Math 10 - Exam 1 Topics
|
|
- Todd Evans
- 5 years ago
- Views:
Transcription
1 Math 10 - Exam 1 Tpics Types and Levels f data Categrical, Discrete r Cntinuus Nminal, Ordinal, Interval r Rati Descriptive Statistics Stem and Leaf Graph Dt Plt (Interpret) Gruped Data Relative and Cumulative Relative Frequencies Histgram Ogive Mean, Median, Mde Skewness Range, Variance, Standard Deviatin Empirical Rule Z-Scres Percentiles, Quartiles Interquartile Range Bx Plt Crrelatin Bivariate Data Scatterplt Crrelatin Cefficient Outliers Identifying Effect f utliers n Descriptive Statistics Experimental Design Steps f a Statistical Prcess Observatinal Study Representative Sample Sampling Methds Experiment Explanatry Variable Respnse Variable Blinding Placebs Prbability Empirical, Classical r Subjective Terms and Laws f Prbability Events and Outcmes Sample Space Cmplement Unins and Intersectins Additive Rule Cnditinal Prbability Tree Diagram Multiplicative Rule Independence Changing the cnditinality Cntingency (Tw way) Tables Marginal Prbabilities Jint Prbabilities Cnditinal Prbabilities Cnstructing table Discrete Randm Variables Mean and Standard Deviatin Prbability distributin functin (pdf) Prbability prblems Binmial Distributin Cntinuus Randm Variables Mean and Standard Deviatin Prbability density functin (pdf) Prbability and Percentile prblems fr Nrmal Distributin Central Limit Therem pdf f the randm variable X (3 imprtant parts) pdf f sample prprtin ˆp Prbability Questins Yu must bring a picture ID t the exam. Yu may bring 4 pages f HANDWRITTEN ntes t the exam. Bring yur prbability tables (Binmial Nrmal, etc) Bring Pencil, Calculatr and yur ntes t the exam n sharing is allwed during the exam. N cell phne calculatrs. Cell Phnes, ipds, PDAs, and ther electrnic devices must be turned ff and put away. Manage yur time s yu can attempt every questin.
2 Practice Questins fr Exam % f American adults have Type II diabetes. A test has been develped that has a 80% chance f crrectly detecting this disease, but has a false psitive rate f 15%. a. Draw a tree diagram f all pssibilities, where the first branch represents persn having Type II diabetes (psitive D+ r negative D-) and the secnd branch represents the test (psitive T+ r negative T-). b. What percentage f American adults will TEST psitive fr the Type II diabetes? c. Given an adult tests psitive fr the disease, what is the prbability the adult actually has Type II diabetes? 2. The data shwn in the scatter plt is the distance traveled and the airfare fr 12 flights n Delta Airlines: a. Which f the fllwing is a reasnable estimate f the crrelatin cefficient? (Circle ne answer) b. What des this graph tell us abut distance and airfare c. What is the type and level f distance traveled? Type (Circle One) Categrical Discrete Cntinuus Level (Circle One) Nminal Ordinal Interval Rati 3. Yu have a 70% chance f being n time t class tday and a 80% chance f being n time t class tmrrw. Assume these tw days are independent events. a. Find the prbability f being n time t class bth tday and tmrrw. b. Find the prbability f being n time t class at least nce tday r tmrrw. 4. The fllwing data represent the daily births at a hspital fr 20 days a) Cnstruct a stem and leaf diagram f the data b) Calculate the interquartile range fr this data set. c) Calculate the median fr this data set. d) Withut calculating, what can yu say abut the mean births fr this Hspital.(check ne answer belw)? The mean is greater than the median. The mean is less than the median. The mean is abut the same as the median. Nne f the abve n way t knw withut calculating. 5. The fllwing data represents the hurs per week wrked utside f schl by 200 randmly selected night students at a cmmunity cllege: Hurs Frequency Relative Freq C.R.Freq a) In the space abve, determine the relative frequencies and cumulative relative frequencies. b) Sketch a relative frequency histgram, shwing all hrizntal and vertical labels. c) Sketch a cumulative relative frequency give, shwing all hrizntal and vertical labels. d) Estimate the median frm the graph. e) What percentage f the night students wrk 32 hurs per week r less? f) Withut calculating but explaining yur reasning, which f the fllwing is a reasnable estimate fr the standard deviatin? a) 0.5 b) 1 c) 10 d) 50
3 6. Determine if each f the fllwing data are categrical, cntinuus r discrete (circle ne fr each) a. Number f fatalities frm a tsunami: categrical cntinuus discrete b. Time spent in traffic: categrical cntinuus discrete c. Number f Sngs n yur I-pd: categrical cntinuus discrete d. Yur student number categrical cntinuus discrete e. Names f cities in Califrnia with a Walmart: categrical cntinuus discrete f. Price per galln f gasline: categrical cntinuus discrete g. Number f Curses taken in a year. categrical cntinuus discrete h. Tns f steel used by a manufacturer: categrical cntinuus discrete students (500 mrning, 300 afternn, 200 night) were asked hw ften they use the campus library. The results are summarized in the table belw: Never uses library Smetimes uses library Frequently uses libray Ttal Mrning Afternn Night Ttal a. Find the fllwing prbabilities: i) A randmly selected student never uses the library. ii) iii) A randmly selected student is a night student and frequently uses the library. Given the student is an afternn student, the student never uses the library. b. Are Afternn Student and Never uses library Independent Events? Justify and explain yur answer. c. Wuld the prbabilities generated frm this data be classical, empirical r subjective prbability? 8. These descriptive statistics and bxplts were generated frm data representing calries per serving fr three types f htdgs: All Beef, Mixed Meat and Pultry. a. Cmpare the mean t the median calries fr the Meat grup. Is the result cnsistent with the shape f the bx plt? Explain yur answer. b. If the data is apprximately bell shaped, between what tw values f calries wuld yu expect t find abut 95% f the Beef data? c. Which f the three grups has the mst variability in calries per serving? Explain yur answer. d. Hebrew Natinal All Beef Htdgs had 190 calries per serving. Calculate and interpret the z-scre fr Hebrew Natinal Htdgs using the Beef Categry data. e. Determine the prbability a randmly selected Pultry Ht Dg exceeds 113 calries. f. Cmpare the three grups and draw at least tw cnclusins frm the results.
