EXPERIMENTAL INVESTIGATION ON LAMINAR HIGHLY CONCENTRATED FLOW MODELED BY A PLASTIC LAW Session 5

Size: px
Start display at page:

Download "EXPERIMENTAL INVESTIGATION ON LAMINAR HIGHLY CONCENTRATED FLOW MODELED BY A PLASTIC LAW Session 5"

Transcription

1 EXPERIMENTAL INVESTIGATION ON LAMINAR HIGHLY CONCENTRATED FLOW MODELED BY A PLASTIC LAW Sessio 5 Sergio Brambilla, Ramo Pacheco, Fabrizio Sala ENEL.HYDRO S.p.a. Polo Idraulico Strutturale, Milao; Seior Hydraulic Egieer; Studet, Civil Egieerig, Politecico di Milao. SUMMARY A lamiar viscoplastic model Herschel-Bulkley for a steady uiform flow ad gradually varig flow of water ad clay at high cocetratio is preseted here. The model was aalysed experimetally at ENEL.HYDRO Polo Idraulico Strutturale laboratory of Mila by meas of a 15m log, 0.50m wide plexiglass walled laboratory flume with adjustable bottom slope. Rheological measuremets o samples of mud that were carried out promptly after the flume experimets were used to establish the variatio of its yield stress ad plastic viscosity with cocetratio of solid particles. A iterestig fidig was obtaied i the experimets preseted here: there is ot a cotiuous icrease i velocity with depth of flow as stated by Chezy s formula for the whole rage of cocetratio used. The lamiar viscoplastic model Herschel-Bulkey is able to reproduce the shape of the discharge vs. flow depth curve ad give some isight about the dyamical behaviour of the flow i coditio of steady flow. 1. INTRODUCTION It is well kow that mud ad debris flows ca cause devastatio i moutaious regios throughout the world where soils o steep slopes are saturated by heavy rais or sow melt. Much of the loss due to mud ad debris flow could be avoided if the path of probable flows could be predicted. Also, the desig of cotrol structures would be greatly improved by a ability to simulate such flows (Wright ad Kroe, 1987). May models have bee developed to determie the mud ad debris flows behavior, ad most of the them are based upo a costitutive equatio represetig the solid-water rheology. However, a theoretical model by itself is ot eough to describe ad explai the mud ad debris flow pheomea but it is ecessary to have experimetal ad field data to improve our kowledge of this kid of flows. The objective of this paper is to preset a theoretical ad experimetal ivestigatio based upo a Herschel-Bulkley model for the simulatio of lamiar ad viscoplastic free surface flows. We first examie the problem of a uiform steady mud flow. The model developed uses depth-averaged values for a uiform steady mud-fluid flow dow a iclied chael, i order to be able to explai some of the experimetal fidigs. Furthermore, from the equatios of the viscoplastic fluid a estimatio of the gradually ad spatially varied steady flow is also preseted. 2. EXPERIMENTAL SET-UP Experimets of steady, uiform flow ad gradually varied flow dow a iclied chael, of water- clay mixtures were coducted i a 15m log, 50cm wide chael. The chute agle was

2 1,93%. Clay particles with d 50 10µ m ad desity of 2650kg/m 3 were used. The grai size distributio is preseted i Figure clay silt fie sad coarse sad Weight percetage [%] Diameter [ µm] Figure 1. Grai size distributio of the atural fie mud suspesio. The chael bottom was i PVC. The mud flow was supplied by a pump located at the upper ed of the chael, it esured the steady circulatio. The mass flow rates were measured by a flow meter. The mixture clay-water was mixed i a power mixer for five hours to assure a uiform ad homogeeous mud mixture. The uiformity of the flow depth was cofirmed by markig the flow depth alog the chael side wall, which was clear ad allowed for direct visual observatio. The levels were recorded alog of the flume. Figure 2. Experimetal istallatio ENEL.HYDRO Hydraulic Laboratory of Mila-Italy.

3 3. RHEOLOGY The debris ad mud flows have differet characteristics depedig o the grai size distributio, the cocetratio of sedimet, ad the magitude of the flow. Previous rheological studies cocerig cocetrated mud suspesios have show that these materials are o-newtoia, viscoplastic fluids. The mai feature of these fluids is their yield stress which might be defied as the miimum shear stress to overcome for flow to take place. The yield stress of a mud or debris suspesio icreases expoetially with its solid cocetratio. Because of their high apparet viscosity, atural flows of cocetrated mud suspesios are lamiar. The rheological measuremets showed that water-clay mixtures are a visco-elastic fluid. The fluid respose to a applied shear rate it is deoted total stress. The shear depedecy of the mud viscosity ad yield stregth was visible i all the experimets. Due to shear depedecy of the rheological properties of mud a Herschel-Bulkley model have bee adopted sice it appears to be i keepig with the rheometrical measuremets i a very large, shear rate rage. This model expresses as follows: du du τ = τ c + k whe 0 ; (1) dy dy du τ τ c whe = 0. (2) dy where τ is the total shear stress magitude, du/dy the shear rate magitude ad τ c, k ad are fluid parameters. I this experimetal ivestigatio may geerally be take as 2/3 with water-clay mixtures with volume cocetratio Φ betwee 10 ad 19% experimetal results Herschel-Bulkley model Shear stress τ[pa] Φ =18,8% (21 C ) = 2/3 τ c = 19,013Pa k = 0,174Pa.s 2/ Shear rate du/dy[s -1 ] Figure 3. Flow curve of clay-water suspesio with 18.8% solid fractio.

