In biostatistics, spectrum bias refers to the phenomenon that the performance of a diagnostic test may vary in different clinical settings because each setting has a different mix of patients. Because the performance may be dependent on the mix of patients, performance at one clinic may not be predictive of performance at another clinic. These differences are interpreted as a kind of bias. Mathematically, the spectrum bias is a sampling bias and not a traditional statistical bias; this has led some authors to refer to the phenomenon as spectrum effects, whilst others maintain it is a bias if the true performance of the test differs from that which is 'expected'. Usually the performance of a diagnostic test is measured in terms of its sensitivity and specificity and it is changes in these that are considered when referring to spectrum bias. However, other performance measures such as the likelihood ratios may also be affected by spectrum bias. Generally spectrum bias is considered to have three causes. The first is due to a change in the case-mix of those patients with the target disorder (disease) and this affects the sensitivity. The second is due to a change in the case-mix of those without the target disorder (disease-free) and this affects the specificity. The third is due to a change in the prevalence, and this affects both the sensitivity and specificity. This final cause is not widely appreciated, but there is mounting empirical evidence as well as theoretical arguments which suggest that it does indeed affect a test's performance. Examples where the sensitivity and specificity change between different sub-groups of patients may be found with the carcinoembryonic antigen test and urinary dipstick tests. Diagnostic test performances reported by some studies may be artificially overestimated if it is a case-control design where a healthy population ('fittest of the fit') is compared with a population with advanced disease ('sickest of the sick'); that is two extreme populations are compared, rather than typical healthy and diseased populations. If properly analyzed, recognition of heterogeneity of subgroups can lead to insights about the test's performance in varying populations. (Wikipedia).
Physics demonstrations. Polarisation of light
Only transverse waves can be polarised, this video explains why. It also shows why sunglasses are known as polaroids and how you can test this yourself on a sunny day.
From playlist WAVES
Polarised light and uses: fizzics.org
The video explains what polarised light is, the effects it can cause and some of the applications. Notes can be downloaded from the associated website at https://www.fizzics.org/using-polarised-waves/
From playlist The electromagnetic spectrum and waves
Physics demonstrations. Polarisation of microwaves
This video shows how you can use a microwave transmitter and receiver to investigate the polarisation of microwaves. Plane polarised waves are emitted by the transmitter and If you measure the angle of the filter and record the intensity at the receiver you can then show.
From playlist WAVES
Episode 3 of 5 Check us out on iTunes! http://dne.ws/1NixUds Please Subscribe! http://testu.be/1FjtHn5 Human perception of light is extremely limited. From gamma rays to radio waves what we see is only a sliver of the electromagnetic spectrum. + + + + + + + + Previous Episode: We Sti
From playlist Light And The Human Experience
Teach Astronomy - Electromagnetic Spectrum
http://www.teachastronomy.com/ The visible spectrum of light is just a small sliver in an enormously broad spectrum of radiation called the electromagnetic spectrum. The electromagnetic spectrum ranges through an array of wavelengths that span fifteen orders of magnitudes or decades. The
From playlist 06. Optics and Quantum Theory
Physics - Optics: Single Slit Diffraction (6 of 15) What Causes Intensity Diffraction Patterns?
Visit http://ilectureonline.com for more math and science lectures! In this video I will conceptually explain the intensity cause by diffraction patterns. Next video in series: http://youtu.be/OuaPzAN67fw
From playlist PHYSICS 61 DIFFRACTION OF LIGHT
Light and Optics 7_2 Interference
Out of phase waves lead to interference.