4 9. Frm samples f a ttal f 2100 yung (18-24 year ld) White, Black and Latin men taken in January 2010 in the U.S., the unemplyment rate f each sample was determined as given in the fllwing table. (2013, Urban Institute, The Labr Market Perfrmance f Yung Black Men Race/Ethnicity Unemplyment Rate in the Great Recessin). The study used stratified sampling. The Urban Institute cncluded that yung black men have a higher unemplyment during the recessin than their white and Latin peers. White 15.6% a. What is the ppulatin and what is the sample? Black 30.0% b. Identify the steps f the statistical prcess: Hispanic 26.9% Ask a questin that can be answered with sample data. Determine the infrmatin needed. Cllect sample data that is representative f the ppulatin. Summarize, interpret and analyze the sample data. State the results and cnclusin f the study. 10. A study was cnducted t examine the effects f active recvery (AR), massage (MR), and cld water immersin (CR) n perfrmance f repeated buts f high-intensity cycling separated by 24 hurs. A sample f physically active men aged were randmly assigned t ne f fur grups. Each grup perfrmed an intense 18-minute cycling wrkut after which each underwent a 15-minute recvery perid. In the 15 minutes, the first grup (AR) cntinued t cycle at a lw level, the secnd grup (MR) received leg massage, the third grup (CR) immersed their legs in a bath f cld water. The last grup simply sat and rested. The next day the subjects did the same intense 18-minute cycling wrkut. Each exercise was dne n a cycle ergmeter s that the wrk level (measure in kiljules) was calculated fr each. The researchers fund that n the secnd day, that there was n difference in the perfrmance level f the subjects in the AR, MR and CR, but that the subjects wh just sat in a chair t rest did less wrk than the ther grups. (Jurnal f Strength and Cnditining Research (2004; 18 [4], ). a. What is the explanatry variable? b. What is the respnse variable? c. Which grups are the treatment grups? d. Is there a cntrl grup? If s, which ne? e. Is there blinding in this experiment? Explain yur answer % f students at a large New Yrk University receive sme financial aid. a. If 4 students are randmly selected, determine the prbability that exactly 2 students in the sample receive sme financial aid. b. If 4 students are randmly selected, determine the prbability that less than 2 students in the sample receive sme financial aid The randm variable X fllws the prbability distributin functin as shwn t the right: a. Determine P(X=3) b. Determine the ppulatin mean. c. Determine the ppulatin variance
5 13. 40% f students at a cllege use the cafeteria. a. If 9 students are randmly sampled, determine the prbability that less than 3 use the cafeteria. If 9 students are randmly sampled and X represents the number f students in the sample wh use the cafeteria, find the mean and standard deviatin f X. 14. Accidents in a pwer plant ccur at a Pissn rate f 1.39 per year a. Find the prbability f at least 2 accidents ccurring at the plant in the next year. b. Find the prbability that the plant has zer accidents in tw year. 15. Find the 30 th percentile fr each f the cking time fr atmeal which fllws a Nrmal Distributin with a mean f 4 and a standard deviatin f Students exam scres fr a curse fllw a Nrmal Distributin with μ=70 and σ=10. a. Find the prbability a randmly selected student scres a 75 r mre. b. Find the exam scre which is the 25 th percentile f this distributin. c. Yu take a randm sample f 40 students. Find the prbability the sample mean is between 68 and 72. d. Wuld yur answer fr part c be different if the prbability distributin f exam scres did nt fllw a Nrmal distributin? Explain yur answer. 17. The age f a grve f walnut trees fllw a Nrmal Distributin with μ=50 years and σ=15 years. a. Find the prbability that the age f a randmly selected tree is between 40 and 70 years. b. Find the prbability f a randmly selected tree has lived exactly years. c. Find the 30 th percentile f this distributin % f students at De Anza Cllege plan t transfer t San Jse State. 200 students are randmly selected and the sample prprtin ˆp will be calculated. a. Determine the expected value and standard deviatin f the sample prprtin. b. Determine that the cnditin fr nrmality is satisfied. c. Determine the prbability the sample prprtin exceeds 0.40.
1b) =.215 1c).080/.215 =.372
Practice Exam 1 - Answers 1. / \.1/ \.9 (D+) (D-) / \ / \.8 / \.2.15/ \.85 (T+) (T-) (T+) (T-).080.020.135.765 1b).080 +.135 =.215 1c).080/.215 =.372 2. The data shwn in the scatter plt is the distance
More informationAP Statistics Practice Test Unit Three Exploring Relationships Between Variables. Name Period Date
AP Statistics Practice Test Unit Three Explring Relatinships Between Variables Name Perid Date True r False: 1. Crrelatin and regressin require explanatry and respnse variables. 1. 2. Every least squares
More informationAP Statistics Notes Unit Two: The Normal Distributions
AP Statistics Ntes Unit Tw: The Nrmal Distributins Syllabus Objectives: 1.5 The student will summarize distributins f data measuring the psitin using quartiles, percentiles, and standardized scres (z-scres).