4 4. UNIFORM LAMINAR FLOW Figure 4. Free surface flow o a iclied plae. Figure 4 presets a idealized sketch of free surface flows modeled as a yield visco plasticfluid. The free surface flows of fluids whose behaviour follows the model expressed by Herschel-Bulkley model are basically govered by: y ( ) y q = u = p h hs dy u 0 p h hs (3) + hs 2 1 U = q h hs = u p 1 (4) h where U [m/s] is the mea flow velocity, h [m] the flow depth, q [l/ms] the discharge by uit legth ad u p [m/s] the velocity of the plug flow. Figures 5a-5b show a tred i the values of the mea velocity agaist flow depth very differet to that of pure water. The icrease of depth is very little with a icrease i the flow velocity. This is better observed where the results obtaied are preseted. This behaviour is differet to that of the water flow typically represeted by the Chezy or Maig equatio i the case of turbulet flow or i the case of lamiar flow. This criteria could be useful for the desig of cotrol works for this kid of flows. Uiform depth h [m] experimetal results Herschel-Bulkley model Chézy equatio Φ =13,5% τc =10,177Pa k =0,117Pa.s =2/ Discharge by uit leght q[l/s/m]

5 Uiform depth h [m] experimetal results Herschel-Bulkley model Chézy equatio Φ =15,6% τc =13,318Pa k =0,143Pa.s =2/ Discharge by uit leght q[l/s/m] Figure 5a-5b. Stage-discharge relatioship at various solid fractio. 5. FREE SURFACE PROFILE IN STEADY FLOW We cosider here the case of a steady o-uiform flow i a ope chael. Applicatio of mometum theorem to the cotrol volume idicated i Figure 4. ad assumig gradually varied flow leads to: dh dx ( + 1) ( 2 1) 1 + q 1 τc + k ρgh ta θ ( h h p ) [( 1) h h p] ta + + = θ (5) 2 1 Fr h p () x = τc dh ρg cosθ ta θ dx (6) where τ c = yield stress, k = Herschel-Bukley fluid behaviour parameter, = 2 3, ρ = specific mass, u p = velocity of plug, h p (x) = depth of plug alog the chael, h p = depth of plug i uiform flow, θ = bed slope, Fr = Froude umber. The theoretical predictios usig equatio (5) were compared with experimetal results correspodig to rectagular chael flows ad showed a rather good global agreemet (see Figures 6a-6b). Uder the steady coditios, the depths of plug were recorded alog the flume. The measuremets have bee obtaied whe τ = τc ad the discharge was carried out from q steady to q ull. The mathematical model based upo the costitutive equatio Herschel Bulkley shows good capabilities to predict plug-flow of the water-clay mixtures i gradually varied flow.

6 0.075 flow to chael ed Flow depth h [m] Φ =12% =4,789Pa τc k =0,072Pa.s =2/3 water surface profile plug flow profile water profile (experimetal results) plug flow profile (experimetal results) x [m] flow to chael ed Flow depth h [m] Φ =10,4% =3,326Pa τc k =0,062Pa.s =2/3 water surface profile plug flow profile water profile (experimetal results) plug profile (experimetal results) x [m] Figure 6a-6b. Compariso betwee mathematical model ad experimetal results. 6. CONCLUSIONS A lamiar viscoplastic Herschel-Bulkley model for a steady uiform flow ad gradually varied flow of water ad clay at high cocetratio has bee verified here. The model shows good capabilities to predict flows of the studied water-clay mixtures. The model is able to reproduce the shape of the relatioship betwee mea velocity ad depth of flow for the whole rage of cocetratios. The mai source of error i ay flow predictio (i atural) comes from rheometrical measuremets eve whe these latter are doe carefully. I these coditios this problem appears as a critical poit for the predictio of free surface flow characteristics especially i fields where it is hard to carry out precise rheometrical experimets. 7. BIBLIOGRAPHY 1. V.G. Wright ad R.B. Kroe Laboratory ad umerical study of mud ad debris flow. AIRH Cogress, Lausae, 1987; 2. Z. Wa ad Z. Wag Hypercocetrated flow. Balkema, Rotterdam, 1994; 3. P. Coussot Mudflow rheology ad dyamics. Balkema, Rotterdam, 1997; 4. ENEL HYDRO S.p.a. Verifica teorico-sperimetale di u modello visco-plastico per lo studio delle correti ipercocetrate, rapporto fiale per l ao 1999.

Free Surface Hydrodynamics

Free Surface Hydrodynamics Water Sciece ad Egieerig Free Surface Hydrodyamics y A part of Module : Hydraulics ad Hydrology Water Sciece ad Egieerig Dr. Shreedhar Maskey Seior Lecturer UNESCO-IHE Istitute for Water Educatio S. Maskey

More information

4.1 Introduction. 4. Uniform Flow and its Computations

4.1 Introduction. 4. Uniform Flow and its Computations 4. Uiform Flow ad its Computatios 4. Itroductio A flow is said to be uiform if its properties remai costat with respect to distace. As metioed i chapter oe of the hadout, the term ope chael flow i ope

More information

UNIFORM FLOW. U x. U t

UNIFORM FLOW. U x. U t UNIFORM FLOW if : 1) there are o appreciable variatios i the chael geometry (width, slope, roughess/grai size), for a certai legth of a river reach ) flow discharge does ot vary the, UNIFORM FLOW coditios

More information

1 Inferential Methods for Correlation and Regression Analysis

1 Inferential Methods for Correlation and Regression Analysis 1 Iferetial Methods for Correlatio ad Regressio Aalysis I the chapter o Correlatio ad Regressio Aalysis tools for describig bivariate cotiuous data were itroduced. The sample Pearso Correlatio Coefficiet

More information

11 Correlation and Regression

11 Correlation and Regression 11 Correlatio Regressio 11.1 Multivariate Data Ofte we look at data where several variables are recorded for the same idividuals or samplig uits. For example, at a coastal weather statio, we might record

More information

A statistical method to determine sample size to estimate characteristic value of soil parameters

A statistical method to determine sample size to estimate characteristic value of soil parameters A statistical method to determie sample size to estimate characteristic value of soil parameters Y. Hojo, B. Setiawa 2 ad M. Suzuki 3 Abstract Sample size is a importat factor to be cosidered i determiig

More information

BACKMIXING IN SCREW EXTRUDERS

BACKMIXING IN SCREW EXTRUDERS BACKMIXING IN SCREW EXTRUDERS Chris Rauwedaal, Rauwedaal Extrusio Egieerig, Ic. Paul Grama, The Madiso Group Abstract Mixig is a critical fuctio i most extrusio operatios. Oe of the most difficult mixig