From playlist Physics - Light and Optics
Teach Astronomy - Doppler Effect
http://www.teachastronomy.com/ The Doppler Effect is the shift of wavelength or frequency of a source of waves due to the motion of that source of waves. Doppler Effect is most familiar in terms of sound waves. As a source of sound, such as a siren, approaches you, the pitch or frequency
From playlist 06. Optics and Quantum Theory
Introduction to Frequency Selective Filtering
http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Separation of signals based on frequency content using lowpass, highpass, bandpass, etc filters. Filter g
From playlist Introduction to Filter Design
Galaxy Bias Loops - R. Scoccimarro - Workshop 1 - CEB T3 2018
Roman Scoccimarro (NYU) / 21.09.2018 Galaxy Bias Loops ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/ Twitter : https://twitter.com/InHenriPoincare Instagram : h
From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology
Measurement of Galaxy Bias from the Three-Point Function - Chi-Ting Chiang
Chi-Ting Chiang - September 24, 2015 http://sns.ias.edu/~baldauf/Bias/index.html The interpretation of low-redshift galaxy surveys is more complicated than the interpretation of CMB temperature anisotropies. First, the matter distribution evolves nonlinearly at low redshift, limiting the
From playlist Unbiased Cosmology from Biased Tracers
Galaxy Bias Loops by Roman Scoccimarro
Program Cosmology - The Next Decade ORGANIZERS : Rishi Khatri, Subha Majumdar and Aseem Paranjape DATE : 03 January 2019 to 25 January 2019 VENUE : Ramanujan Lecture Hall, ICTS Bangalore The great observational progress in cosmology has revealed some very intriguing puzzles, the most i
From playlist Cosmology - The Next Decade
Galaxy bias and its implications for forward models (...) - F. Schmidt - Workshop 1 - CEB T3 2018
Fabian Schmidt (MPA) / 21.09.2018 Galaxy bias and its implications for forward models of the large-scale structure ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/
From playlist 2018 - T3 - Analytics, Inference, and Computation in Cosmology
Power Spectrum Estimation Examples: Welch's Method
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Examples of applying Welch's method to estimate power spectrum highlighting the tradeoffs between bias and variance that are associated with s
From playlist Estimation and Detection Theory
Cosmology with LSS (Lecture 2) by John Peacock
Program Cosmology - The Next Decade ORGANIZERS : Rishi Khatri, Subha Majumdar and Aseem Paranjape DATE : 03 January 2019 to 25 January 2019 VENUE : Ramanujan Lecture Hall, ICTS Bangalore The great observational progress in cosmology has revealed some very intriguing puzzles, the most i
From playlist Cosmology - The Next Decade
Welch's Method: The Averaged Periodogram
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Poor variance properties of the periodogram motivate averaging methods for estimating the power spectrum. In Welch's method the data is partit
From playlist Estimation and Detection Theory
Cosmology with LSS (Lecture 1) by John Peacock
Program Cosmology - The Next Decade ORGANIZERS : Rishi Khatri, Subha Majumdar and Aseem Paranjape DATE : 03 January 2019 to 25 January 2019 VENUE : Ramanujan Lecture Hall, ICTS Bangalore The great observational progress in cosmology has revealed some very intriguing puzzles, the most i
From playlist Cosmology - The Next Decade
Anna Little - Unbiasing Procedures for Scale-invariant Multi-reference Alignment - IPAM at UCLA
Recorded 28 November 2022. Anna Little of the University of Utah presents "Unbiasing Procedures for Scale-invariant Multi-reference Alignment" at IPAM's Multi-Modal Imaging with Deep Learning and Modeling Workshop. Abstract: Recent advances in applications such as cryo-electron microscopy
From playlist 2022 Multi-Modal Imaging with Deep Learning and Modeling
Halo Bias Beyond CDM - Marilena LoVerde
Marilena LoVerde - September 25, 2015 http://sns.ias.edu/~baldauf/Bias/program.html The interpretation of low-redshift galaxy surveys is more complicated than the interpretation of CMB temperature anisotropies. First, the matter distribution evolves nonlinearly at low redshift, limiting
From playlist Unbiased Cosmology from Biased Tracers
Teach Astronomy - Visual Magnitude
http://www.teachastronomy.com/ Apparent magnitude or apparent brightness must be specified at a particular wavelength. Stars have different colors or different energy distributions, so the apparent brightness depends on the wavelength of observation. Traditionally, astronomy is done by e
From playlist 14. Stars