More information, which yields. where z1. and z2
The Gaussian r Nrmal PDF, Page 1 The Gaussian r Nrmal Prbability Density Functin Authr: Jhn M Cimbala, Penn State University Latest revisin: 11 September 13 The Gaussian r Nrmal Prbability Density Functin
More informationEASTERN ARIZONA COLLEGE Introduction to Statistics
EASTERN ARIZONA COLLEGE Intrductin t Statistics Curse Design 2014-2015 Curse Infrmatin Divisin Scial Sciences Curse Number PSY 220 Title Intrductin t Statistics Credits 3 Develped by Adam Stinchcmbe Lecture/Lab
More informationCHAPTER 24: INFERENCE IN REGRESSION. Chapter 24: Make inferences about the population from which the sample data came.
MATH 1342 Ch. 24 April 25 and 27, 2013 Page 1 f 5 CHAPTER 24: INFERENCE IN REGRESSION Chapters 4 and 5: Relatinships between tw quantitative variables. Be able t Make a graph (scatterplt) Summarize the
More informationLesson Plan. Recode: They will do a graphic organizer to sequence the steps of scientific method.
Lessn Plan Reach: Ask the students if they ever ppped a bag f micrwave ppcrn and nticed hw many kernels were unppped at the bttm f the bag which made yu wnder if ther brands pp better than the ne yu are
More informationHypothesis Tests for One Population Mean
Hypthesis Tests fr One Ppulatin Mean Chapter 9 Ala Abdelbaki Objective Objective: T estimate the value f ne ppulatin mean Inferential statistics using statistics in rder t estimate parameters We will be
More informationTEST 3A AP Statistics Name: Directions: Work on these sheets. A standard normal table is attached.
TEST 3A AP Statistics Name: Directins: Wrk n these sheets. A standard nrmal table is attached. Part 1: Multiple Chice. Circle the letter crrespnding t the best answer. 1. In a statistics curse, a linear
More informationBootstrap Method > # Purpose: understand how bootstrap method works > obs=c(11.96, 5.03, 67.40, 16.07, 31.50, 7.73, 11.10, 22.38) > n=length(obs) >
Btstrap Methd > # Purpse: understand hw btstrap methd wrks > bs=c(11.96, 5.03, 67.40, 16.07, 31.50, 7.73, 11.10, 22.38) > n=length(bs) > mean(bs) [1] 21.64625 > # estimate f lambda > lambda = 1/mean(bs);
More informationStatistics Statistical method Variables Value Score Type of Research Level of Measurement...
Lecture 1 Displaying data... 12 Statistics... 13 Statistical methd... 13 Variables... 13 Value... 15 Scre... 15 Type f Research... 15 Level f Measurement... 15 Numeric/Quantitative variables... 15 Ordinal/Rank-rder
More informationMath Foundations 20 Work Plan
Math Fundatins 20 Wrk Plan Units / Tpics 20.8 Demnstrate understanding f systems f linear inequalities in tw variables. Time Frame December 1-3 weeks 6-10 Majr Learning Indicatrs Identify situatins relevant
More informationChapter 8: The Binomial and Geometric Distributions
Sectin 8.1: The Binmial Distributins Chapter 8: The Binmial and Gemetric Distributins A randm variable X is called a BINOMIAL RANDOM VARIABLE if it meets ALL the fllwing cnditins: 1) 2) 3) 4) The MOST
More informationMATHEMATICS SYLLABUS SECONDARY 5th YEAR
Eurpean Schls Office f the Secretary-General Pedaggical Develpment Unit Ref. : 011-01-D-8-en- Orig. : EN MATHEMATICS SYLLABUS SECONDARY 5th YEAR 6 perid/week curse APPROVED BY THE JOINT TEACHING COMMITTEE
More informationANSWER KEY FOR MATH 10 SAMPLE EXAMINATION. Instructions: If asked to label the axes please use real world (contextual) labels
ANSWER KEY FOR MATH 10 SAMPLE EXAMINATION Instructins: If asked t label the axes please use real wrld (cntextual) labels Multiple Chice Answers: 0 questins x 1.5 = 30 Pints ttal Questin Answer Number 1
More informationUnit 1: Introduction to Biology
Name: Unit 1: Intrductin t Bilgy Theme: Frm mlecules t rganisms Students will be able t: 1.1 Plan and cnduct an investigatin: Define the questin, develp a hypthesis, design an experiment and cllect infrmatin,
More informationDirections: Show all work. When using the calculator write down the function buttons used. not just write numerical solution write
MAT 1272 Practic Exercises fr the Final Revised Spring 2017 (Ellner) Directins: Shw all wrk. When using the calculatr write dwn the functin buttns used. D nt just write a numerical slutin write A SENTENCE
More informationmaking triangle (ie same reference angle) ). This is a standard form that will allow us all to have the X= y=
Intrductin t Vectrs I 21 Intrductin t Vectrs I 22 I. Determine the hrizntal and vertical cmpnents f the resultant vectr by cunting n the grid. X= y= J. Draw a mangle with hrizntal and vertical cmpnents
More informationDistributions, spatial statistics and a Bayesian perspective
Distributins, spatial statistics and a Bayesian perspective Dug Nychka Natinal Center fr Atmspheric Research Distributins and densities Cnditinal distributins and Bayes Thm Bivariate nrmal Spatial statistics
More informationTree Structured Classifier
Tree Structured Classifier Reference: Classificatin and Regressin Trees by L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stne, Chapman & Hall, 98. A Medical Eample (CART): Predict high risk patients
More informationInternal vs. external validity. External validity. This section is based on Stock and Watson s Chapter 9.
