PHYSICS 2150 EXPERIMENTAL MODERN PHYSICS. Lecture 3 Statistical vs. Systematic Errors,Rejection of Data; Weighted Averages

Similar documents
PHYSICS 2150 EXPERIMENTAL MODERN PHYSICS. Lecture 3 Rejection of Data; Weighted Averages

High Energy Physics. Lecture 5 The Passage of Particles through Matter

On the Hamiltonian of a Multi-Electron Atom

Classical Magnetic Dipole

Lecture 37 (Schrödinger Equation) Physics Spring 2018 Douglas Fields

The van der Waals interaction 1 D. E. Soper 2 University of Oregon 20 April 2012

PHYSICS 489/1489 LECTURE 7: QUANTUM ELECTRODYNAMICS

The pn junction: 2 Current vs Voltage (IV) characteristics

SCALING OF SYNCHROTRON RADIATION WITH MULTIPOLE ORDER. J. C. Sprott

22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.

Electromagnetism Physics 15b

Why is a E&M nature of light not sufficient to explain experiments?

de/dx Effectively all charged particles except electrons

Unit 7 Charge-to-mass ratio of the electron

Ch. 24 Molecular Reaction Dynamics 1. Collision Theory

Brief Introduction to Statistical Mechanics

As the matrix of operator B is Hermitian so its eigenvalues must be real. It only remains to diagonalize the minor M 11 of matrix B.

E hf. hf c. 2 2 h 2 2 m v f ' f 2f ' f cos c

Forces. Quantum ElectroDynamics. α = = We have now:

PH300 Modern Physics SP11 Final Essay. Up Next: Periodic Table Molecular Bonding

EXST Regression Techniques Page 1

Coupled Pendulums. Two normal modes.

Background: We have discussed the PIB, HO, and the energy of the RR model. In this chapter, the H-atom, and atomic orbitals.

orbiting electron turns out to be wrong even though it Unfortunately, the classical visualization of the

Standard Model - Electroweak Interactions. Standard Model. Outline. Weak Neutral Interactions. Electroweak Theory. Experimental Tests.

Collisions between electrons and ions

Atomic energy levels. Announcements:

Hydrogen Atom and One Electron Ions

Pair (and Triplet) Production Effect:

Higher order derivatives

Derivation of Electron-Electron Interaction Terms in the Multi-Electron Hamiltonian

1.2 Faraday s law A changing magnetic field induces an electric field. Their relation is given by:

Chapter 7b Electron Spin and Spin- Orbit Coupling

DIS-Parity. Search for New Physics Through Parity Violation In Deep Inelastic Electron Scattering. The Physics Case

SPH4U Electric Charges and Electric Fields Mr. LoRusso

Data Assimilation 1. Alan O Neill National Centre for Earth Observation UK

Observer Bias and Reliability By Xunchi Pu

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation.

Chemical Physics II. More Stat. Thermo Kinetics Protein Folding...

A Propagating Wave Packet Group Velocity Dispersion

Intro to Nuclear and Particle Physics (5110)

Radiation Physics Laboratory - Complementary Exercise Set MeBiom 2016/2017

ELECTRON-NEUTRINOS, v e. G. R. Kalbfleisch Brookhaven National Laboratory ABSTRACT

u x v x dx u x v x v x u x dx d u x v x u x v x dx u x v x dx Integration by Parts Formula

Quasi-Classical States of the Simple Harmonic Oscillator

Today. Wave-Matter Duality. Quantum Non-Locality. What is waving for matter waves?

Davisson Germer experiment

The DELPHI experiment at the LEP accelerator at the CERN laboratory

Gradebook & Midterm & Office Hours

Alpha and beta decay equation practice

Math 34A. Final Review

Addition of angular momentum

5.80 Small-Molecule Spectroscopy and Dynamics

Low-energy QED tests (and what we can learn from them)

fiziks Institute for NET/JRF, GATE, IIT JAM, M.Sc. Entrance, JEST, TIFR and GRE in Physics NUCLEAR AND PARTICLE PHYSICS NET/JRF (JUNE-2011)

Chapter 1 Late 1800 s Several failures of classical (Newtonian) physics discovered

Electroweak studies and search for new phenomena at HERA

Pion condensation with neutrinos

MCB137: Physical Biology of the Cell Spring 2017 Homework 6: Ligand binding and the MWC model of allostery (Due 3/23/17)

Partial Derivatives: Suppose that z = f(x, y) is a function of two variables.

