Carrier Action under Perturbation

Size: px
Start display at page:

Download "Carrier Action under Perturbation"

Transcription

1 Carrer Acto uder Perturbato Eulbrum: o curret ad o formato ca be represeted. Ferm-level s flat! Perturbato s ecessary to artfcally ecode formato perturbed states: electrc feld (drft), cocetrato gradet (dffuso), temperature gradet (thermal dffuso) ad excess carrers (R-G), ad radato (photoelectrc R-G). Ferm-level s ot flat! Drft curret: whe the carrers semcoductor s uder eulbrum, all radom moto k (phase) space s exactly cacelled: o curret flowg ad the system has a costat Ferm eergy However, whe there s a electrc feld F, the forward moto s preferred amog all radomzg scatterg: a skew dstrbuto Electros fucto of k space wll result et curret. dv dk wth all sort F m h ef eergy k y k y dt dt below E F eft F kt () k(0) move all h drectos. k x k x v0 Ferm sphere at t0 Ferm sphere at t Chapter

2 Quas Ferm Levels Whe we dsturb our system from eulbrum, our mathematcal treatmet wll employ aother cocept Quas Ferm level. Smlar to the Ferm-level used descrbg the occupato probablty eulbrum, uas Ferm-level s used to descrbe the carrer occupato probablty uder o-eulbrum codto. uder eulbrum, p ; uder o-eulbrum p E F splts to E FN ad E FP where E FN ad E FP follow the carrer relatoshp: EFN E c ( EFN Ec )/ kbt ( EFN E )/ kbt Nc F/ Nce e f Ec EFN 3kBT π kt B Ev E FP ( Ev EFP) / kbt ( Ev EFP) / kbt p Nv F/ Nve e f EFP Ev 3kBT π kt B Chapter

3 Drft Velocty ad Carrer Moblty J p drft p v p p μ p F wth v p μ p F J drft - v μ F wth v -μ F The moblty μ s the ut of cm /Vs ad s the same as the Ohm s law. Actual pcture s: accelerato, scatterg J drft (p μ p + μ )F A L J drft (/ρ) A L F ρ L I (A/ρ L) VR V μ + pμ p Moblty aga takes to accout all QM scatterg processes E < τ > F E a v a< τ > E μe * * m m l where < τ > s the mea tme betwee collso ν Chapter th 3 A

4 Carrer Scatterg The major scatterg evets semcoductors: phoo scatterg (lattce vbrato) mpurty scatterg (ozed ad eutral mpurty) surface scatterg (termato of perodc potetal) Matthesse s rule: μ total μ phoo + μ mpurty + μ surface +... μ μ mpurty σ Moblty reducto μ total Dopat freeze-out μ phoo T T Chapter 4

5 Hgh-feld Moblty: Velocty Saturato Velocty Saturato: pheomeologcal expressos, sce the physcal effects behd the velocty saturato s too complex to gve good physcal fuctos drectly optcal phoo scatterg s stroger whe the carrer has larger ketc eergy. May popular semcoductors have velocty saturato aroud 0 7 cm/s (/3,000 of speed of lght) μ μ 0 / ( + (μ 0 F/v sat ) β ) /β, where v sat s the saturato velocty coducto moblty s derved from the effectve mass of coducto ad the mea free tme of collso. For S, μ 360 cm /Vs ad μ p 460 cm /Vs at room temperature for trsc samples v drft v sat μ F Chapter 5 F

6 Dffuso - Fck s Frst Law F F C(l) C(0) C(-l) X0 F: Flux; ½ represets eual probablty to move to left or rght C(x,t): cocetrato V th : thermal velocty l: mea free path F C ( l ) vth F C () l vth F F [ ] F vth C( l) C( l) Cxt (, ) Cxt (, ) vth C(0) l C(0) l x + x Cxt (,) Cxt (,) vl th D x x Taylor seres D s dffuso coeffcet Chapter 6

7 Dffuso (Perturbato from Carrer Numbers) Carrer dffuso J pdff - D p p; J dff D D, D p are dffuso coeffcet wth uts of cm /s Thermal dffuso J ptdff - p D Tp T; J Tdff D T T; to tell the type of carrer coducto, ether thermal or Halleffect duced curret has to be used. Carrer Curret Euatos: J p J pdrft + J pdff + J ptdff pμ p F - D p p - p D Tp T J J drft + J dff + J Tdff μ F + D + D T T If oly homogeeous lattce temperature s cosdered, the eulbrum codto AND Boltzma statstcs (odegeerate cases) wll result the Eeste relatoshp betwee μ ad D Chapter 7

8 Este Relato < τ > μ m D ν l th D μ * * m ν * th l mν th From K.E. a oe-dmesoal case, * mν th kt Therefore, D μ kt Chapter 8

9 Este Relato The electrc feld F ca be cosdered as bad bedg (except whe there s heterojucto): F / E / E C / E V For homogeeous T, eulbrum -D, o-degeerate dopg e ( E E )/ k T F B d de de dx k T dx dx B F D μ Dp μ p kt B d de de de J F D F dx dx dx dx F F N 0 μ + μ μ μ I eulbrum de F /dx 0; Ferm-level s flat! Out of eulbrum de F /dx 0 def E EF EFp 0 J μ ψf 0 ψf dx Chapter 9 F