Sectin 7 Mdel Assessment This sectin is based n Stck and Watsn s Chapter 9. Internal vs. external validity Internal validity refers t whether the analysis is valid fr the ppulatin and sample being studied.
More informationUnit 1 Study Guide Name Date Scientific Method Notes
Unit 1 Study Guide Name Date Scientific Methd Ntes 1) What is the difference between an bservatin and an inference? 2) What are the tw types f bservatins? Give examples f each type. 3) Define the fllwing:
More informationCAUSAL INFERENCE. Technical Track Session I. Phillippe Leite. The World Bank
CAUSAL INFERENCE Technical Track Sessin I Phillippe Leite The Wrld Bank These slides were develped by Christel Vermeersch and mdified by Phillippe Leite fr the purpse f this wrkshp Plicy questins are causal
More informationCHM112 Lab Graphing with Excel Grading Rubric
Name CHM112 Lab Graphing with Excel Grading Rubric Criteria Pints pssible Pints earned Graphs crrectly pltted and adhere t all guidelines (including descriptive title, prperly frmatted axes, trendline
More informationExperiment #3. Graphing with Excel
Experiment #3. Graphing with Excel Study the "Graphing with Excel" instructins that have been prvided. Additinal help with learning t use Excel can be fund n several web sites, including http://www.ncsu.edu/labwrite/res/gt/gt-
More informationEnd of Course Algebra I ~ Practice Test #2
End f Curse Algebra I ~ Practice Test #2 Name: Perid: Date: 1: Order the fllwing frm greatest t least., 3, 8.9, 8,, 9.3 A. 8, 8.9,, 9.3, 3 B., 3, 8, 8.9,, 9.3 C. 9.3, 3,,, 8.9, 8 D. 3, 9.3,,, 8.9, 8 2:
More informationLarge Sample Hypothesis Tests for a Population Proportion
Ntes-10.3a Large Sample Hypthesis Tests fr a Ppulatin Prprtin ***Cin Tss*** 1. A friend f yurs claims that when he tsses a cin he can cntrl the utcme. Yu are skeptical and want him t prve it. He tsses
More informationIt is compulsory to submit the assignment before filling in the exam form.
OMT-101 ASSIGNMENT BOOKLET Bachelr's Preparatry Prgramme PREPARATORY COURSE IN GENERAL MATHEMATICS (This assignment is valid nly upt: 1 st December, 01 And Valid fr bth Jan 01 cycle and July 01 cycle)
More informationAP Statistics Notes Unit Five: Randomness and Probability
AP Statistics Ntes Unit Five: Randmness and Prbability Syllabus Objectives: 3.1 The student will interpret prbability, including the lng-term relative frequency distributin. 3.2 The student will discuss
More informationCHAPTER 3 INEQUALITIES. Copyright -The Institute of Chartered Accountants of India
CHAPTER 3 INEQUALITIES Cpyright -The Institute f Chartered Accuntants f India INEQUALITIES LEARNING OBJECTIVES One f the widely used decisin making prblems, nwadays, is t decide n the ptimal mix f scarce
More informationMath 9 Year End Review Package. (b) = (a) Side length = 15.5 cm ( area ) (b) Perimeter = 4xside = 62 m
Math Year End Review Package Chapter Square Rts and Surface Area KEY. Methd #: cunt the number f squares alng the side ( units) Methd #: take the square rt f the area. (a) 4 = 0.7. = 0.. _Perfect square
More informationNUMBERS, MATHEMATICS AND EQUATIONS
AUSTRALIAN CURRICULUM PHYSICS GETTING STARTED WITH PHYSICS NUMBERS, MATHEMATICS AND EQUATIONS An integral part t the understanding f ur physical wrld is the use f mathematical mdels which can be used t
More informationNAME TEMPERATURE AND HUMIDITY. I. Introduction
NAME TEMPERATURE AND HUMIDITY I. Intrductin Temperature is the single mst imprtant factr in determining atmspheric cnditins because it greatly influences: 1. The amunt f water vapr in the air 2. The pssibility
More informationHow do scientists measure trees? What is DBH?