BETA DECAY VISUAL PHYSICS ONLINE

INFLUENCE OF GROUND SUBSIDENCE IN THE DAMAGE TO MEXICO CITY S PRIMARY WATER SYSTEM DUE TO THE 1985 EARTHQUAKE

Addition of angular momentum

Contemporary, atomic, nuclear, and particle physics

Maxwellian Collisions

Engineering 323 Beautiful HW #13 Page 1 of 6 Brown Problem 5-12

Relativistic electron microscopy of hadron dynamics

Nuclear reactions The chain reaction

Title: Vibrational structure of electronic transition

Machine Detector Interface Workshop: ILC-SLAC, January 6-8, 2005.

Chapter 8: Electron Configurations and Periodicity

Lecture Outline. Skin Depth Power Flow 8/7/2018. EE 4347 Applied Electromagnetics. Topic 3e

2. Background Material

Exam 1. It is important that you clearly show your work and mark the final answer clearly, closed book, closed notes, no calculator.

Schrodinger Equation in 3-d

PHYS-333: Problem set #2 Solutions

26-Sep-16. Nuclear energy production. Nuclear energy production. Nuclear energy production. Nuclear energy production

Search sequence databases 3 10/25/2016

Neutrino Probes of Dark Energy and Dark Matter

Introduction to the quantum theory of matter and Schrödinger s equation

Physics 43 HW #9 Chapter 40 Key

ELECTRON-MUON SCATTERING

Γ W. (GeV) 3. τ e universality in W decays

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.

Extraction of Doping Density Distributions from C-V Curves

Dealing with quantitative data and problem solving life is a story problem! Attacking Quantitative Problems

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS

Davisson Germer experiment Announcements:

Estimation of the two-photon QED background in Belle II

u r du = ur+1 r + 1 du = ln u + C u sin u du = cos u + C cos u du = sin u + C sec u tan u du = sec u + C e u du = e u + C

Elements of Statistical Thermodynamics

Part 7: Capacitance And Capacitors

Lecture 28 Title: Diatomic Molecule : Vibrational and Rotational spectra

REGISTER!!! The Farmer and the Seeds (a parable of scientific reasoning) Class Updates. The Farmer and the Seeds. The Farmer and the Seeds

Deepak Rajput

Where k is either given or determined from the data and c is an arbitrary constant.

Lecture 19: Free Energies in Modern Computational Statistical Thermodynamics: WHAM and Related Methods

Physics 2D Lecture Slides Lecture 12: Jan 28 th 2004

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018

Chapter. 3 Wave & Particles I

Transcription:

PHYSICS 150 EXPERIMENTAL MODERN PHYSICS Lctur 3 Statistical vs. Systmatic Errors,Rjction of Data; Wightd Avrags

SO FAR WE DISCUSS STATISTICAL UNCERTAINTY. NOW WHAT ABOUT UNCERTAINTY INVOLVED WITH MEASUREMENT ITSELF? (SYSTEMATIC UNCERTAINTY)

ANALYZING ERROR ON A QUANTITY You ar in a car on a bumpy road on a rainy day, and ar trying to masur th lngth of th moving windshild wipr with a shaky rulr. You masur it 37 tims. 1σ rror on man Th histogram of your rsults is at right. It dosn t look vry gaussian. But, with only 37 masurmnts plottd in lots of bins, distributions oftn look ratty.

ANALYZING ERROR ON A QUANTITY Th 1σ uncrtainty on th man is 1.1 cm. If w assum th undrlying distribution is nvrthlss gaussian and cntrd on th tru valu, w can turn this into a confidnc lvl: th wipr lngth is btwn 55.1 and 57.3 cm with 68% confidnc. 1σ rror on man

ANALYZING ERROR ON A QUANTITY Stop th car, go outsid and masur th wipr proprly: it is 61.0 cm long! W said th wipr lngth was btwn 55.1 and 57.3 cm with 68% confidnc. W ar off by ovr 4 sigma. This is shockingly unlikly! Clarly thr is a systmatic shift. Th distribution dos not cntr on th tru valu. Mor data points won t gt us any closr to th tru valu. W nd to mak bttr masurmnts, or find th sourc of th rror and apply a corrction to th data.