10 Electro-Hole Par Geerato-Recombato Fck slaw for carrer coservato (or the cotuty euato): v J + G R p(x)v t d A p(x+dx) v d A p v J p + Gp Rp t G p R The geerato-recombato evets semcoductors ca be categorzed by bad-to-bad, bad-to-trap ad trap-to-trap. The reured coservato of total mometum ad eergy wll be completed by teracto wth phoos (thermal), photos (lght) or aother carrer (mpact ozato ad Auger recombato) Remember that traps are localzed allowable states wth the badgap for electros ad/or holes. Sce trap states are local space, they caot cause drft curret drectly, but ther charge states wll affect the Posso euato ad cotuty euatos Chapter 0

11 Category of Geerato-Recombato Geerato- Recombato bad-to-bad bad-to-trap trap-to-trap thermal optcal carrer (elec. capture) (elec. capture) (chage locato) (trap hoppg/tuelg) (chage eergy) (mpact ozato) Photos have large eergy but small mometum, ot effectve for drect badgap Phoos have small eergy (kt/) but large mometum, ot effectve for.ev badgap Trap asssted geeratorecombato s most effcet at mdgap (Au, Cu, M, Cr, Fe S) Chapter

12 Shockley-Read-Hall (SRH) processes Two thermal bad-to-trap processes that complete a bad-to-bad electro-hole par geerato or recombato are called SRH (Shockley-Read-Hall) processes, whch s most mportat S. p p cnp cnp ep p cnp t t p p T 0 p T p T T p T C E T 0 Capture rate s proportoal to the umber of carrers (p), umber of traps (N T ) ad capture coeffcet (c p ), whch has the ut of a cross secto (cm ) the thermal velocty (cm/s). I eulbrum, geerato has to cacel recombato (detaled balace). Off eulbrum, the et geerato-recombato s the: p t R G c p N T ( p p0) c A more geeral expresso preservg the low-jecto lmt: p N T 0 Δp Δp τ p Detal balace t R G Δ τ p t R G t R G p τ ( + ) + τ ( p + p p ) e ( E T E ) / kt p e ( E E T ) / kt Chapter

13 Sx Shockley Euatos of States Most classcal devce models are derved from these euatos Frst put together by Wllam Shockley for semcoductor classcal devce aalyss (o QM effects such as tuelg yet) ρ ψ ( ψ) F ε Posso E. curvature + + ε ε s J μ F + D p p p 0 J pμ F D p v J + G R t p v J + G R t p t t t ( + p N ) D NA T p p p T Chapter 3 R G R G Elec. Curret E. Hole Curret E. Elec. Cotuty E. Hole Cotuty E. Trap Charge E.

14 Posso Euato ad Bad Bedg Majorty charge dstrbuto ρ(x) s perturbed. E E c E F E E v x E E c E F E E v x e Ne c ( E E )/ k T F B ( E E )/ k T c F B I -D, E ψ E : eletrostatc (electro) eergy + + p N + N + ( N ) ψ ( ) dx s d x ( ) ψ ε ε ε ε D A T D 0 s 0 ε ε ( ψ( x) ψf )/ kbt ( e ND) Chapter s 0 4

15 The Debye Legth from the Posso Euato d ψ ( x) ( ψ( x) ψf )/ kbt ( e ND) dx εsε0 d ( ψ( x) ψ( )) ( ( x) ( ))/ kbt ( ( ) F )/ kbt ( ) ψ ψ ψ ψ e e ND dx εsε0 d Δψ ND ( )/ kbt ( ) e Δψ dx εsε0 L D s the Debye legth. It takes L D to resolve the potetal perturbato from the chage et majorty charge. For example, L D 0.04μm for N D 0 6 cm -3 S. Chapter 5 E E c E F E E v x e Ne c ( E E )/ k T F B ( E E )/ k T c F B Assume ( Ψ )/k B T << Ψ << k B T/ uas-eutralty codto Expad the expoetal fucto a Taylor seres ad stop after the secod term. d Δψ N N Δ Δψ dx kt kt D D ( ψ ) εsε0 B εsε0 B x Δψ exp LD LD εsε0kt B N D

16 Delectrc Relaxato Tme I -D -type materals, there s a small charge desty dsturbace ad we ow wat to fd out about how log t takes to reestablsh a steady state Cotuty E. Δ J t x J F+ D x Curret E. μ Posso E. F x Δ ε ε s 0 F ρ Ψ << kbt/ uas-eutralty codto (t) exp(-t/ρ ε s ε 0 ), where ρ ε s ε 0 s called the delectrc relaxato tme, or the majorty-carrer respose tme, ad s typcally < 0 - s. Chapter 6

17 Dffuso Legth ad Morty Carrer Lfetme I -D p-type materals, the morty carrers ( 0 /N A ) t J x ( ) τ 0 J μ F + D If J s eglgble (o carrer jecto), the morty carrer decays the order of τ (morty carrer lfetme), 0-4 to 0-9 s depedg o the ualty of the slco crystal. I steady state (o tme varato, costat jecto) ad the drft curret s small for morty carrers exp(-x/l) wth L(D τ ) / beg the dffuso legth (usually o the order of 0-00μm S). x Chapter 7

18 Tme ad Legth Scale Semcoductor For electro: Debye Legth Delectrc Relaxato Tme τ Morty Carrer Lfetme τ Dffuso Legth L D L εsε0kt B N Dτ D ρ ε ε D s 0 ~ m majorty carrer ~ ps > μs > μm morty carrer L Dτ D D I both majorty ad morty carrer cases, the tmes ad legths gve the umbers for how fast a devato from the carrer eulbrum wll be eualzed ad over whch dstaces small devatos are felt. Chapter 8

