observable
  • indeterminacy
  • momentum

Examples of uncertainty in the following topics:

  • The Uncertainty Principle

    • The reasoning was derived from considering the uncertainty in both the position and the momentum of an object.
    • Roughly, the uncertainty in the position of a particle is approximately equal to its wavelength (λ).
    • The uncertainty in the momentum of the object follows from de Broglie's equation as h/λ.
    • Therefore, to a first approximation the Heisenberg Uncertainty Principle gives that the product of these two uncertainties is on the order of Planck's constant (h).
    • Doc Physics - Heisenberg Uncertainty Principle Derived and Explained - YouTube
  • The Heisenberg Uncertainty Principle

    • The uncertainty principle asserts a basic limit to the precision with which some physical properties of a particle can be known simultaneously.
    • The uncertainty principle is inherent in the properties of all wave-like systems, and it arises in quantum mechanics simply due to the matter wave nature of all quantum objects.
    • Thus, the uncertainty principle actually states a fundamental property of quantum systems, and is not a statement about the observational success of current technology.
    • In fact, if anything about a system is known perfectly, there is likely another characteristic that is completely shrouded in uncertainty.
    • Relate the Heisenberg uncertainty principle with the matter wave nature of all quantum objects
  • Responding to Uncertainty in Strategic Planning

    • Uncertainty exists when there is more than one possible outcome; it is best managed using scenario-planning tools.
    • Management specialists define uncertainty as a state of having limited knowledge such that it is impossible to exactly describe an existing state or future outcomes or to determine which of several possible outcomes will happen.
    • It is still possible, however, to measure uncertainty—by assigning a probability to each possible state or outcome to estimate its likelihood.
    • The second component, uncertainties, involves indeterminable factors such as future interest rates, outcomes of political elections, rates of innovation, fads in markets, and so on.
    • Recognize the inevitability of uncertainty in strategic planning, alongside planning for effective responses to these uncertainties
  • Making Decisions Under Conditions of Risk and Uncertainty

    • Conditions of risk and uncertainty frame most decisions rendered by management.
    • Uncertainty is a state of having limited knowledge of current conditions or future outcomes.
    • Managers often deal with uncertainty in their work; to minimize the risk that their decisions will lead to undesired outcomes, they must develop the skills and judgment necessary for reducing this uncertainty.
    • One approach to dealing with uncertainty is to put off decisions until data become more accessible and reliable.
    • Managing uncertainty in decision-making relies on identifying, quantifying, and analyzing the factors that can affect outcomes.
  • Risk Adjusting for the Time Horizon

    • A longer time horizon usually requires a higher return, due to increased price volatility and uncertainty relating to possible outcomes.
    • A longer time horizon will generally require a higher return, due to an increased risk in price volatility and increased uncertainty relating to possible outcomes.
    • In terms of long term debt investments, such as long term corporate or government bonds, a longer time horizon gives rise to uncertainties in the potential operations of the debtor entity as well as unforeseen movements in the market as a whole.
    • When uncertainty exists as to when and how business or other conditions will eventuate, flexibility as to the timing of the relevant project is valuable and constitutes optionality.
    • Finally, sequencing options, where management can observe outcomes from a part of a project and resolve some of the uncertainty relating to the venture overall.
  • The bottom line

    • Future-proofing products involves working to insulate products and services from risk and uncertainty by eliminating waste in all phases of a product's life-cycle to: (1) avoid rises in raw material costs, (2) reduce the chances of bad publicity, and (3) prepare for coming changes in environmental legislation.
  • Introduction to inference for linear regression

    • In this section we discuss uncertainty in the estimates of the slope and y-intercept for a regression line.
    • This video introduces consideration of the uncertainty associated with the parameter estimates in linear regression.
  • Other Considerations in Capital Budgeting

    • In other words, it fails to capture managers' flexibility in adapting their decisions to evolving market and technological uncertainty.
    • In an uncertain environment, having the flexibility to decide what to do after some of that uncertainty is resolved has value.
    • A strategic implication of real options theory is that investment will be discouraged by exogenous uncertainty.
    • In other words, the option to defer an investment creates value because exogenous uncertainty can be reduced with the passage of time.
  • Risks Involved in Capital Budgeting

    • Sensitivity analysis is the study of how the uncertainty in the output of a model (numerical or otherwise) can be apportioned to different sources of uncertainty in the model input.
    • A related practice is uncertainty analysis which focuses rather on quantifying uncertainty in model output.
    • Ideally, uncertainty and sensitivity analysis should be run in tandem.
  • Exact Numbers

    • There is a degree of uncertainty any time you measure something.
    • For example, the weight of a particular sample is 0.825 g, but it may actually be 0.828 g or 0.821 g because there is inherent uncertainty involved.
    • On the other hand, because exact numbers are not measured, they have no uncertainty and an infinite numbers of significant figures.
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