Hw d scientists measure trees? What is DBH? Purpse Students develp an understanding f tree size and hw scientists measure trees. Students bserve and measure tree ckies and explre the relatinship between
More informationCompetency Statements for Wm. E. Hay Mathematics for grades 7 through 12:
Cmpetency Statements fr Wm. E. Hay Mathematics fr grades 7 thrugh 12: Upn cmpletin f grade 12 a student will have develped a cmbinatin f sme/all f the fllwing cmpetencies depending upn the stream f math
More informationLab 1 The Scientific Method
INTRODUCTION The fllwing labratry exercise is designed t give yu, the student, an pprtunity t explre unknwn systems, r universes, and hypthesize pssible rules which may gvern the behavir within them. Scientific
More informationM thematics. National 5 Practice Paper D. Paper 1. Duration 1 hour. Total marks 40
N5 M thematics Natinal 5 Practice Paper D Paper 1 Duratin 1 hur Ttal marks 40 Yu may NOT use a calculatr Attempt all the questins. Use blue r black ink. Full credit will nly be given t slutins which cntain
More informationMaximum A Posteriori (MAP) CS 109 Lecture 22 May 16th, 2016
Maximum A Psteriri (MAP) CS 109 Lecture 22 May 16th, 2016 Previusly in CS109 Game f Estimatrs Maximum Likelihd Nn spiler: this didn t happen Side Plt argmax argmax f lg Mther f ptimizatins? Reviving an
More informationFunction notation & composite functions Factoring Dividing polynomials Remainder theorem & factor property
Functin ntatin & cmpsite functins Factring Dividing plynmials Remainder therem & factr prperty Can d s by gruping r by: Always lk fr a cmmn factr first 2 numbers that ADD t give yu middle term and MULTIPLY
More informationWeathering. Title: Chemical and Mechanical Weathering. Grade Level: Subject/Content: Earth and Space Science
Weathering Title: Chemical and Mechanical Weathering Grade Level: 9-12 Subject/Cntent: Earth and Space Science Summary f Lessn: Students will test hw chemical and mechanical weathering can affect a rck
More informationDepartment: MATHEMATICS
Cde: MATH 022 Title: ALGEBRA SKILLS Institute: STEM Department: MATHEMATICS Curse Descriptin: This curse prvides students wh have cmpleted MATH 021 with the necessary skills and cncepts t cntinue the study
More informationThe Law of Total Probability, Bayes Rule, and Random Variables (Oh My!)
The Law f Ttal Prbability, Bayes Rule, and Randm Variables (Oh My!) Administrivia Hmewrk 2 is psted and is due tw Friday s frm nw If yu didn t start early last time, please d s this time. Gd Milestnes:
More informationSticiGui Chapter 4: Measures of Location and Spread Philip Stark (2013)
SticiGui Chapter 4: Measures f Lcatin and Spread Philip Stark (2013) Summarizing data can help us understand them, especially when the number f data is large. This chapter presents several ways t summarize
More informationCS 477/677 Analysis of Algorithms Fall 2007 Dr. George Bebis Course Project Due Date: 11/29/2007
CS 477/677 Analysis f Algrithms Fall 2007 Dr. Gerge Bebis Curse Prject Due Date: 11/29/2007 Part1: Cmparisn f Srting Algrithms (70% f the prject grade) The bjective f the first part f the assignment is
More informationLHS Mathematics Department Honors Pre-Calculus Final Exam 2002 Answers
LHS Mathematics Department Hnrs Pre-alculus Final Eam nswers Part Shrt Prblems The table at the right gives the ppulatin f Massachusetts ver the past several decades Using an epnential mdel, predict the
More informationMedium Scale Integrated (MSI) devices [Sections 2.9 and 2.10]
EECS 270, Winter 2017, Lecture 3 Page 1 f 6 Medium Scale Integrated (MSI) devices [Sectins 2.9 and 2.10] As we ve seen, it s smetimes nt reasnable t d all the design wrk at the gate-level smetimes we just
More informationExam #1. A. Answer any 1 of the following 2 questions. CEE 371 October 8, Please grade the following questions: 1 or 2
CEE 371 Octber 8, 2009 Exam #1 Clsed Bk, ne sheet f ntes allwed Please answer ne questin frm the first tw, ne frm the secnd tw and ne frm the last three. The ttal ptential number f pints is 100. Shw all
More information4th Indian Institute of Astrophysics - PennState Astrostatistics School July, 2013 Vainu Bappu Observatory, Kavalur. Correlation and Regression
4th Indian Institute f Astrphysics - PennState Astrstatistics Schl July, 2013 Vainu Bappu Observatry, Kavalur Crrelatin and Regressin Rahul Ry Indian Statistical Institute, Delhi. Crrelatin Cnsider a tw
More informationENSC Discrete Time Systems. Project Outline. Semester
ENSC 49 - iscrete Time Systems Prject Outline Semester 006-1. Objectives The gal f the prject is t design a channel fading simulatr. Upn successful cmpletin f the prject, yu will reinfrce yur understanding
More informationModelling of Clock Behaviour. Don Percival. Applied Physics Laboratory University of Washington Seattle, Washington, USA
Mdelling f Clck Behaviur Dn Percival Applied Physics Labratry University f Washingtn Seattle, Washingtn, USA verheads and paper fr talk available at http://faculty.washingtn.edu/dbp/talks.html 1 Overview
More informationM thematics. National 5 Practice Paper B. Paper 1. Duration 1 hour. Total marks 40
M thematics Natinal 5 Practice Paper B Paper 1 Duratin 1 hur Ttal marks 40 Yu may NOT use a calculatr Attempt all the questins. Use blue r black ink. Full credit will nly be given t slutins which cntain
More informationWe say that y is a linear function of x if. Chapter 13: The Correlation Coefficient and the Regression Line
Chapter 13: The Crrelatin Cefficient and the Regressin Line We begin with a sme useful facts abut straight lines. Recall the x, y crdinate system, as pictured belw. 3 2 1 y = 2.5 y = 0.5x 3 2 1 1 2 3 1
More informationSIZE BIAS IN LINE TRANSECT SAMPLING: A FIELD TEST. Mark C. Otto Statistics Research Division, Bureau of the Census Washington, D.C , U.S.A.