STATISTICAL (RANDOM) VS. SYSTEMATIC UNCERTAINTIES Statistical Systmatic No prfrrd dirction Changs with ach data point: taking mor data rducs man. Gaussian modl is usually good (xcpt counting xprimnts) Bias on th masurmnt: Only on dirction Stays th sam for ach masurmnt: mor data won t hlp you Gaussian modl is usually trribl, but w us it anyway

STATISTICAL (RANDOM) VS. SYSTEMATIC UNCERTAINTIES Kp statistical, systmatic rrors sparat. Rport rsults as somthing lik: g = [965 ± 30(stat) ± 1(sys)] cm/s Add in quadratur (not that this assums Gaussian distribution) to compar with known valus: g = [965 ± 3(total)] cm/s

EXAMPLE: E/M EXPERIMENT Elctrons acclratd with 40, 60, or 80V Magntic fild prpndicular to vlocity Lorntz forc F = v B forcs lctrons into circular paths Cntriptal forc: Elctron nrgy: Magntic fild of Hlmholtz coils is This givs F = mv r 1 mv = V m =3.906 Va µ 0 N I r B = 8µ 0NI a 15

m =3.906 Va µ 0 N I r Variabl Dfinition How Dtrmind V Acclrating Potntial masurd a Hlmholtz Coil radius masurd μ0 Prmability of fr spac constant N Numbr of turns in ach coil givn r Elctron bam radius givn I=IT-I0 Nt currnt calculatd IT Total currnt masurd I0 Cancllation currnt masurd Want /m with systmatic and statistical uncrtaintis

DATA FOR m =3.906 Va µ 0 N I r Thr masurmnts of I0={0.17, 0.0, 0.3} I0=0.0±0.03A Comput /m for 14 diffrnt combinations of V and pin radii Entry I (A) r (m) V (V) /m (10 11 C/kg) 1 1.75 0.057 40.08 1.99 0.0509 40.08 3.8 0.0447 40.00 4.67 0.0384 40 1.98 5 3.0 0.031 40 1.97 6.0 0.057 60 1.97 7.49 0.0509 60 1.94 8.85 0.0447 60 1.9 9 3.34 0.0384 60 1.90 10 4.03 0.031 60 1.86 11.58 0.057 80 1.91 1.90 0.0509 80 1.91 13 3.30 0.0447 80 1.88 14 3.39 0.0384 80 1.85

E/M: STATISTICAL UNCERTAINTY Man: x = 1 N Standard dviation: N i=1 x = 1 N 1 Uncrtainty on man: x i =1.946 10 11 C/kg N i=1 (x i x) 1 =0.07 10 11 C/kg x = x N =0.019 1011 C/kg Rsult with statistical uncrtainty only: m =(1.946 ± 0.019) 1011 C/kg

E/M: SYSTEMATIC UNCERTAINTY m =3.906 Va µ 0 N I r Uncrtainty in a powr: q(x) =x n q q = n x x Error propagation givs: m m sys = V V + a a + I I + r r

E/M: SYSTEMATIC UNCERTAINTY m m sys = V V + a a + I I + r r Acclration Voltag: V V 0.1V +0.001 60V = 60V =0.003 Hlmholtz Coil radius: a a = 0.3 cm 33. cm =0.009 Elctron bam radius: r r = 0.00 cm 4.47 cm =0.004

E/M: SYSTEMATIC UNCERTAINTY Nt Currnt: I = I 0 + I T I = ( I T ) +( I 0 ) from statistical uncrtainty: I 0 =0.0 ± 0.03 A from mtr: (0.003 0.A+0.01 A) = 0.011 A I 0 = (0.03 A) + (0.01 A) =0.03 A from mtr: (0.003.85 A + 0.01 A) = 0.019 A I I = (0.03 A) + (0.019 A).65 A =0.013