More information

On a Smarandache problem concerning the prime gaps

On a Smarandache problem concerning the prime gaps O a Smaradache problem cocerig the prime gaps Felice Russo Via A. Ifate 7 6705 Avezzao (Aq) Italy felice.russo@katamail.com Abstract I this paper, a problem posed i [] by Smaradache cocerig the prime gaps

More information

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 9

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 9 Hypothesis testig PSYCHOLOGICAL RESEARCH (PYC 34-C Lecture 9 Statistical iferece is that brach of Statistics i which oe typically makes a statemet about a populatio based upo the results of a sample. I

More information

On the Blasius correlation for friction factors

On the Blasius correlation for friction factors O the Blasius correlatio for frictio factors Trih, Khah Tuoc Istitute of Food Nutritio ad Huma Health Massey Uiversity, New Zealad K.T.Trih@massey.ac.z Abstract The Blasius empirical correlatio for turbulet

More information

1036: Probability & Statistics

1036: Probability & Statistics 036: Probability & Statistics Lecture 0 Oe- ad Two-Sample Tests of Hypotheses 0- Statistical Hypotheses Decisio based o experimetal evidece whether Coffee drikig icreases the risk of cacer i humas. A perso

More information

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter Time Respose & Frequecy Respose d -Order Dyamic System -Pole, Low-Pass, Active Filter R 4 R 7 C 5 e i R 1 C R 3 - + R 6 - + e out Assigmet: Perform a Complete Dyamic System Ivestigatio of the Two-Pole,

More information

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense, 3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [

More information

A proposed discrete distribution for the statistical modeling of

A proposed discrete distribution for the statistical modeling of It. Statistical Ist.: Proc. 58th World Statistical Cogress, 0, Dubli (Sessio CPS047) p.5059 A proposed discrete distributio for the statistical modelig of Likert data Kidd, Marti Cetre for Statistical

More information

TURBULENT SHEAR STRESS IN HETEROGENEOUS SEDIMENT-LADEN FLOWS

TURBULENT SHEAR STRESS IN HETEROGENEOUS SEDIMENT-LADEN FLOWS TURBULENT SHEAR STRESS IN HETEROGENEOUS SEDIMENT-LADEN FLOWS By Hyoseop Woo, 1 Associate Member, ASCE, ad Pierre Y. Julie, 2 Member, ASCE INTRODUCTION Curret kowledge of the mechaics of alluvial chaels

More information

Numerical Simulation of Thermomechanical Problems in Applied Mechanics: Application to Solidification Problem

Numerical Simulation of Thermomechanical Problems in Applied Mechanics: Application to Solidification Problem Leoardo Joural of Scieces ISSN 1583-0233 Issue 9, July-December 2006 p. 25-32 Numerical Simulatio of Thermomechaical Problems i Applied Mechaics: Applicatio to Solidificatio Problem Vicet Obiajulu OGWUAGWU

More information

If, for instance, we were required to test whether the population mean μ could be equal to a certain value μ

If, for instance, we were required to test whether the population mean μ could be equal to a certain value μ STATISTICAL INFERENCE INTRODUCTION Statistical iferece is that brach of Statistics i which oe typically makes a statemet about a populatio based upo the results of a sample. I oesample testig, we essetially

More information

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering CEE 5 Autum 005 Ucertaity Cocepts for Geotechical Egieerig Basic Termiology Set A set is a collectio of (mutually exclusive) objects or evets. The sample space is the (collectively exhaustive) collectio

More information

II. Descriptive Statistics D. Linear Correlation and Regression. 1. Linear Correlation

II. Descriptive Statistics D. Linear Correlation and Regression. 1. Linear Correlation II. Descriptive Statistics D. Liear Correlatio ad Regressio I this sectio Liear Correlatio Cause ad Effect Liear Regressio 1. Liear Correlatio Quatifyig Liear Correlatio The Pearso product-momet correlatio

More information

Properties and Hypothesis Testing

Properties and Hypothesis Testing Chapter 3 Properties ad Hypothesis Testig 3.1 Types of data The regressio techiques developed i previous chapters ca be applied to three differet kids of data. 1. Cross-sectioal data. 2. Time series data.

More information

11TH INTERNATIONAL SYMPOSIUM ON PARTICLE IMAGE VELOCIMETRY - PIV15 Santa Barbara, California, Sept , 2015

11TH INTERNATIONAL SYMPOSIUM ON PARTICLE IMAGE VELOCIMETRY - PIV15 Santa Barbara, California, Sept , 2015 11TH INTERNATIONAL SYMPOSIUM ON PARTICLE IMAGE VELOCIMETRY - PIV15 Sata Barbara, Califoria, Sept. 14-16, 2015 ABSTRACT HELE-SHAW RHEOMETRY BY MEANS OF PARTICLE IMAGE VELOCIMETRY Sita Drost & Jerry Westerweel

More information

Probability, Expectation Value and Uncertainty

Probability, Expectation Value and Uncertainty Chapter 1 Probability, Expectatio Value ad Ucertaity We have see that the physically observable properties of a quatum system are represeted by Hermitea operators (also referred to as observables ) such

More information

Econ 325 Notes on Point Estimator and Confidence Interval 1 By Hiro Kasahara

Econ 325 Notes on Point Estimator and Confidence Interval 1 By Hiro Kasahara Poit Estimator Eco 325 Notes o Poit Estimator ad Cofidece Iterval 1 By Hiro Kasahara Parameter, Estimator, ad Estimate The ormal probability desity fuctio is fully characterized by two costats: populatio

More information

n 3 ln n n ln n is convergent by p-series for p = 2 > 1. n2 Therefore we can apply Limit Comparison Test to determine lutely convergent.

n 3 ln n n ln n is convergent by p-series for p = 2 > 1. n2 Therefore we can apply Limit Comparison Test to determine lutely convergent. 06 微甲 0-04 06-0 班期中考解答和評分標準. ( poits) Determie whether the series is absolutely coverget, coditioally coverget, or diverget. Please state the tests which you use. (a) ( poits) (b) ( poits) (c) ( poits)

More information

a b c d e f g h Supplementary Information

a b c d e f g h Supplementary Information Supplemetary Iformatio a b c d e f g h Supplemetary Figure S STM images show that Dark patters are frequetly preset ad ted to accumulate. (a) mv, pa, m ; (b) mv, pa, m ; (c) mv, pa, m ; (d) mv, pa, m ;

