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Related Concept Videos

Local Maximum and Minimum Values01:31

Local Maximum and Minimum Values

In multivariable calculus, a function of two variables can exhibit local maximum or minimum values at certain points on its surface. A local maximum occurs when the function's value at a point is greater than at all nearby points, while a local minimum occurs when the function’s value is less than at all nearby locations. These points are referred to as local extrema and are of central importance in optimization problems.Local extrema are found at critical points, where the surface becomes...
Unusual Results01:16

Unusual Results

Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
According to the range rule of thumb, any value above or below two standard deviations, 2σ  from the mean, μ  is considered unusual.
Maximum unusual value = μ + 2σ
Minimum unusual value...
Range00:59

Range

The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This number is...
Maximum Size of Aggregate01:12

Maximum Size of Aggregate

The maximum size of aggregate is defined as the aperture of the sieve retaining 15 percent or more of the particles present in the aggregate sample. The aggregate's maximum size impacts the concrete's water requirement, workability, and strength. Larger aggregates reduce the surface area needing cement paste coverage, which can lower water needs, thereby allowing a decrease in the water-to-cement ratio when the desired workability and richness of the mix are to be maintained, which can result...
Critical Numbers and the Closed Interval Method01:21

Critical Numbers and the Closed Interval Method

Understanding the maximum and minimum values of a function is essential for analyzing its overall behavior. These values, often referred to as extrema, provide insight into how a function behaves across its domain. In mathematical terms, extrema can be either local—representing peaks and valleys within a limited region—or absolute, indicating the highest or lowest points over an entire interval.A function’s extrema occur at critical numbers, which are values in the domain where the derivative...

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Related Experiment Video

Updated: Jun 24, 2026

Design and Optimization Strategies of a High-Performance Vented Box
14:23

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Published on: June 9, 2023

Benchmarking for maximum value.

Ed Baldwin1

  • 1EC Harris LLP.

Health Estate
|April 7, 2009
PubMed
Summary
This summary is machine-generated.

Benchmarking and market-testing are key to evaluating hard and soft facilities management (FM) services in PFI healthcare schemes. These methods ensure maximum value for money and optimal quality in healthcare infrastructure.

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Area of Science:

  • Healthcare management
  • Infrastructure evaluation
  • Public-Private Partnerships

Background:

  • Private Finance Initiative (PFI) schemes are widely used for healthcare infrastructure development.
  • Ensuring the quality and cost-effectiveness of facilities management (FM) services within these schemes is crucial.
  • Evaluating FM services requires robust methodologies to guarantee value for money.

Purpose of the Study:

  • To examine the role of benchmarking in assessing FM services under PFI healthcare schemes.
  • To investigate the application of market-testing for evaluating hard and soft FM services.
  • To ensure optimal value for money and quality in PFI healthcare facilities.

Main Methods:

  • Benchmarking of FM service quality and cost.
  • Market-testing of hard and soft FM services.
  • Evaluation of PFI healthcare schemes.

Main Results:

  • Benchmarking provides a framework for assessing FM service performance.
  • Market-testing identifies opportunities for cost savings and quality improvements.
  • These methods are essential for maximizing value in PFI healthcare contracts.

Conclusions:

  • Benchmarking and market-testing are vital tools for PFI healthcare FM services.
  • Effective evaluation ensures services meet quality standards and financial targets.
  • Continuous assessment is necessary for sustained value and performance.