SIZE BIAS IN LINE TRANSECT SAMPLING: A FIELD TEST Mark C. Ott Statistics Research Divisin, Bureau f the Census Washingtn, D.C. 20233, U.S.A. and Kenneth H. Pllck Department f Statistics, Nrth Carlina State
More informationTHERMAL-VACUUM VERSUS THERMAL- ATMOSPHERIC TESTS OF ELECTRONIC ASSEMBLIES
PREFERRED RELIABILITY PAGE 1 OF 5 PRACTICES PRACTICE NO. PT-TE-1409 THERMAL-VACUUM VERSUS THERMAL- ATMOSPHERIC Practice: Perfrm all thermal envirnmental tests n electrnic spaceflight hardware in a flight-like
More informationExam #1. A. Answer any 1 of the following 2 questions. CEE 371 March 10, Please grade the following questions: 1 or 2
CEE 371 March 10, 2009 Exam #1 Clsed Bk, ne sheet f ntes allwed Please answer ne questin frm the first tw, ne frm the secnd tw and ne frm the last three. The ttal ptential number f pints is 100. Shw all
More information2004 AP CHEMISTRY FREE-RESPONSE QUESTIONS
2004 AP CHEMISTRY FREE-RESPONSE QUESTIONS 6. An electrchemical cell is cnstructed with an pen switch, as shwn in the diagram abve. A strip f Sn and a strip f an unknwn metal, X, are used as electrdes.
More informationDifferentiation Applications 1: Related Rates
Differentiatin Applicatins 1: Related Rates 151 Differentiatin Applicatins 1: Related Rates Mdel 1: Sliding Ladder 10 ladder y 10 ladder 10 ladder A 10 ft ladder is leaning against a wall when the bttm
More informationCONSTRUCTING STATECHART DIAGRAMS
CONSTRUCTING STATECHART DIAGRAMS The fllwing checklist shws the necessary steps fr cnstructing the statechart diagrams f a class. Subsequently, we will explain the individual steps further. Checklist 4.6
More informationBasics. Primary School learning about place value is often forgotten and can be reinforced at home.
Basics When pupils cme t secndary schl they start a lt f different subjects and have a lt f new interests but it is still imprtant that they practise their basic number wrk which may nt be reinfrced as
More informationBEAULIEU COLLEGE PRELIMINARY EXAMINATIONS 2016 MATHEMATICS GRADE 12 PAPER 2
BEAULIEU COLLEGE PRELIMINARY EXAMINATIONS 2016 MATHEMATICS GRADE 12 PAPER 2 Examiner: Mr J Ruiz Mesa Ttal marks: 150 Date: 25 July 2016 Instructins: Mderatr: Ms A Smith Time: 3hrs This questin paper cnsists
More informationComparing Several Means: ANOVA. Group Means and Grand Mean
STAT 511 ANOVA and Regressin 1 Cmparing Several Means: ANOVA Slide 1 Blue Lake snap beans were grwn in 12 pen-tp chambers which are subject t 4 treatments 3 each with O 3 and SO 2 present/absent. The ttal
More informationGroup Color: Subgroup Number: How Science Works. Grade 5. Module 2. Class Question: Scientist (Your Name): Teacher s Name: SciTrek Volunteer s Name:
Grup Clr: Subgrup Number: Hw Science Wrks Grade 5 Mdule 2 Class Questin: Scientist (Yur Name): Teacher s Name: SciTrek Vlunteer s Name: VOCABULARY Science: The study f the material wrld using human reasn.
More informationCHAPTER 2 Algebraic Expressions and Fundamental Operations
CHAPTER Algebraic Expressins and Fundamental Operatins OBJECTIVES: 1. Algebraic Expressins. Terms. Degree. Gruping 5. Additin 6. Subtractin 7. Multiplicatin 8. Divisin Algebraic Expressin An algebraic
More information7 TH GRADE MATH STANDARDS
ALGEBRA STANDARDS Gal 1: Students will use the language f algebra t explre, describe, represent, and analyze number expressins and relatins 7 TH GRADE MATH STANDARDS 7.M.1.1: (Cmprehensin) Select, use,
More informationHow topics involving numbers are taught within Budehaven Community School
Numeracy Acrss The Curriculum Hw tpics invlving numbers are taught within Budehaven Cmmunity Schl Cmpiled by James Grill - 1 - Cntents Tpic Page Intrductin 3 Basics 4 Estimating 5 Runding 6 Subtractin
More informationMath 105: Review for Exam I - Solutions
1. Let f(x) = 3 + x + 5. Math 105: Review fr Exam I - Slutins (a) What is the natural dmain f f? [ 5, ), which means all reals greater than r equal t 5 (b) What is the range f f? [3, ), which means all
More informationMonroe Township School District Monroe Township, New Jersey
Mnre Twnship Schl District Mnre Twnship, New Jersey Preparing fr 6 th Grade Middle Schl *PREPARATION PACKET* Summer 2014 ***SOLVE THESE PROBLEMS WITHOUT THE USE OF A CALCULATOR AND SHOW ALL WORK*** Yu
More informationWest Deptford Middle School 8th Grade Curriculum Unit 4 Investigate Bivariate Data