More information

WHAT IS THE PROBABILITY FUNCTION FOR LARGE TSUNAMI WAVES? ABSTRACT

WHAT IS THE PROBABILITY FUNCTION FOR LARGE TSUNAMI WAVES? ABSTRACT WHAT IS THE PROBABILITY FUNCTION FOR LARGE TSUNAMI WAVES? Harold G. Loomis Hoolulu, HI ABSTRACT Most coastal locatios have few if ay records of tsuami wave heights obtaied over various time periods. Still

More information

Damped Vibration of a Non-prismatic Beam with a Rotational Spring

Damped Vibration of a Non-prismatic Beam with a Rotational Spring Vibratios i Physical Systems Vol.6 (0) Damped Vibratio of a No-prismatic Beam with a Rotatioal Sprig Wojciech SOCHACK stitute of Mechaics ad Fudametals of Machiery Desig Uiversity of Techology, Czestochowa,

More information

Disaster Mitigation of Debris Flows, Slope Failures and Landslides 141

Disaster Mitigation of Debris Flows, Slope Failures and Landslides 141 Disaster Mitigatio of Debris Flows, Slope Failures ad Ladslides 141 Slit-Check Dams for Cotrollig Debris Flow ad Mudflow Aroe Armaii, 1) Claudio Dalrì 1) ad Michele Larcher 1) 1) CUDAM ad Departmet of

More information

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING Lectures MODULE 5 STATISTICS II. Mea ad stadard error of sample data. Biomial distributio. Normal distributio 4. Samplig 5. Cofidece itervals

More information

Chapter 11 Output Analysis for a Single Model. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation

Chapter 11 Output Analysis for a Single Model. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation Chapter Output Aalysis for a Sigle Model Baks, Carso, Nelso & Nicol Discrete-Evet System Simulatio Error Estimatio If {,, } are ot statistically idepedet, the S / is a biased estimator of the true variace.

More information

MATH/STAT 352: Lecture 15

MATH/STAT 352: Lecture 15 MATH/STAT 352: Lecture 15 Sectios 5.2 ad 5.3. Large sample CI for a proportio ad small sample CI for a mea. 1 5.2: Cofidece Iterval for a Proportio Estimatig proportio of successes i a biomial experimet

More information

Open book and notes. 120 minutes. Cover page and six pages of exam. No calculators.

Open book and notes. 120 minutes. Cover page and six pages of exam. No calculators. IE 330 Seat # Ope book ad otes 120 miutes Cover page ad six pages of exam No calculators Score Fial Exam (example) Schmeiser Ope book ad otes No calculator 120 miutes 1 True or false (for each, 2 poits

More information

Activity 3: Length Measurements with the Four-Sided Meter Stick

Activity 3: Length Measurements with the Four-Sided Meter Stick Activity 3: Legth Measuremets with the Four-Sided Meter Stick OBJECTIVE: The purpose of this experimet is to study errors ad the propagatio of errors whe experimetal data derived usig a four-sided meter

More information

Topic 5 [434 marks] (i) Find the range of values of n for which. (ii) Write down the value of x dx in terms of n, when it does exist.

Topic 5 [434 marks] (i) Find the range of values of n for which. (ii) Write down the value of x dx in terms of n, when it does exist. Topic 5 [44 marks] 1a (i) Fid the rage of values of for which eists 1 Write dow the value of i terms of 1, whe it does eist Fid the solutio to the differetial equatio 1b give that y = 1 whe = π (cos si

More information

Principle Of Superposition

Principle Of Superposition ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give

More information

6.003 Homework #3 Solutions

6.003 Homework #3 Solutions 6.00 Homework # Solutios Problems. Complex umbers a. Evaluate the real ad imagiary parts of j j. π/ Real part = Imagiary part = 0 e Euler s formula says that j = e jπ/, so jπ/ j π/ j j = e = e. Thus the

More information

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + 62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of

More information

R. van Zyl 1, A.J. van der Merwe 2. Quintiles International, University of the Free State

R. van Zyl 1, A.J. van der Merwe 2. Quintiles International, University of the Free State Bayesia Cotrol Charts for the Two-parameter Expoetial Distributio if the Locatio Parameter Ca Take o Ay Value Betwee Mius Iity ad Plus Iity R. va Zyl, A.J. va der Merwe 2 Quitiles Iteratioal, ruaavz@gmail.com

More information

Chemical Engineering 374

Chemical Engineering 374 Chemical Egieerig 374 Fluid Mechaics NoNewtoia Fluids Outlie 2 Types ad properties of o-newtoia Fluids Pipe flows for o-newtoia fluids Velocity profile / flow rate Pressure op Frictio factor Pump power

More information

1 of 7 7/16/2009 6:06 AM Virtual Laboratories > 6. Radom Samples > 1 2 3 4 5 6 7 6. Order Statistics Defiitios Suppose agai that we have a basic radom experimet, ad that X is a real-valued radom variable

More information

THE NUMERICAL SOLUTION OF THE NEWTONIAN FLUIDS FLOW DUE TO A STRETCHING CYLINDER BY SOR ITERATIVE PROCEDURE ABSTRACT

THE NUMERICAL SOLUTION OF THE NEWTONIAN FLUIDS FLOW DUE TO A STRETCHING CYLINDER BY SOR ITERATIVE PROCEDURE ABSTRACT Europea Joural of Egieerig ad Techology Vol. 3 No., 5 ISSN 56-586 THE NUMERICAL SOLUTION OF THE NEWTONIAN FLUIDS FLOW DUE TO A STRETCHING CYLINDER BY SOR ITERATIVE PROCEDURE Atif Nazir, Tahir Mahmood ad

More information

Course Outline. Designing Control Systems. Proportional Controller. Amme 3500 : System Dynamics and Control. Root Locus. Dr. Stefan B.