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon EE105 - Srg 007 Mcroelectroc Devces ad Crcuts Perodc Table of Elemets Lecture Semcoductor Bascs Electroc Proertes of Slco Slco s Grou IV (atomc umber 14) Atom electroc structure: 1s s 6 3s 3 Crystal electroc

More information

Diode DC Non-ideal Characteristics

Diode DC Non-ideal Characteristics Dode DC No-deal Characterstcs - e qv/kt V reverse curret ot saturated (geerato the deleto rego) dode breakdow 2 3 recombato the deleto rego l( ) 5 hgh-level jecto of morty carrers l( ) sloeq/ηkt V η η2

More information

Semiconductor Device Physics

Semiconductor Device Physics 1 Semcoductor evce Physcs Lecture 7 htt://ztomul.wordress.com 0 1 3 Semcoductor evce Physcs Chater 6 Jucto odes: I-V Characterstcs 3 Chater 6 Jucto odes: I-V Characterstcs Qualtatve ervato Majorty carrers

More information

Solid State Device Fundamentals

Solid State Device Fundamentals Sold State Devce Fudametals 9 polar jucto trasstor Sold State Devce Fudametals 9. polar Jucto Trasstor NS 345 Lecture ourse by Alexader M. Zatsev alexader.zatsev@cs.cuy.edu Tel: 718 98 81 4N101b Departmet

More information

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013 ECE 595, Secto 0 Numercal Smulatos Lecture 9: FEM for Electroc Trasport Prof. Peter Bermel February, 03 Outle Recap from Wedesday Physcs-based devce modelg Electroc trasport theory FEM electroc trasport

More information

The E vs k diagrams are in general a function of the k -space direction in a crystal

The E vs k diagrams are in general a function of the k -space direction in a crystal vs dagram p m m he parameter s called the crystal mometum ad s a parameter that results from applyg Schrödger wave equato to a sgle-crystal lattce. lectros travelg dfferet drectos ecouter dfferet potetal

More information

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical ECE66: Sold State Devces Lecture 13 Solutos of the Cotuty Eqs. Aalytcal & Numercal Gerhard Klmeck gekco@purdue.edu Outle Aalytcal Solutos to the Cotuty Equatos 1) Example problems ) Summary Numercal Solutos

More information

UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES. Midterm I

UNIVERSITY OF CALIFORNIA, BERKELEY DEPARTMENT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES. Midterm I UNIVERSITY OF CALIFORNIA, BERKELEY EPARTMENT OF ELECTRICAL ENGINEERING AN COMPUTER SCIENCES EECS 130 Professor Chemg Hu Fall 009 Mdterm I Name: Closed book. Oe sheet of otes s allowed. There are 8 pages

More information

Space charge. Lecture 8 09/11/2011. p-n junction with gradient. p-n junction with gradient. V. p-n junction. Space charge

Space charge. Lecture 8 09/11/2011. p-n junction with gradient. p-n junction with gradient. V. p-n junction. Space charge ecture 8 09/11/011 Sace charge. - jucto Sace charge th a gradet Out of equlbrum Sace charge -tye ad -tye regos Usually N >>N A thus q N x = N A /(N +N A x = N /(N +N A A ad x = The sace charge exteds towards

More information

Lecture #13. Diode Current due to Generation

Lecture #13. Diode Current due to Generation Lecture #13 Juctos OUTLINE reverse bas curret devatos from deal behavor small-sgal model Readg: Chaters 6. & 7 EE13 Lecture 13, Slde 1 Dode Curret due to Geerato If a electro-hole ar s geerated (e.g. by

More information

EE105 - Fall 2006 Microelectronic Devices and Circuits. Your EECS105 Week

EE105 - Fall 2006 Microelectronic Devices and Circuits. Your EECS105 Week EE15 - Fall 6 Mcroelectroc Devces a Crcuts Prof. Ja M. Rabaey (ja@eecs) Lecture : Semcouctor Bascs Your EECS15 Week Mo Tu We Th Fr 9am 1am Lab 353 Cory Lab 353 Cory Lab 353 Cory 11am Dscusso 93 Cory 1pm

More information

6.4.5 MOS capacitance-voltage analysis

6.4.5 MOS capacitance-voltage analysis 6.4.5 MOS capactace-voltage aalyss arous parameters of a MOS devce ca be determed from the - characterstcs.. Type of substrate dopg. Isulator capactace = /d sulator thckess d 3. The mmum depleto capactace

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

( ) Thermal noise ktb (T is absolute temperature in kelvin, B is bandwidth, k is Boltzamann s constant) Shot noise

( ) Thermal noise ktb (T is absolute temperature in kelvin, B is bandwidth, k is Boltzamann s constant) Shot noise OISE Thermal oe ktb (T abolute temperature kelv, B badwdth, k Boltzama cotat) 3 k.38 0 joule / kelv ( joule /ecod watt) ( ) v ( freq) 4kTB Thermal oe refer to the ketc eergy of a body of partcle a a reult

More information

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law Module : The equato of cotuty Lecture 5: Coservato of Mass for each speces & Fck s Law NPTEL, IIT Kharagpur, Prof. Sakat Chakraborty, Departmet of Chemcal Egeerg 2 Basc Deftos I Mass Trasfer, we usually