West Deptfrd Middle Schl 8th Grade Curriculum Unit 4 Investigate Bivariate Data Office f Curriculum and Instructin West Deptfrd Middle Schl 675 Grve Rd, Paulsbr, NJ 08066 wdeptfrd.k12.nj.us (856) 848-1200
More informationChapter 3: Cluster Analysis
Chapter 3: Cluster Analysis } 3.1 Basic Cncepts f Clustering 3.1.1 Cluster Analysis 3.1. Clustering Categries } 3. Partitining Methds 3..1 The principle 3.. K-Means Methd 3..3 K-Medids Methd 3..4 CLARA
More information**DO NOT ONLY RELY ON THIS STUDY GUIDE!!!**
Tpics lists: UV-Vis Absrbance Spectrscpy Lab & ChemActivity 3-6 (nly thrugh 4) I. UV-Vis Absrbance Spectrscpy Lab Beer s law Relates cncentratin f a chemical species in a slutin and the absrbance f that
More informationSpace Shuttle Ascent Mass vs. Time
Space Shuttle Ascent Mass vs. Time Backgrund This prblem is part f a series that applies algebraic principles in NASA s human spaceflight. The Space Shuttle Missin Cntrl Center (MCC) and the Internatinal
More informationCLASS. Fractions and Angles. Teacher Report. No. of test takers: 25. School Name: EI School. City: Ahmedabad CLASS 6 B 8709
SEPTEMBER 07 Math Fractins and Angles CLASS 6 Teacher Reprt Test Taken 4 5 6 7 8 Schl Name: EI Schl City: Ahmedabad CLASS SECTION EXAM CODE 6 B 8709 N. f test takers: 5 6.5 Average.5 9.0 Range (Scres are
More informationPerfrmance f Sensitizing Rules n Shewhart Cntrl Charts with Autcrrelated Data Key Wrds: Autregressive, Mving Average, Runs Tests, Shewhart Cntrl Chart
Perfrmance f Sensitizing Rules n Shewhart Cntrl Charts with Autcrrelated Data Sandy D. Balkin Dennis K. J. Lin y Pennsylvania State University, University Park, PA 16802 Sandy Balkin is a graduate student
More informationM thematics. National 5 Practice Paper C. Paper 1. Duration 1 hour. Total marks 40
N5 M thematics Natinal 5 Practice Paper C Paper 1 Duratin 1 hur Ttal marks 40 Yu may NOT use a calculatr Attempt all the questins. Use blue r black ink. Full credit will nly be given t slutins which cntain
More informationDepartment of Economics, University of California, Davis Ecn 200C Micro Theory Professor Giacomo Bonanno. Insurance Markets
Department f Ecnmics, University f alifrnia, Davis Ecn 200 Micr Thery Prfessr Giacm Bnann Insurance Markets nsider an individual wh has an initial wealth f. ith sme prbability p he faces a lss f x (0
More informationAccelerated Chemistry POGIL: Half-life
Name: Date: Perid: Accelerated Chemistry POGIL: Half-life Why? Every radiistpe has a characteristic rate f decay measured by its half-life. Half-lives can be as shrt as a fractin f a secnd r as lng as
More informationAP Literature and Composition. Summer Reading Packet. Instructions and Guidelines
AP Literature and Cmpsitin Summer Reading Packet Instructins and Guidelines Accrding t the Cllege Bard Advanced Placement prgram: "The AP English curse in Literature and Cmpsitin shuld engage students
More information1 PreCalculus AP Unit G Rotational Trig (MCR) Name:
1 PreCalculus AP Unit G Rtatinal Trig (MCR) Name: Big idea In this unit yu will extend yur knwledge f SOH CAH TOA t wrk with btuse and reflex angles. This extensin will invlve the unit circle which will
More informationThe standards are taught in the following sequence.
B L U E V A L L E Y D I S T R I C T C U R R I C U L U M MATHEMATICS Third Grade In grade 3, instructinal time shuld fcus n fur critical areas: (1) develping understanding f multiplicatin and divisin and
More informationPlant Science Course Outcome Summary Chippewa Valley Technical College
Curse Number 006-160 Credits 3 Cntact Hurs 64 Develpers Flint Thmpsn Plant Science Curse Outcme Summary Chippewa Valley Technical Cllege Infrmatin Types f Instructin Type f Instructin Cntact Hurs Outside
More informationIB Sports, Exercise and Health Science Summer Assignment. Mrs. Christina Doyle Seneca Valley High School
IB Sprts, Exercise and Health Science Summer Assignment Mrs. Christina Dyle Seneca Valley High Schl Welcme t IB Sprts, Exercise and Health Science! This curse incrprates the traditinal disciplines f anatmy
More informationA New Evaluation Measure. J. Joiner and L. Werner. The problems of evaluation and the needed criteria of evaluation
III-l III. A New Evaluatin Measure J. Jiner and L. Werner Abstract The prblems f evaluatin and the needed criteria f evaluatin measures in the SMART system f infrmatin retrieval are reviewed and discussed.