Course Outline. Designing Control Systems. Proportional Controller. Amme 3500 : System Dynamics and Control. Root Locus. Dr. Stefan B. Amme 3500 : System Dyamics ad Cotrol Root Locus Course Outlie Week Date Cotet Assigmet Notes Mar Itroductio 8 Mar Frequecy Domai Modellig 3 5 Mar Trasiet Performace ad the s-plae 4 Mar Block Diagrams Assig

More information

The Generalized Newtonian Fluid - Isothermal Flows Constitutive Equations! Viscosity Models! Solution of Flow Problems!

The Generalized Newtonian Fluid - Isothermal Flows Constitutive Equations! Viscosity Models! Solution of Flow Problems! The Geeralized Newtoia Fluid - Isothermal Flows Costitutive Equatios! Viscosity Models! Solutio of Flow Problems! 0.53/2.34! Sprig 204! MIT! Cambridge, MA 0239! Geeralized Newtoia Fluid Simple Shear Flow

More information

Mark Lundstrom Spring SOLUTIONS: ECE 305 Homework: Week 5. Mark Lundstrom Purdue University

Mark Lundstrom Spring SOLUTIONS: ECE 305 Homework: Week 5. Mark Lundstrom Purdue University Mark udstrom Sprig 2015 SOUTIONS: ECE 305 Homework: Week 5 Mark udstrom Purdue Uiversity The followig problems cocer the Miority Carrier Diffusio Equatio (MCDE) for electros: Δ t = D Δ + G For all the

More information

MATH 1080: Calculus of One Variable II Fall 2017 Textbook: Single Variable Calculus: Early Transcendentals, 7e, by James Stewart.

MATH 1080: Calculus of One Variable II Fall 2017 Textbook: Single Variable Calculus: Early Transcendentals, 7e, by James Stewart. MATH 1080: Calculus of Oe Variable II Fall 2017 Textbook: Sigle Variable Calculus: Early Trascedetals, 7e, by James Stewart Uit 3 Skill Set Importat: Studets should expect test questios that require a

More information

Statisticians use the word population to refer the total number of (potential) observations under consideration

Statisticians use the word population to refer the total number of (potential) observations under consideration 6 Samplig Distributios Statisticias use the word populatio to refer the total umber of (potetial) observatios uder cosideratio The populatio is just the set of all possible outcomes i our sample space

More information

MATH 320: Probability and Statistics 9. Estimation and Testing of Parameters. Readings: Pruim, Chapter 4

MATH 320: Probability and Statistics 9. Estimation and Testing of Parameters. Readings: Pruim, Chapter 4 MATH 30: Probability ad Statistics 9. Estimatio ad Testig of Parameters Estimatio ad Testig of Parameters We have bee dealig situatios i which we have full kowledge of the distributio of a radom variable.

More information

IIT JAM Mathematical Statistics (MS) 2006 SECTION A

IIT JAM Mathematical Statistics (MS) 2006 SECTION A IIT JAM Mathematical Statistics (MS) 6 SECTION A. If a > for ad lim a / L >, the which of the followig series is ot coverget? (a) (b) (c) (d) (d) = = a = a = a a + / a lim a a / + = lim a / a / + = lim

More information

ChE 471 Lecture 10 Fall 2005 SAFE OPERATION OF TUBULAR (PFR) ADIABATIC REACTORS

ChE 471 Lecture 10 Fall 2005 SAFE OPERATION OF TUBULAR (PFR) ADIABATIC REACTORS SAFE OPERATION OF TUBULAR (PFR) ADIABATIC REACTORS I a exothermic reactio the temperature will cotiue to rise as oe moves alog a plug flow reactor util all of the limitig reactat is exhausted. Schematically

More information

PREDICTION OF REVERBERATION TIME IN RECTANGULAR ROOMS WITH NON UNIFORMLY DISTRIBUTED ABSORPTION USING A NEW FORMULA

PREDICTION OF REVERBERATION TIME IN RECTANGULAR ROOMS WITH NON UNIFORMLY DISTRIBUTED ABSORPTION USING A NEW FORMULA PREDICTION OF REVERBERATION TIME IN RECTANGULAR ROOM WITH NON UNIFORMLY DITRIBUTED ABORPTION UING A NEW FORMULA PAC REFERENCE: 43.55.Br Neubauer, Reihard O. Ig.-Büro Neubauer VDI Theresiestr. 8 D-85049

More information

STP 226 ELEMENTARY STATISTICS

STP 226 ELEMENTARY STATISTICS TP 6 TP 6 ELEMENTARY TATITIC CHAPTER 4 DECRIPTIVE MEAURE IN REGREION AND CORRELATION Liear Regressio ad correlatio allows us to examie the relatioship betwee two or more quatitative variables. 4.1 Liear

More information

GROUND MOTION OF NON-CIRCULAR ALLUVIAL VALLEY FOR INCIDENT PLANE SH-WAVE. Hui QI, Yong SHI, Jingfu NAN

GROUND MOTION OF NON-CIRCULAR ALLUVIAL VALLEY FOR INCIDENT PLANE SH-WAVE. Hui QI, Yong SHI, Jingfu NAN The th World Coferece o Earthquake Egieerig October -7, 8, Beiig, Chia GROUND MOTION OF NON-CIRCULAR ALLUVIAL VALLEY FOR INCIDENT PLANE SH-WAVE Hui QI, Yog SHI, Jigfu NAN ABSTRACT : Professor, Dept. of

More information

Lecture 1 Probability and Statistics

Lecture 1 Probability and Statistics Wikipedia: Lecture 1 Probability ad Statistics Bejami Disraeli, British statesma ad literary figure (1804 1881): There are three kids of lies: lies, damed lies, ad statistics. popularized i US by Mark

More information

µ and π p i.e. Point Estimation x And, more generally, the population proportion is approximately equal to a sample proportion

µ and π p i.e. Point Estimation x And, more generally, the population proportion is approximately equal to a sample proportion Poit Estimatio Poit estimatio is the rather simplistic (ad obvious) process of usig the kow value of a sample statistic as a approximatio to the ukow value of a populatio parameter. So we could for example

More information

Lecture 1 Probability and Statistics

Lecture 1 Probability and Statistics Wikipedia: Lecture 1 Probability ad Statistics Bejami Disraeli, British statesma ad literary figure (1804 1881): There are three kids of lies: lies, damed lies, ad statistics. popularized i US by Mark