More information

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits Block-Based Compact hermal Modelg of Semcoductor Itegrated Crcuts Master s hess Defese Caddate: Jg Ba Commttee Members: Dr. Mg-Cheg Cheg Dr. Daqg Hou Dr. Robert Schllg July 27, 2009 Outle Itroducto Backgroud

More information

Homework #2 Solutions, EE/MSE 486, Spring 2017 Problem 1:

Homework #2 Solutions, EE/MSE 486, Spring 2017 Problem 1: Homework # Solutos, EE/MSE 486, Sprg 017 Problem 1: P o p N N A ( N N A) Here / for type dopg; 4 p p N A N ( N A N) / for p type dog. 4 At 1000C, 3.1*10 16 3/ From the table the otes, we have T 0.603eV

More information

Third handout: On the Gini Index

Third handout: On the Gini Index Thrd hadout: O the dex Corrado, a tala statstca, proposed (, 9, 96) to measure absolute equalt va the mea dfferece whch s defed as ( / ) where refers to the total umber of dvduals socet. Assume that. The

More information

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution: Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed

More information

We have already referred to a certain reaction, which takes place at high temperature after rich combustion.

We have already referred to a certain reaction, which takes place at high temperature after rich combustion. ME 41 Day 13 Topcs Chemcal Equlbrum - Theory Chemcal Equlbrum Example #1 Equlbrum Costats Chemcal Equlbrum Example #2 Chemcal Equlbrum of Hot Bured Gas 1. Chemcal Equlbrum We have already referred to a

More information

Introduction. Free Electron Fermi Gas. Energy Levels in One Dimension

Introduction. Free Electron Fermi Gas. Energy Levels in One Dimension ree Electro er Gas Eergy Levels Oe Deso Effect of eperature o the er-drac Dstrbuto ree Electro Gas hree Desos Heat Capacty of the Electro Gas Electrcal Coductvty ad Oh s Law Moto Magetc elds heral Coductvty

More information

Physics 114 Exam 2 Fall Name:

Physics 114 Exam 2 Fall Name: Physcs 114 Exam Fall 015 Name: For gradg purposes (do ot wrte here): Questo 1. 1... 3. 3. Problem Aswer each of the followg questos. Pots for each questo are dcated red. Uless otherwse dcated, the amout

More information

ECE606: Solid State Devices Lecture 11 Interface States Recombination Carrier Transport

ECE606: Solid State Devices Lecture 11 Interface States Recombination Carrier Transport C606: Sold State eves Leture Iterfae States Reombato Carrer Trasport Gerhard Klmek geko@purdue.edu Outle ) SRH formula adapted to terfae states ) Surfae reombato depleto rego 3) Coluso Surfae Reombato

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

Arithmetic Mean Suppose there is only a finite number N of items in the system of interest. Then the population arithmetic mean is

Arithmetic Mean Suppose there is only a finite number N of items in the system of interest. Then the population arithmetic mean is Topc : Probablty Theory Module : Descrptve Statstcs Measures of Locato Descrptve statstcs are measures of locato ad shape that perta to probablty dstrbutos The prmary measures of locato are the arthmetc

More information

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

More information

PHYS Look over. examples 2, 3, 4, 6, 7, 8,9, 10 and 11. How To Make Physics Pay PHYS Look over. Examples: 1, 4, 5, 6, 7, 8, 9, 10,

PHYS Look over. examples 2, 3, 4, 6, 7, 8,9, 10 and 11. How To Make Physics Pay PHYS Look over. Examples: 1, 4, 5, 6, 7, 8, 9, 10, PHYS Look over Chapter 9 Sectos - Eamples:, 4, 5, 6, 7, 8, 9, 0, PHYS Look over Chapter 7 Sectos -8 8, 0 eamples, 3, 4, 6, 7, 8,9, 0 ad How To ake Phscs Pa We wll ow look at a wa of calculatg where the

More information

Ellipsometry Overview

Ellipsometry Overview llpsometry Overvew ~ R Δ p ρ = ta( Ψ) e = ~ Rs ñ(λ) = (λ) + k(λ) ε = ñ 2 p-plae s-plae p-plae plae of cdece s-plae llpsometry buldg-blocks Lght ad Polarzato Materals / Optcal Costats Iteracto of Lght wth

More information

Lecture 3. Sampling, sampling distributions, and parameter estimation

Lecture 3. Sampling, sampling distributions, and parameter estimation Lecture 3 Samplg, samplg dstrbutos, ad parameter estmato Samplg Defto Populato s defed as the collecto of all the possble observatos of terest. The collecto of observatos we take from the populato s called

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

Lecture 7: Properties of Materials for Integrated Circuits Context

Lecture 7: Properties of Materials for Integrated Circuits Context Lecture 7: Propertes of Materals for Itegrate Crcuts Cotext Over the last two weeks, we revewe: Basc passve compoets Capactors Resstors Iuctors Lear crcut moels Phasor otato Trasfer fuctos Boe plots 1

More information

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations HP 30S Statstcs Averages ad Stadard Devatos Average ad Stadard Devato Practce Fdg Averages ad Stadard Devatos HP 30S Statstcs Averages ad Stadard Devatos Average ad stadard devato The HP 30S provdes several

More information

Long Tailed functions

Long Tailed functions Log Taled fuctos Log tal fuctos are desrable for fttg may physologcal data sets A geeral example s fttg the respose of a system to a mpulse put Most passve systems have u modal rght skewed respose fuctos

More information

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems Char for Network Archtectures ad Servces Prof. Carle Departmet of Computer Scece U Müche Aalyss of System Performace IN2072 Chapter 5 Aalyss of No Markov Systems Dr. Alexader Kle Prof. Dr.-Ig. Georg Carle

More information

MOLECULAR VIBRATIONS

MOLECULAR VIBRATIONS MOLECULAR VIBRATIONS Here we wsh to vestgate molecular vbratos ad draw a smlarty betwee the theory of molecular vbratos ad Hückel theory. 1. Smple Harmoc Oscllator Recall that the eergy of a oe-dmesoal

More information

Lecture 2 - What are component and system reliability and how it can be improved?