More informationSUPPLEMENTARY MATERIAL GaGa: a simple and flexible hierarchical model for microarray data analysis
SUPPLEMENTARY MATERIAL GaGa: a simple and flexible hierarchical mdel fr micrarray data analysis David Rssell Department f Bistatistics M.D. Andersn Cancer Center, Hustn, TX 77030, USA rsselldavid@gmail.cm
More informationUNIV1"'RSITY OF NORTH CAROLINA Department of Statistics Chapel Hill, N. C. CUMULATIVE SUM CONTROL CHARTS FOR THE FOLDED NORMAL DISTRIBUTION
UNIV1"'RSITY OF NORTH CAROLINA Department f Statistics Chapel Hill, N. C. CUMULATIVE SUM CONTROL CHARTS FOR THE FOLDED NORMAL DISTRIBUTION by N. L. Jlmsn December 1962 Grant N. AFOSR -62..148 Methds f
More informationCHAPTER 4 DIAGNOSTICS FOR INFLUENTIAL OBSERVATIONS
CHAPTER 4 DIAGNOSTICS FOR INFLUENTIAL OBSERVATIONS 1 Influential bservatins are bservatins whse presence in the data can have a distrting effect n the parameter estimates and pssibly the entire analysis,
More informationActivity Guide Loops and Random Numbers
Unit 3 Lessn 7 Name(s) Perid Date Activity Guide Lps and Randm Numbers CS Cntent Lps are a relatively straightfrward idea in prgramming - yu want a certain chunk f cde t run repeatedly - but it takes a
More informationProfessional Development. Implementing the NGSS: High School Physics
Prfessinal Develpment Implementing the NGSS: High Schl Physics This is a dem. The 30-min vide webinar is available in the full PD. Get it here. Tday s Learning Objectives NGSS key cncepts why this is different
More informationChem 112, Fall 05 (Weis/Garman) Exam 4A, December 14, 2005 (Print Clearly) +2 points
+2 pints Befre yu begin, make sure that yur exam has all 7 pages. There are 14 required prblems (7 pints each) and tw extra credit prblems (5 pints each). Stay fcused, stay calm. Wrk steadily thrugh yur
More informationBiochemistry Summer Packet
Bichemistry Summer Packet Science Basics Metric Cnversins All measurements in chemistry are made using the metric system. In using the metric system yu must be able t cnvert between ne value and anther.
More informationDo we really need statistics in science?
September 16, 2009 D we really need statistics in science? FWF Graduate Seminar Timthy M. Yung, Ph.D. Assciate Prfessr Department f Frestry, Wildlife & Fisheries Frest Prducts Center Dn t wrry, it will
More informationhttps://goo.gl/eaqvfo SUMMER REV: Half-Life DUE DATE: JULY 2 nd
NAME: DUE DATE: JULY 2 nd AP Chemistry SUMMER REV: Half-Life Why? Every radiistpe has a characteristic rate f decay measured by its half-life. Half-lives can be as shrt as a fractin f a secnd r as lng
More informationMODULE 1. e x + c. [You can t separate a demominator, but you can divide a single denominator into each numerator term] a + b a(a + b)+1 = a + b
. REVIEW OF SOME BASIC ALGEBRA MODULE () Slving Equatins Yu shuld be able t slve fr x: a + b = c a d + e x + c and get x = e(ba +) b(c a) d(ba +) c Cmmn mistakes and strategies:. a b + c a b + a c, but
More informationIntroduction to Smith Charts
Intrductin t Smith Charts Dr. Russell P. Jedlicka Klipsch Schl f Electrical and Cmputer Engineering New Mexic State University as Cruces, NM 88003 September 2002 EE521 ecture 3 08/22/02 Smith Chart Summary
More informationEASTERN ARIZONA COLLEGE Precalculus Trigonometry
EASTERN ARIZONA COLLEGE Precalculus Trignmetry Curse Design 2017-2018 Curse Infrmatin Divisin Mathematics Curse Number MAT 181 Title Precalculus Trignmetry Credits 3 Develped by Gary Rth Lecture/Lab Rati
More informationPLEASURE TEST SERIES (XI) - 07 By O.P. Gupta (For stuffs on Math, click at theopgupta.com)
A Cmpilatin By : OP Gupta (WhatsApp @ +9-9650 50 80) Fr mre stuffs n Maths, please visit : wwwtheopguptacm Time Allwed : 80 Minutes Max Marks : 00 SECTION A Questin numbers 0 t 0 carry mark each x x 5
More informationSimple Linear Regression (single variable)
Simple Linear Regressin (single variable) Intrductin t Machine Learning Marek Petrik January 31, 2017 Sme f the figures in this presentatin are taken frm An Intrductin t Statistical Learning, with applicatins
More informationALE 21. Gibbs Free Energy. At what temperature does the spontaneity of a reaction change?
Name Chem 163 Sectin: Team Number: ALE 21. Gibbs Free Energy (Reference: 20.3 Silberberg 5 th editin) At what temperature des the spntaneity f a reactin change? The Mdel: The Definitin f Free Energy S
More informationNew SAT Math Diagnostic Test
New SAT Math Diagnstic Test Answer Key Slve and Graph Linear Equatins 1. Slve fr z: 4 + z (+ z) z (5 ) = 6 7 1. z = 61. Given the table f values: x -9 0 9 y 11 8 7?. y = 5 If the values in the table represent
More informationTHERMAL TEST LEVELS & DURATIONS
PREFERRED RELIABILITY PAGE 1 OF 7 PRACTICES PRACTICE NO. PT-TE-144 Practice: 1 Perfrm thermal dwell test n prtflight hardware ver the temperature range f +75 C/-2 C (applied at the thermal cntrl/munting
More informationSource Coding and Compression
Surce Cding and Cmpressin Heik Schwarz Cntact: Dr.-Ing. Heik Schwarz heik.schwarz@hhi.fraunhfer.de Heik Schwarz Surce Cding and Cmpressin September 22, 2013 1 / 60 PartI: Surce Cding Fundamentals Heik
More information