More information

Discrete Orthogonal Moment Features Using Chebyshev Polynomials

Discrete Orthogonal Moment Features Using Chebyshev Polynomials Discrete Orthogoal Momet Features Usig Chebyshev Polyomials R. Mukuda, 1 S.H.Og ad P.A. Lee 3 1 Faculty of Iformatio Sciece ad Techology, Multimedia Uiversity 75450 Malacca, Malaysia. Istitute of Mathematical

More information

Mathematical Modeling of Optimum 3 Step Stress Accelerated Life Testing for Generalized Pareto Distribution

Mathematical Modeling of Optimum 3 Step Stress Accelerated Life Testing for Generalized Pareto Distribution America Joural of Theoretical ad Applied Statistics 05; 4(: 6-69 Published olie May 8, 05 (http://www.sciecepublishiggroup.com/j/ajtas doi: 0.648/j.ajtas.05040. ISSN: 6-8999 (Prit; ISSN: 6-9006 (Olie Mathematical

More information

Statistical Fundamentals and Control Charts

Statistical Fundamentals and Control Charts Statistical Fudametals ad Cotrol Charts 1. Statistical Process Cotrol Basics Chace causes of variatio uavoidable causes of variatios Assigable causes of variatio large variatios related to machies, materials,

More information

Review Questions, Chapters 8, 9. f(y) = 0, elsewhere. F (y) = f Y(1) = n ( e y/θ) n 1 1 θ e y/θ = n θ e yn

Review Questions, Chapters 8, 9. f(y) = 0, elsewhere. F (y) = f Y(1) = n ( e y/θ) n 1 1 θ e y/θ = n θ e yn Stat 366 Lab 2 Solutios (September 2, 2006) page TA: Yury Petracheko, CAB 484, yuryp@ualberta.ca, http://www.ualberta.ca/ yuryp/ Review Questios, Chapters 8, 9 8.5 Suppose that Y, Y 2,..., Y deote a radom

More information

MAT 271 Project: Partial Fractions for certain rational functions

MAT 271 Project: Partial Fractions for certain rational functions MAT 7 Project: Partial Fractios for certai ratioal fuctios Prerequisite kowledge: partial fractios from MAT 7, a very good commad of factorig ad complex umbers from Precalculus. To complete this project,

More information

The axial dispersion model for tubular reactors at steady state can be described by the following equations: dc dz R n cn = 0 (1) (2) 1 d 2 c.

The axial dispersion model for tubular reactors at steady state can be described by the following equations: dc dz R n cn = 0 (1) (2) 1 d 2 c. 5.4 Applicatio of Perturbatio Methods to the Dispersio Model for Tubular Reactors The axial dispersio model for tubular reactors at steady state ca be described by the followig equatios: d c Pe dz z =

More information

Indian Institute of Information Technology, Allahabad. End Semester Examination - Tentative Marking Scheme

Indian Institute of Information Technology, Allahabad. End Semester Examination - Tentative Marking Scheme Idia Istitute of Iformatio Techology, Allahabad Ed Semester Examiatio - Tetative Markig Scheme Course Name: Mathematics-I Course Code: SMAT3C MM: 75 Program: B.Tech st year (IT+ECE) ate of Exam:..7 ( st

More information

A CONFINEMENT MODEL OF HIGH STRENGTH CONCRETE

A CONFINEMENT MODEL OF HIGH STRENGTH CONCRETE 3 th World Coferece o Earthquake Egieerig Vacouver, B.C., Caada August -6, 24 Paper No. 873 A CONFINEMENT MODEL OF HIGH STRENGTH CONCRETE Nobutaka NAKAZAWA, Kazuhiko KAWASHIMA 2, Gakuho WATANABE 3, Ju-ichi

More information

Goodness-Of-Fit For The Generalized Exponential Distribution. Abstract

Goodness-Of-Fit For The Generalized Exponential Distribution. Abstract Goodess-Of-Fit For The Geeralized Expoetial Distributio By Amal S. Hassa stitute of Statistical Studies & Research Cairo Uiversity Abstract Recetly a ew distributio called geeralized expoetial or expoetiated

More information

APPLICATION OF ERGUN EQUATION TO COMPUTATION OF CRITICAL SHEAR VELOCITY SUBJECT TO SEEPAGE

APPLICATION OF ERGUN EQUATION TO COMPUTATION OF CRITICAL SHEAR VELOCITY SUBJECT TO SEEPAGE Citatio: Cheg, N. S. (). Applicatio of Ergu equatio to computatio of critical shear velocity subject to seepage. Joural of Irrigatio ad Draiage Egieerig, ASCE. 9(4), 78-8. APPLICATION OF ERGUN EQUATION

More information

Calculus 2 Test File Fall 2013

Calculus 2 Test File Fall 2013 Calculus Test File Fall 013 Test #1 1.) Without usig your calculator, fid the eact area betwee the curves f() = 4 - ad g() = si(), -1 < < 1..) Cosider the followig solid. Triagle ABC is perpedicular to

More information

MOST PEOPLE WOULD RATHER LIVE WITH A PROBLEM THEY CAN'T SOLVE, THAN ACCEPT A SOLUTION THEY CAN'T UNDERSTAND.

MOST PEOPLE WOULD RATHER LIVE WITH A PROBLEM THEY CAN'T SOLVE, THAN ACCEPT A SOLUTION THEY CAN'T UNDERSTAND. XI-1 (1074) MOST PEOPLE WOULD RATHER LIVE WITH A PROBLEM THEY CAN'T SOLVE, THAN ACCEPT A SOLUTION THEY CAN'T UNDERSTAND. R. E. D. WOOLSEY AND H. S. SWANSON XI-2 (1075) STATISTICAL DECISION MAKING Advaced

More information

Name: Math 10550, Final Exam: December 15, 2007

Name: Math 10550, Final Exam: December 15, 2007 Math 55, Fial Exam: December 5, 7 Name: Be sure that you have all pages of the test. No calculators are to be used. The exam lasts for two hours. Whe told to begi, remove this aswer sheet ad keep it uder

More information

NUCLEATION 7.1 INTRODUCTION 7.2 HOMOGENEOUS NUCLEATION Embryos and nuclei CHAPTER 7