Lecture 2 - What are component and system reliability and how it can be improved? Lecture 2 - What are compoet ad system relablty ad how t ca be mproved? Relablty s a measure of the qualty of the product over the log ru. The cocept of relablty s a exteded tme perod over whch the expected

More information

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

More information

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR Pot Patter Aalyss Part I Outle Revst IRP/CSR, frst- ad secod order effects What s pot patter aalyss (PPA)? Desty-based pot patter measures Dstace-based pot patter measures Revst IRP/CSR Equal probablty:

More information

Section l h l Stem=Tens. 8l Leaf=Ones. 8h l 03. 9h 58

Section l h l Stem=Tens. 8l Leaf=Ones. 8h l 03. 9h 58 Secto.. 6l 34 6h 667899 7l 44 7h Stem=Tes 8l 344 Leaf=Oes 8h 5557899 9l 3 9h 58 Ths dsplay brgs out the gap the data: There are o scores the hgh 7's. 6. a. beams cylders 9 5 8 88533 6 6 98877643 7 488

More information

External Electric Field Influence on Charge Carriers and Electrical Parameters of Polycrystalline Silicon Solar Cell

External Electric Field Influence on Charge Carriers and Electrical Parameters of Polycrystalline Silicon Solar Cell Research Joural of Appled ceces, Egeerg ad Techology 4(17: 967-97, 1 IN: 4-7467 Maxwell cetfc Orgazato, 1 ubmtted: ecember, 11 Accepted: Jauary 1, 1 Publshed: eptember 1, 1 Exteral Electrc Feld Ifluece

More information

Chapter 2 Motion and Recombination of Electrons and Holes

Chapter 2 Motion and Recombination of Electrons and Holes Chapter 2 Motio ad Recombiatio of Electros ad Holes 2.1 Thermal Eergy ad Thermal Velocity Average electro or hole kietic eergy 3 2 kt 1 2 2 mv th v th 3kT m eff 3 23 1.38 10 JK 0.26 9.1 10 1 31 300 kg

More information

Econometric Methods. Review of Estimation

Econometric Methods. Review of Estimation Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators

More information

Simple Linear Regression

Simple Linear Regression Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato

More information

Analysis of Variance with Weibull Data

Analysis of Variance with Weibull Data Aalyss of Varace wth Webull Data Lahaa Watthaacheewaul Abstract I statstcal data aalyss by aalyss of varace, the usual basc assumptos are that the model s addtve ad the errors are radomly, depedetly, ad

More information

1. MOS: Device Operation and Large Signal Model

1. MOS: Device Operation and Large Signal Model 1. MOS: ece Oerato ad arge Sgal Model Readg: Sedra & Smth Sec. 5.1-5.3 (S&S 5 th Ed: Sec. 4.1-4.3) ECE 10, Fall 011, F. Najmabad Oeratoal Bass of a Feld-Effect Trasstor (1) Cosder the hyothetcal semcoductor

More information

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace

More information

THE ROYAL STATISTICAL SOCIETY HIGHER CERTIFICATE

THE ROYAL STATISTICAL SOCIETY HIGHER CERTIFICATE THE ROYAL STATISTICAL SOCIETY 00 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE PAPER I STATISTICAL THEORY The Socety provdes these solutos to assst caddates preparg for the examatos future years ad for the

More information

D. VQ WITH 1ST-ORDER LOSSLESS CODING

D. VQ WITH 1ST-ORDER LOSSLESS CODING VARIABLE-RATE VQ (AKA VQ WITH ENTROPY CODING) Varable-Rate VQ = Quatzato + Lossless Varable-Legth Bary Codg A rage of optos -- from smple to complex A. Uform scalar quatzato wth varable-legth codg, oe

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

STA 108 Applied Linear Models: Regression Analysis Spring Solution for Homework #1

STA 108 Applied Linear Models: Regression Analysis Spring Solution for Homework #1 STA 08 Appled Lear Models: Regresso Aalyss Sprg 0 Soluto for Homework #. Let Y the dollar cost per year, X the umber of vsts per year. The the mathematcal relato betwee X ad Y s: Y 300 + X. Ths s a fuctoal

More information

A New Measure of Probabilistic Entropy. and its Properties

A New Measure of Probabilistic Entropy. and its Properties Appled Mathematcal Sceces, Vol. 4, 200, o. 28, 387-394 A New Measure of Probablstc Etropy ad ts Propertes Rajeesh Kumar Departmet of Mathematcs Kurukshetra Uversty Kurukshetra, Ida rajeesh_kuk@redffmal.com

More information

First Law of Thermodynamics

First Law of Thermodynamics Cocept o Iteral Eergy, U Iteral eergy s the sum o the ketc ad potetal eerges o the partcles that make up the system. Frst Law o Thermodyamcs Chapter Coservato o Eergy At molecular level, cotrbutors to