E/M: SYSTEMATIC UNCERTAINTY m m sys = V V + a a + I I + r r m m sys = 0.003 + ( 0.009) + ( 0.013) + ( 0.004) m m sys =0.033 = 3.3% m sys =0.033 1.946 10 11 C/kg = 0.064 10 11 C/kg

E/M: UNCERTAINTY Statistical: m stat =0.019 10 11 C/kg Systmatical: m sys =0.064 10 11 C/kg (Almost) Final Rsult: m =(1.946 ± 0.019(stat.) ± 0.064(sys.)) 1011 C/kg Final Rsult (significant digits!): m =(1.95 ± 0.0(stat.) ± 0.06(sys.)) 1011 C/kg

E/M: SUMMARY OF RESULTS Masurd Valu: m =(1.95 ± 0.0(stat.) ± 0.06(sys.)) 1011 C/kg Accptd Valu: m = (1.75880088 ± 0.000000039) 1011 C/kg Discrpancy from Accptd Valu: m =(1.95 1.76) 1011 C/kg = 0.19 10 11 C/kg Significanc of Discrpancy: m total = 1.95 0.0 =.8 th rsult is off by.8σ +0.06

HOW GOOD IS OUR RESULT? What is th probability for a valu to dviat mor than.8σ from th man for a Gaussian distribution? Probability that x insid.8! : µ+.8 µ.8 Probability that x outsid.8! : (x µ) dx =0.99489 µ.8 - - - µ µ µ+ µ+.8 1 0.99489 = 0.00511 = 0.51% Vry unlikly rsult This rsult rquirs furthr analysis of possibl rror sourcs

PREVIOUS LECTURE: GAUSS DISTRIBUTION 1.5 p(x µ, )= 1 1 ( x µ ) µ=, σ=0.5 1.0 µ=3, σ=0.5 0.5 µ=4, σ=1 4 6 8

WE CAN NOW ANSWER WHY ERRORS ADD IN QUADRATURE Masur indpndnt quantitis A and B and calculat sum 1.0 p(a µa, σa) 0.8 0.6 p(b µb, σb) 0.4 0. 4 6 8

WHAT IS p(a + B µ A+B, A+B)? Probability to masur A AND B simultanously: p(a µ A, A) p(b µ B, B) 1 ( A µ A A ) 1 ( B µ B B ) 1 h ( A µ A A ) +( B µ B B )i W now hav in fact probability dnsity for A+B and Z: p(a + B,Z µ A + µ B, ( A + B ) 1 ) 1 x o + y p 1 = (x + y) o + p + (px oy) op(o + p) (A+B µ A µ B ) A + B 1 Z (A+B µ A µ B ) A + B 1 Z

HOW ABOUT Z? W only car about A+B, so w intgrat ovr all valus of Z: p(a + B) = p(a + B,z)dz 1 (A+B µ A µ B ) A + B 1 Z dz Probability dnsity for A+B is also a Gaussian p(a + B) = 1 A + B with th standard dviation A+B = A + B 1 (A+B µ A µ B ) A + B

WE CAN NOW ANSWER WHY ERRORS ADD IN QUADRATURE 1.0 p(a µa, σa) A+B = A + B 0.8 0.6 0.4 p(b µb, σb) p(a+b µa+µb, (σb +σb ) 1/ ) 0. 4 6 8 10 1

WE CAN ALSO JUSTIFY THE MEAN BEING THE BEST ESTIMATE Obtain data finit data st x1, x,...,xn and want to find th tru valu X 60 0 p(x)? 0 40 0 0 0 0 0 0 - - - - - -6V -5V -4V -3V -V -1V Elctrostatic Grain Potntial If w would know th limiting distribution p(x), w would also know X, but w don t!