NUCLEATION 7.1 INTRODUCTION 7.2 HOMOGENEOUS NUCLEATION Embryos and nuclei CHAPTER 7 CHAPER 7 NUCLEAION 7.1 INRODUCION I this text, we focus our attetio o crystallie solids that form from the melt. he process begis with the creatio of a cluster of atoms of crystallie structure, which may

More information

Kinetics of Complex Reactions

Kinetics of Complex Reactions Kietics of Complex Reactios by Flick Colema Departmet of Chemistry Wellesley College Wellesley MA 28 wcolema@wellesley.edu Copyright Flick Colema 996. All rights reserved. You are welcome to use this documet

More information

Tests of Hypotheses Based on a Single Sample (Devore Chapter Eight)

Tests of Hypotheses Based on a Single Sample (Devore Chapter Eight) Tests of Hypotheses Based o a Sigle Sample Devore Chapter Eight MATH-252-01: Probability ad Statistics II Sprig 2018 Cotets 1 Hypothesis Tests illustrated with z-tests 1 1.1 Overview of Hypothesis Testig..........

More information

Sample Size Estimation in the Proportional Hazards Model for K-sample or Regression Settings Scott S. Emerson, M.D., Ph.D.

Sample Size Estimation in the Proportional Hazards Model for K-sample or Regression Settings Scott S. Emerson, M.D., Ph.D. ample ie Estimatio i the Proportioal Haards Model for K-sample or Regressio ettigs cott. Emerso, M.D., Ph.D. ample ie Formula for a Normally Distributed tatistic uppose a statistic is kow to be ormally

More information

CUMULATIVE DAMAGE ESTIMATION USING WAVELET TRANSFORM OF STRUCTURAL RESPONSE

CUMULATIVE DAMAGE ESTIMATION USING WAVELET TRANSFORM OF STRUCTURAL RESPONSE CUMULATIVE DAMAGE ESTIMATION USING WAVELET TRANSFORM OF STRUCTURAL RESPONSE Ryutaro SEGAWA 1, Shizuo YAMAMOTO, Akira SONE 3 Ad Arata MASUDA 4 SUMMARY Durig a strog earthquake, the respose of a structure

More information

EECS564 Estimation, Filtering, and Detection Hwk 2 Solns. Winter p θ (z) = (2θz + 1 θ), 0 z 1

EECS564 Estimation, Filtering, and Detection Hwk 2 Solns. Winter p θ (z) = (2θz + 1 θ), 0 z 1 EECS564 Estimatio, Filterig, ad Detectio Hwk 2 Sols. Witer 25 4. Let Z be a sigle observatio havig desity fuctio where. p (z) = (2z + ), z (a) Assumig that is a oradom parameter, fid ad plot the maximum

More information

We will conclude the chapter with the study a few methods and techniques which are useful

We will conclude the chapter with the study a few methods and techniques which are useful Chapter : Coordiate geometry: I this chapter we will lear about the mai priciples of graphig i a dimesioal (D) Cartesia system of coordiates. We will focus o drawig lies ad the characteristics of the graphs

More information

Parasitic Resistance L R W. Polysilicon gate. Drain. contact L D. V GS,eff R S R D. Drain

Parasitic Resistance L R W. Polysilicon gate. Drain. contact L D. V GS,eff R S R D. Drain Parasitic Resistace G Polysilico gate rai cotact V GS,eff S R S R S, R S, R + R C rai Short Chael Effects Chael-egth Modulatio Equatio k ( V V ) GS T suggests that the trasistor i the saturatio mode acts

More information

1 Models for Matched Pairs

1 Models for Matched Pairs 1 Models for Matched Pairs Matched pairs occur whe we aalyse samples such that for each measuremet i oe of the samples there is a measuremet i the other sample that directly relates to the measuremet i

More information

Lecture 2: Monte Carlo Simulation

Lecture 2: Monte Carlo Simulation STAT/Q SCI 43: Itroductio to Resamplig ethods Sprig 27 Istructor: Ye-Chi Che Lecture 2: ote Carlo Simulatio 2 ote Carlo Itegratio Assume we wat to evaluate the followig itegratio: e x3 dx What ca we do?

More information

577. Estimation of surface roughness using high frequency vibrations

577. Estimation of surface roughness using high frequency vibrations 577. Estimatio of surface roughess usig high frequecy vibratios V. Augutis, M. Sauoris, Kauas Uiversity of Techology Electroics ad Measuremets Systems Departmet Studetu str. 5-443, LT-5368 Kauas, Lithuaia

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION DOI: 10.1038/NPHYS309 O the reality of the quatum state Matthew F. Pusey, 1, Joatha Barrett, ad Terry Rudolph 1 1 Departmet of Physics, Imperial College Lodo, Price Cosort Road, Lodo SW7 AZ, Uited Kigdom

More information

ECE 8527: Introduction to Machine Learning and Pattern Recognition Midterm # 1. Vaishali Amin Fall, 2015

ECE 8527: Introduction to Machine Learning and Pattern Recognition Midterm # 1. Vaishali Amin Fall, 2015 ECE 8527: Itroductio to Machie Learig ad Patter Recogitio Midterm # 1 Vaishali Ami Fall, 2015 tue39624@temple.edu Problem No. 1: Cosider a two-class discrete distributio problem: ω 1 :{[0,0], [2,0], [2,2],

More information

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series

More information

Chapter 7: The z-transform. Chih-Wei Liu

Chapter 7: The z-transform. Chih-Wei Liu Chapter 7: The -Trasform Chih-Wei Liu Outlie Itroductio The -Trasform Properties of the Regio of Covergece Properties of the -Trasform Iversio of the -Trasform The Trasfer Fuctio Causality ad Stability

More information

Finally, we show how to determine the moments of an impulse response based on the example of the dispersion model.

Finally, we show how to determine the moments of an impulse response based on the example of the dispersion model. 5.3 Determiatio of Momets Fially, we show how to determie the momets of a impulse respose based o the example of the dispersio model. For the dispersio model we have that E θ (θ ) curve is give by eq (4).