More information

d b c d a c a a a c d b

d b c d a c a a a c d b Beha Uverty Faculty of Egeerg Shoubra Electrcal Egeerg eartmet Frt Year commucato. t emeter Eam ate: 3 0 ECE: Electroc Egeerg fudametal urato : 3 hour K=.38 3 J/K h=6.64 34 J. q=.6 9 C m o =9. 3 Kg [S]

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

Lecture 9: Tolerant Testing

Lecture 9: Tolerant Testing Lecture 9: Tolerat Testg Dael Kae Scrbe: Sakeerth Rao Aprl 4, 07 Abstract I ths lecture we prove a quas lear lower boud o the umber of samples eeded to do tolerat testg for L dstace. Tolerat Testg We have

More information

Absorption in Solar Atmosphere

Absorption in Solar Atmosphere Absorpto Solar Atmosphere A black body spectrum emtted from solar surface causes exctato processes o atoms the solar atmosphere. Ths tur causes absorpto of characterstc wavelegths correspodg to those atoms

More information

Multiple Regression. More than 2 variables! Grade on Final. Multiple Regression 11/21/2012. Exam 2 Grades. Exam 2 Re-grades

Multiple Regression. More than 2 variables! Grade on Final. Multiple Regression 11/21/2012. Exam 2 Grades. Exam 2 Re-grades STAT 101 Dr. Kar Lock Morga 11/20/12 Exam 2 Grades Multple Regresso SECTIONS 9.2, 10.1, 10.2 Multple explaatory varables (10.1) Parttog varablty R 2, ANOVA (9.2) Codtos resdual plot (10.2) Trasformatos

More information

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i CHEMICAL EQUILIBRIA The Thermodyamc Equlbrum Costat Cosder a reversble reacto of the type 1 A 1 + 2 A 2 + W m A m + m+1 A m+1 + Assgg postve values to the stochometrc coeffcets o the rght had sde ad egatve

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

Stationary states of atoms and molecules

Stationary states of atoms and molecules Statoary states of atos ad olecules I followg wees the geeral aspects of the eergy level structure of atos ad olecules that are essetal for the terpretato ad the aalyss of spectral postos the rotatoal

More information

Chapter 3 Sampling For Proportions and Percentages

Chapter 3 Sampling For Proportions and Percentages Chapter 3 Samplg For Proportos ad Percetages I may stuatos, the characterstc uder study o whch the observatos are collected are qualtatve ature For example, the resposes of customers may marketg surveys

More information

ECE 421/599 Electric Energy Systems 7 Optimal Dispatch of Generation. Instructor: Kai Sun Fall 2014

ECE 421/599 Electric Energy Systems 7 Optimal Dispatch of Generation. Instructor: Kai Sun Fall 2014 ECE 4/599 Electrc Eergy Systems 7 Optmal Dspatch of Geerato Istructor: Ka Su Fall 04 Backgroud I a practcal power system, the costs of geeratg ad delverg electrcty from power plats are dfferet (due to

More information

STK4011 and STK9011 Autumn 2016

STK4011 and STK9011 Autumn 2016 STK4 ad STK9 Autum 6 Pot estmato Covers (most of the followg materal from chapter 7: Secto 7.: pages 3-3 Secto 7..: pages 3-33 Secto 7..: pages 35-3 Secto 7..3: pages 34-35 Secto 7.3.: pages 33-33 Secto

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Exam: ECON430 Statstcs Date of exam: Frday, December 8, 07 Grades are gve: Jauary 4, 08 Tme for exam: 0900 am 00 oo The problem set covers 5 pages Resources allowed:

More information

Cross-plane Seebeck coefficient and Lorenz number in superlattices

Cross-plane Seebeck coefficient and Lorenz number in superlattices PHYSICAL REVIEW B 76, 25311 27 Cross-plae Seebeck coeffcet ad Lorez umber superlattces Z. Ba, M. Zebarjad, R. Sgh, Y. Ezzahr, ad A. Shakour Electrcal Egeerg Departmet, Uversty of Calfora, Sata Cruz, Calfora

More information

Silicon solar cell under electromagnetic wave in steady state: effect of the telecommunication source's power of radiation

Silicon solar cell under electromagnetic wave in steady state: effect of the telecommunication source's power of radiation IOP Coferece Seres: Materals Scece ad Egeerg Slco solar cell uder electromagetc wave steady state: effect of the telecommucato source's power of radato To cte ths artcle: I Zerbo et al 1 IOP Cof. Ser.:

More information

Lecture Notes Types of economic variables

Lecture Notes Types of economic variables Lecture Notes 3 1. Types of ecoomc varables () Cotuous varable takes o a cotuum the sample space, such as all pots o a le or all real umbers Example: GDP, Polluto cocetrato, etc. () Dscrete varables fte

More information

Chapter Business Statistics: A First Course Fifth Edition. Learning Objectives. Correlation vs. Regression. In this chapter, you learn:

Chapter Business Statistics: A First Course Fifth Edition. Learning Objectives. Correlation vs. Regression. In this chapter, you learn: Chapter 3 3- Busess Statstcs: A Frst Course Ffth Edto Chapter 2 Correlato ad Smple Lear Regresso Busess Statstcs: A Frst Course, 5e 29 Pretce-Hall, Ic. Chap 2- Learg Objectves I ths chapter, you lear:

More information

III-16 G. Brief Review of Grand Orthogonality Theorem and impact on Representations (Γ i ) l i = h n = number of irreducible representations.

