uncertainty

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.