More information

The target reliability and design working life

The target reliability and design working life Safety ad Security Egieerig IV 161 The target reliability ad desig workig life M. Holický Kloker Istitute, CTU i Prague, Czech Republic Abstract Desig workig life ad target reliability levels recommeded

More information

Lecture III-2: Light propagation in nonmagnetic

Lecture III-2: Light propagation in nonmagnetic A. La Rosa Lecture Notes ALIED OTIC Lecture III2: Light propagatio i omagetic materials 2.1 urface ( ), volume ( ), ad curret ( j ) desities produced by arizatio charges The objective i this sectio is

More information

OBJECTIVES. Chapter 1 INTRODUCTION TO INSTRUMENTATION FUNCTION AND ADVANTAGES INTRODUCTION. At the end of this chapter, students should be able to:

OBJECTIVES. Chapter 1 INTRODUCTION TO INSTRUMENTATION FUNCTION AND ADVANTAGES INTRODUCTION. At the end of this chapter, students should be able to: OBJECTIVES Chapter 1 INTRODUCTION TO INSTRUMENTATION At the ed of this chapter, studets should be able to: 1. Explai the static ad dyamic characteristics of a istrumet. 2. Calculate ad aalyze the measuremet

More information

Discrete Mathematics for CS Spring 2008 David Wagner Note 22

Discrete Mathematics for CS Spring 2008 David Wagner Note 22 CS 70 Discrete Mathematics for CS Sprig 2008 David Wager Note 22 I.I.D. Radom Variables Estimatig the bias of a coi Questio: We wat to estimate the proportio p of Democrats i the US populatio, by takig

More information

Deterministic Model of Multipath Fading for Circular and Parabolic Reflector Patterns

Deterministic Model of Multipath Fading for Circular and Parabolic Reflector Patterns To appear i the Proceedigs of the 5 IEEE outheastco, (Ft. Lauderdale, FL), April 5 Determiistic Model of Multipath Fadig for Circular ad Parabolic Reflector Patters Dwight K. Hutcheso dhutche@clemso.edu

More information

Formation of A Supergain Array and Its Application in Radar

Formation of A Supergain Array and Its Application in Radar Formatio of A Supergai Array ad ts Applicatio i Radar Tra Cao Quye, Do Trug Kie ad Bach Gia Duog. Research Ceter for Electroic ad Telecommuicatios, College of Techology (Coltech, Vietam atioal Uiversity,

More information

Chapter 13, Part A Analysis of Variance and Experimental Design

Chapter 13, Part A Analysis of Variance and Experimental Design Slides Prepared by JOHN S. LOUCKS St. Edward s Uiversity Slide 1 Chapter 13, Part A Aalysis of Variace ad Eperimetal Desig Itroductio to Aalysis of Variace Aalysis of Variace: Testig for the Equality of

More information

Regression and correlation

Regression and correlation Cotets 43 Regressio ad correlatio 1. Regressio. Correlatio Learig outcomes You will lear how to explore relatioships betwee variables ad how to measure the stregth of such relatioships. You should ote

More information

Infinite Sequences and Series

Infinite Sequences and Series Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet

More information

Last time: Moments of the Poisson distribution from its generating function. Example: Using telescope to measure intensity of an object

Last time: Moments of the Poisson distribution from its generating function. Example: Using telescope to measure intensity of an object 6.3 Stochastic Estimatio ad Cotrol, Fall 004 Lecture 7 Last time: Momets of the Poisso distributio from its geeratig fuctio. Gs () e dg µ e ds dg µ ( s) µ ( s) µ ( s) µ e ds dg X µ ds X s dg dg + ds ds

More information

Assessment of extreme discharges of the Vltava River in Prague

Assessment of extreme discharges of the Vltava River in Prague Flood Recovery, Iovatio ad Respose I 05 Assessmet of extreme discharges of the Vltava River i Prague M. Holický, K. Jug & M. Sýkora Kloker Istitute, Czech Techical Uiversity i Prague, Czech Republic Abstract

More information

Statistical Pattern Recognition

Statistical Pattern Recognition Statistical Patter Recogitio Classificatio: No-Parametric Modelig Hamid R. Rabiee Jafar Muhammadi Sprig 2014 http://ce.sharif.edu/courses/92-93/2/ce725-2/ Ageda Parametric Modelig No-Parametric Modelig

More information

EVALUATION OF GLASS FIBER/EPOXY INTERFACIAL STRENGTH BY THE CRUCIFORM SPECIMEN METHOD

EVALUATION OF GLASS FIBER/EPOXY INTERFACIAL STRENGTH BY THE CRUCIFORM SPECIMEN METHOD EVALUATION OF GLASS FIBER/EPOX INTERFACIAL STRENGTH B THE CRUCIFORM SPECIMEN METHOD Ju KOANAGI, Hajime KATO, Akihiro KASHIMA, uichi IGARASHI, Keichi WATANABE 3, Ichiro UENO 4 ad Shiji OGIHARA 4 Istitute

More information

2 1. The r.s., of size n2, from population 2 will be. 2 and 2. 2) The two populations are independent. This implies that all of the n1 n2

2 1. The r.s., of size n2, from population 2 will be. 2 and 2. 2) The two populations are independent. This implies that all of the n1 n2 Chapter 8 Comparig Two Treatmets Iferece about Two Populatio Meas We wat to compare the meas of two populatios to see whether they differ. There are two situatios to cosider, as show i the followig examples:

More information

Honors Calculus Homework 13 Solutions, due 12/8/5

Honors Calculus Homework 13 Solutions, due 12/8/5 Hoors Calculus Homework Solutios, due /8/5 Questio Let a regio R i the plae be bouded by the curves y = 5 ad = 5y y. Sketch the regio R. The two curves meet where both equatios hold at oce, so where: y

More information

The AMSU Observation Bias Correction and Its Application Retrieval Scheme, and Typhoon Analysis

The AMSU Observation Bias Correction and Its Application Retrieval Scheme, and Typhoon Analysis The AMSU Observatio Bias Correctio ad Its Applicatio Retrieval Scheme, ad Typhoo Aalysis Chie-Be Chou, Kug-Hwa Wag Cetral Weather Bureau, Taipei, Taiwa, R.O.C. Abstract Sice most of AMSU chaels have a

More information