III-16 G. Brief Review of Grand Orthogonality Theorem and impact on Representations (Γ i ) l i = h n = number of irreducible representations. III- G. Bref evew of Grad Orthogoalty Theorem ad mpact o epresetatos ( ) GOT: h [ () m ] [ () m ] δδ δmm ll GOT puts great restrcto o form of rreducble represetato also o umber: l h umber of rreducble

More information

Manipulator Dynamics. Amirkabir University of Technology Computer Engineering & Information Technology Department

Manipulator Dynamics. Amirkabir University of Technology Computer Engineering & Information Technology Department Mapulator Dyamcs mrkabr Uversty of echology omputer Egeerg formato echology Departmet troducto obot arm dyamcs deals wth the mathematcal formulatos of the equatos of robot arm moto. hey are useful as:

More information

Uniform magnetic susceptibilities

Uniform magnetic susceptibilities Uform magetc susceptbltes Typcal behavors ad measuremet techques SUSCPTIILIT UNIFORM & MAGNTOMTRIS page 1 - M ICFP- lectroc propertes of solds (Fabrce ert Varous behavors of M(H magetzato M Lear respose

More information

Intrinsic Carrier Concentration

Intrinsic Carrier Concentration Itrisic Carrier Cocetratio I. Defiitio Itrisic semicoductor: A semicoductor material with o dopats. It electrical characteristics such as cocetratio of charge carriers, deped oly o pure crystal. II. To

More information

CLASS NOTES. for. PBAF 528: Quantitative Methods II SPRING Instructor: Jean Swanson. Daniel J. Evans School of Public Affairs

CLASS NOTES. for. PBAF 528: Quantitative Methods II SPRING Instructor: Jean Swanson. Daniel J. Evans School of Public Affairs CLASS NOTES for PBAF 58: Quattatve Methods II SPRING 005 Istructor: Jea Swaso Dael J. Evas School of Publc Affars Uversty of Washgto Ackowledgemet: The structor wshes to thak Rachel Klet, Assstat Professor,

More information

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model Chapter 3 Asmptotc Theor ad Stochastc Regressors The ature of eplaator varable s assumed to be o-stochastc or fed repeated samples a regresso aalss Such a assumpto s approprate for those epermets whch

More information

Solutions to Homework Problems for the Complexity Explorer Course on Random Walks

Solutions to Homework Problems for the Complexity Explorer Course on Random Walks Solutos to Homework Problems for the Complexty Explorer Course o Radom Walks. Dsplacemet of a radom walk. Cosder the Pearso radom walk ay spatal dmeso whch the legth of each step has the fxed value a,

More information

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS Course Project: Classcal Mechacs (PHY 40) Suja Dabholkar (Y430) Sul Yeshwath (Y444). Itroducto Hamltoa mechacs s geometry phase space. It deals

More information

CIS 800/002 The Algorithmic Foundations of Data Privacy October 13, Lecture 9. Database Update Algorithms: Multiplicative Weights

CIS 800/002 The Algorithmic Foundations of Data Privacy October 13, Lecture 9. Database Update Algorithms: Multiplicative Weights CIS 800/002 The Algorthmc Foudatos of Data Prvacy October 13, 2011 Lecturer: Aaro Roth Lecture 9 Scrbe: Aaro Roth Database Update Algorthms: Multplcatve Weghts We ll recall aga) some deftos from last tme:

More information

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

arxiv:cond-mat/ v2 11 Dec 2000

arxiv:cond-mat/ v2 11 Dec 2000 arxv:cod-mat/0006 v Dec 000 THE NTURE OF THE LON TIME DECY T SECOND ORDER TRNSITION POINT Moshe Schwartz School of Physcs ad stroomy Tel vv Uversty Tel vv, Ramat vv, Israel d S. F. Edwards Cavedsh Laboratory

More information

Lecture 8: Linear Regression

Lecture 8: Linear Regression Lecture 8: Lear egresso May 4, GENOME 56, Sprg Goals Develop basc cocepts of lear regresso from a probablstc framework Estmatg parameters ad hypothess testg wth lear models Lear regresso Su I Lee, CSE

More information

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy Bouds o the expected etropy ad KL-dvergece of sampled multomal dstrbutos Brado C. Roy bcroy@meda.mt.edu Orgal: May 18, 2011 Revsed: Jue 6, 2011 Abstract Iformato theoretc quattes calculated from a sampled

More information

EP2200 Queueing theory and teletraffic systems. Queueing networks. Viktoria Fodor KTH EES/LCN KTH EES/LCN

EP2200 Queueing theory and teletraffic systems. Queueing networks. Viktoria Fodor KTH EES/LCN KTH EES/LCN EP2200 Queueg theory ad teletraffc systems Queueg etworks Vktora Fodor Ope ad closed queug etworks Queug etwork: etwork of queug systems E.g. data packets traversg the etwork from router to router Ope

More information

ECSE-6300 IC Fabrication Laboratory Lecture 6 Diffusion in Silicon. Lecture Outline

ECSE-6300 IC Fabrication Laboratory Lecture 6 Diffusion in Silicon. Lecture Outline ECSE-6300 IC Fabrcato Laboratory Lecture 6 ffuso Slco Prof. Resselaer Polytechc Isttute Troy, NY 1180 Offce: CII-69 Tel.: (518) 76-909 e-mals: luj@rp.edu http://www.ecse.rp.edu/courses/s16/ecse 6300/dex.html