DO WE REALLY NEED THE LIMITING DISTRIBUTION? Lt s assum that th dviation of an individual masurmnt xi from X follows a Gaussian distribution p(x i )= 1 x 1 ( xi X ) Th probability to obtain th data st x1,...,xn is thn p(x 1,x,..., x N )=p(x 1 ) p(x )... p(x N ) 1 N 1 ( x 1 X )... 1 xn X 1 N P 1 N i (x 1 X)

MAXIMUM LIKELIHOOD PRINCIPLE p(x 1,x,..., x N ) 1 N P 1 N i (x 1 X) Which is th most liklist valus for X for our data st x1, x,..., xn? th X for which p(x1, x,..., xn) is maximum p(x1, x,..., xn) is maximum if th xponnt is minimum Nd to find minimum of chi squar : d or dx = N i (x i X)=0 X = 1 N Th man is th bst stimat for X N i=1 N = i=1 x (x i X)

REJECTING DATA DON T!!!!!!! Bst way is to tak mor data!

REJECTING DATA W oftn find suspicious 10 8 6 data points Diffrnt way th data was collctd? 4 Error during data 4 6 8 10 rcording? - It is vr lgitimat to discard thm?

REJECTING DATA B 10 vry carful - you ar trading in th footstps of a long lin of practitionrs of pathological scinc! 8 Thr should b an xtrnal rason for rjcting data! 6 But 4 vn this may not bn nough: Th data may just b in conflict with our xpctation - 4 6 8 10 By rjcting data w may bias th data st and produc bogus rsults

REJECTING DATA 10 8 Thr ar no gnral rcips for rjcting data! 6 4 - All procdurs for rmoving suspicious data ar controvrsial! Will dscrib on which is popular in txtbooks (but not in ral lif): Chauvnt s critrion 4 6 8 10

A CAUTIONARY TALE: HOW TO LOOK FOR A PARTICLE 1.Look in high-nrgy collisions for vnts with multipl output particls that could b dcay products (displacd from primary intraction, if particl is longlivd as with th K 0 ). Thos of you doing th K mson xprimnt hav alrady sn this.rconstruct a rlativistic invariant mass from th momnta of th dcay products.

A CAUTIONARY TALE: HOW TO LOOK FOR A PARTICLE 3.Mak a histogram of th masss from candidat vnts 4.Look for a pak, indicating a stat of wll-dfind mass

A CAUTIONARY TALE: ONE PEAK OR TWO? MV using thir background and rsonanc assumptions, on obtains an accptabl confidnc lvl for th dipol. On also obtains an accptabl dipol fit ovr th whol mass spctrum if on assums a scond-ordr background. Furthrmor, on has to not that th xtrmly crucial background bhavior at both nds of th spctrum is basd on -6 vnts pr 10-MV bin. Th sam procdurs incras th confidnc lvl for a dipol in th p ir+ vnts by a considrabl amount. Asid from statistics and background considrations, on must bar in mind th vry gnral fact that it is much asir not to s a splitting than to s it, bcaus of a varity of rsolution-killing ffcts that ar normally hard to track down, both in countr and bubbl-chambr xprimnts. Exciting nw rsults on th nutral A wr rportd, at th Kiv Intrnational High Enrgy Confrnc in Sptmbr, by T. Massam of th group at CERN hadd by A. Zichichi. In th first rportd obsrvation of th splitting in An, th CERN countr group masurd th rcoil nutron in th chargxchang raction CERN xprimnt in lat 1960s obsrvd A msons 500 - Particl appard to b a a. a. doublt o UJ CO Statistical significanc of split is 400 - vry high 7I-- + p - * n + A at a bam momntum of 3. GV/c. Thy saw a markd dip at th cntr of th Afl. Confidnc lvls for a singl pak, incohrnt doubl pak and dipol wr 1%, 3% and 67% rspctivly. Thr is rally only on particl!! Dpndnc of splitting 300 1. 1.5 1.30 1.35 MISSING MASS (GEV) Fits to th two-pak structur of data from th CERN missing-mass and boson spctromtr group for th A, 1965-68. Th black curv is th fit for two cohrnt To arriv at som conclusions concrning th A splitting w will look for variabls th ffct may dpnd on. Th dpndnc or indpndnc might giv a clu to th natur of th A. W will discuss th possibl dpndnc of th A splitting on four quantitis: bombarding nrgy, final stat, production raction and momntum transfr. Th ffct of symmtric splitting has