More information

SOLUTIONS: ECE 606 Homework Week 7 Mark Lundstrom Purdue University (revised 3/27/13) e E i E T

SOLUTIONS: ECE 606 Homework Week 7 Mark Lundstrom Purdue University (revised 3/27/13) e E i E T SOUIONS: ECE 606 Homework Week 7 Mark udstrom Purdue Uiversity (revised 3/27/13) 1) Cosider a - type semicoductor for which the oly states i the badgap are door levels (i.e. ( E = E D ). Begi with the

More information

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA THE ROYAL STATISTICAL SOCIETY 3 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA PAPER I STATISTICAL THEORY & METHODS The Socety provdes these solutos to assst caddates preparg for the examatos future years ad

More information

2SLS Estimates ECON In this case, begin with the assumption that E[ i

2SLS Estimates ECON In this case, begin with the assumption that E[ i SLS Estmates ECON 3033 Bll Evas Fall 05 Two-Stage Least Squares (SLS Cosder a stadard lear bvarate regresso model y 0 x. I ths case, beg wth the assumto that E[ x] 0 whch meas that OLS estmates of wll

More information

Sampling Theory MODULE V LECTURE - 14 RATIO AND PRODUCT METHODS OF ESTIMATION

Sampling Theory MODULE V LECTURE - 14 RATIO AND PRODUCT METHODS OF ESTIMATION Samplg Theor MODULE V LECTUE - 4 ATIO AND PODUCT METHODS OF ESTIMATION D. SHALABH DEPATMENT OF MATHEMATICS AND STATISTICS INDIAN INSTITUTE OF TECHNOLOG KANPU A mportat objectve a statstcal estmato procedure

More information

Lecture 3 Probability review (cont d)

Lecture 3 Probability review (cont d) STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto

More information

Fitting models to data.

Fitting models to data. Fttg models to data. Prevous lectures dscussed model geerato. Start wth physcal pcture or dagram of what s happeg Make lst of assumptos (e.g., cell drug uptake s by dffuso; covecto ca be eglected) Wrte

More information

Idea is to sample from a different distribution that picks points in important regions of the sample space. Want ( ) ( ) ( ) E f X = f x g x dx

Idea is to sample from a different distribution that picks points in important regions of the sample space. Want ( ) ( ) ( ) E f X = f x g x dx Importace Samplg Used for a umber of purposes: Varace reducto Allows for dffcult dstrbutos to be sampled from. Sestvty aalyss Reusg samples to reduce computatoal burde. Idea s to sample from a dfferet

More information

Dopant Compensation. Lecture 2. Carrier Drift. Types of Charge in a Semiconductor

Dopant Compensation. Lecture 2. Carrier Drift. Types of Charge in a Semiconductor Lecture OUTLIE Bc Semcoductor Phycs (cot d) rrer d uo P ucto odes Electrosttcs ctce ot omesto tye semcoductor c be coverted to P tye mterl by couter dog t wth ccetors such tht >. comested semcoductor mterl

More information

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line HUR Techcal Report 000--9 verso.05 / Frak Borg (borgbros@ett.f) A Study of the Reproducblty of Measuremets wth HUR Leg Eteso/Curl Research Le A mportat property of measuremets s that the results should

More information

Transport Equation. For constant ε, the force per unit fluid volume due to electric field becomes,

Transport Equation. For constant ε, the force per unit fluid volume due to electric field becomes, Trasport Eqato For ostat ε, the fore per t fld volme de to eletr feld beomes, - ρ f E N/m 3 or ρ f ψ Mometm Eq. (trodg the eletr fore term as body fore term) ρ + ρ = p + µ d t Steady state, reep flow d

More information

Mean is only appropriate for interval or ratio scales, not ordinal or nominal.

Mean is only appropriate for interval or ratio scales, not ordinal or nominal. Mea Same as ordary average Sum all the data values ad dvde by the sample sze. x = ( x + x +... + x Usg summato otato, we wrte ths as x = x = x = = ) x Mea s oly approprate for terval or rato scales, ot

More information

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b CS 70 Dscrete Mathematcs ad Probablty Theory Fall 206 Sesha ad Walrad DIS 0b. Wll I Get My Package? Seaky delvery guy of some compay s out delverg packages to customers. Not oly does he had a radom package

More information

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II CEE49b Chapter - Free Vbrato of Mult-Degree-of-Freedom Systems - II We ca obta a approxmate soluto to the fudametal atural frequecy through a approxmate formula developed usg eergy prcples by Lord Raylegh

More information

Chapter 11 Systematic Sampling

Chapter 11 Systematic Sampling Chapter stematc amplg The sstematc samplg techue s operatoall more coveet tha the smple radom samplg. It also esures at the same tme that each ut has eual probablt of cluso the sample. I ths method of

More information

EE3310 Class notes Part 2. Solid State Electronic Devices - EE3310. Class notes. p-n junctions

EE3310 Class notes Part 2. Solid State Electronic Devices - EE3310. Class notes. p-n junctions EE3310 Class otes Part Verso: Fall 00 These class otes were orgally based o the hadwrtte otes of Larry Overzet. It s exected that they wll be modfed (mroved?) as tme goes o. Ths verso was tyed u by Matthew

More information