A CAUTIONARY TALE: HOW DID THIS HAPPEN? MV using thir background and rsonanc assumptions, on obtains an accptabl confidnc lvl for th dipol. On also obtains an accptabl dipol fit ovr th whol mass spctrum if on assums a scond-ordr background. Furthrmor, on has to not that th xtrmly crucial background bhavior at both nds of th spctrum is basd on -6 vnts pr 10-MV bin. Th sam procdurs incras th confidnc lvl for a dipol in th p ir+ vnts by a considrabl amount. Asid from statistics and background considrations, on must bar in mind th vry gnral fact that it is much asir not to s a splitting than to s it, bcaus of a varity of rsolution-killing ffcts that ar normally hard to track down, both in countr and bubbl-chambr xprimnts. Exciting nw rsults on th nutral A wr rportd, at th Kiv Intrnational High Enrgy Confrnc in Sptmbr, by T. Massam of th group at CERN hadd by A. Zichichi. In th first rportd obsrvation of th splitting in An, th CERN countr group masurd th rcoil nutron in th chargxchang raction In an arly run, a dip showd up. It was a statistical fluctuation, but popl noticd it and suspctd it might b ral. 500 - a. a. Subsqunt runs wr lookd at as o UJ CO 400 - thy cam in. If no dip showd up, th run was invstigatd for problms. Thr s usually a minor problm somwhr in a complicatd xprimnt, so most of ths runs wr cut from th sampl. 7I-- + p - * n + A at a bam momntum of 3. GV/c. Thy saw a markd dip at th cntr of th Afl. Confidnc lvls for a singl pak, incohrnt doubl pak and dipol wr 1%, 3% and 67% rspctivly. Dpndnc of splitting 300 1. 1.5 1.30 1.35 MISSING MASS (GEV) Fits to th two-pak structur of data from th CERN missing-mass and boson spctromtr group for th A, 1965-68. Th black curv is th fit for two cohrnt To arriv at som conclusions concrning th A splitting w will look for variabls th ffct may dpnd on. Th dpndnc or indpndnc might giv a clu to th natur of th A. W will discuss th possibl dpndnc of th A splitting on four quantitis: bombarding nrgy, final stat, production raction and momntum transfr. Th ffct of symmtric splitting has

A CAUTIONARY TALE: HOW DID THIS HAPPEN? MV using thir background and rsonanc assumptions, on obtains an accptabl confidnc lvl for th dipol. On also obtains an accptabl dipol fit ovr th whol mass spctrum if on assums a scond-ordr background. Furthrmor, on has to not that th xtrmly crucial background bhavior at both nds of th spctrum is basd on -6 vnts pr 10-MV bin. Th sam procdurs incras th confidnc lvl for a dipol in th p ir+ vnts by a considrabl amount. Asid from statistics and background considrations, on must bar in mind th vry gnral fact that it is much asir not to s a splitting than to s it, bcaus of a varity of rsolution-killing ffcts that ar normally hard to track down, both in countr and bubbl-chambr xprimnts. Exciting nw rsults on th nutral A wr rportd, at th Kiv Intrnational High Enrgy Confrnc in Sptmbr, by T. Massam of th group at CERN hadd by A. Zichichi. In th first rportd obsrvation of th splitting in An, th CERN countr group masurd th rcoil nutron in th chargxchang raction Whn a dip appard, thy didn t 500 - look as carfully for a problm. a. So an insignificant fluctuation was a. o boostd into a compltly wrong discovry. UJ CO 400-7I-- + p - * n + A at a bam momntum of 3. GV/c. Thy saw a markd dip at th cntr of th Afl. Confidnc lvls for a singl pak, incohrnt doubl pak and dipol wr 1%, 3% and 67% rspctivly. Lsson: Don t lt rsult influnc which data sts you us/want. Dpndnc of splitting 300 1. 1.5 1.30 1.35 MISSING MASS (GEV) Fits to th two-pak structur of data from th CERN missing-mass and boson spctromtr group for th A, 1965-68. Th black curv is th fit for two cohrnt To arriv at som conclusions concrning th A splitting w will look for variabls th ffct may dpnd on. Th dpndnc or indpndnc might giv a clu to th natur of th A. W will discuss th possibl dpndnc of th A splitting on four quantitis: bombarding nrgy, final stat, production raction and momntum transfr. Th ffct of symmtric splitting has