# Register now to access 7 million high quality study materials (What's Course Hero?) Course Hero is the premier provider of high quality online educational resources. With millions of study documents, online tutors, digital flashcards and free courseware, Course Hero is helping students learn more efficiently and effectively. Whether you're interested in exploring new subjects or mastering key topics for your next exam, Course Hero has the tools you need to achieve your goals.

30 Pages

### L9_Probability

Course: STAT 2246, Fall 2009
School: Laurentian
Rating:

Word Count: 1645

#### Document Preview

Spaces Outline Sample and Probability Lecture 9, STAT 2246 Julien Dompierre Dpartement de mathmatiques et dinformatique e e Universit Laurentienne e 25 janvier 2007, Sudbury Julien Dompierre 1 Outline Set Theory Probability Theory Outline 1 Sample Spaces and Probability Set Theory Probability Theory Julien Dompierre 2 Outline Set Theory Probability Theory Probability A cynical person once said, The...

Register Now

#### Unformatted Document Excerpt

Coursehero >> Canada >> Laurentian >> STAT 2246

Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.

Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Spaces Outline Sample and Probability Lecture 9, STAT 2246 Julien Dompierre Dpartement de mathmatiques et dinformatique e e Universit Laurentienne e 25 janvier 2007, Sudbury Julien Dompierre 1 Outline Set Theory Probability Theory Outline 1 Sample Spaces and Probability Set Theory Probability Theory Julien Dompierre 2 Outline Set Theory Probability Theory Probability A cynical person once said, The only two sure things are death and taxes. This philosophy no doubt arose because so much in peoples lives is aected by chance. From the time a person awakes until he or she goes to bed, that person makes decisions regarding the possible events that are governed at least in part by chance. For example, should I carry an umbrella to work today? Will my car battery last until spring? Should I accept that new job? Julien Dompierre 3 Outline Set Theory Probability Theory Probability (p. 179) Probability as a general concept can be dened as the chance of an event occurring. Many people are familiar with probability from observing or playing games of chance, such as card games, slot machines, or lotteries. In addition to being used in games of chance, probability theory is used in the elds of insurance, investments, and weather forecasting and in various other areas. Finally, probability is the basis of inferential statistics. For example, predictions are based on probability, and hypotheses are tested by using probability. Julien Dompierre 4 Outline Set Theory Probability Theory Outline 1 Sample Spaces and Probability Set Theory Probability Theory Julien Dompierre 5 Outline Set Theory Probability Theory Set and Elements A set is a collection of objects. The number of objects in a set can be nite or innite. The only common property of these objects is to belong to the set. The objects in the set are also denoted elements of the set. Julien Dompierre 6 Outline Set Theory Probability Theory Membership One writes a A to denote that a is an element of (or belongs to) the set A. One writes a A to denote that a is not an element of (or does / not belong to) the set A. Julien Dompierre 7 Outline Set Theory Probability Theory Set Representation The most common method to write a set is to list all its elements inside braces. For example, the set V of vowels is denoted V = {a, e, i, o, u, y }. Julien Dompierre 8 Outline Set Theory Probability Theory Set Equality Two sets are equal if and only if they contains the same elements. Example: The sets {1, 3, 5} and {3, 5, 1} are equal. Julien Dompierre 9 Outline Set Theory Probability Theory Venn Diagram Venn diagram is a graphical representation of a set. The rectangle represents the universal set of all objects analysed. Inside the rectangle, circles are used to represent sets. We use points to denote specic elements of a set. This is the Venn diagram of the set of all vowels: U V a i y e o u Julien Dompierre 10 Outline Set Theory Probability Theory Empty Set There exists a special set that contains no element. This set is called the empty set. The empty set is denoted by or by { }. Julien Dompierre 11 Outline Set Theory Probability Theory Subset The set A is a subset of the set B, denoted A B, if and only if all the elements of A also belong to the set B. The empty set is a subset of all sets, i.e., S, for all sets S. Every set is a subset of itself, i.e. S S, for all sets S. This Venn diagram shows a set A subset of the set B. U B A Julien Dompierre 12 Outline Set Theory Probability Theory Cardinality Let S be a set. If S has exactly n elements, where n is a non negative integer, then S is called a nite set and n denotes the cardinality of S. The cardinality of the set S is denoted by n(S) (or by |S| in many textbooks). The cardinality of the empty set is 0, i.e., n() = 0. Julien Dompierre 13 Outline Set Theory Probability Theory Set Union Let A and B be two sets. The union of sets A and B, denoted A B, is the set that contains the elements that belong to the set A, or the set B, or both. A B = {x | x A or x B}. U A B Julien Dompierre 14 Outline Set Theory Probability Theory Set Intersection Let A and B be two sets. The intersection of sets A and B, denoted A B, is the set that contains the elements that belong to both sets A and B. A B = {x | x A and x B}. U A B Julien Dompierre 15 Outline Set Theory Probability Theory Mutually Exclusive Sets Two sets are disjoint or mutually exclusive if their intersection is empty. U A B Julien Dompierre 16 Outline Set Theory Probability Theory Set Dierence Given sets A and B, the dierence A B (sometimes denoted as A\B) is dened to be the set of elements of A that are not in B. In other words, A B = {x | x A and x B}. / U A B Julien Dompierre 17 Outline Set Probability Theory Theory Set Complement The complement of a set A is the set of all elements of the universal set U that are not in A. The complement of A is denoted by A (other pieces of notation used by authors are Ac and A ). A = {x | x A}. / U A Note: The union of a set with its complement gives the universal set, i.e. A A = U. Julien Dompierre 18 Outline Set Theory Probability Theory Outline 1 Sample Spaces and Probability Set Theory Probability Theory Julien Dompierre 19 Outline Set Theory Probability Theory Experiment and Outcome (p. 179) A probability experiment (or experiment) is any action or process that leads to well-dened results called outcomes. An outcome is the result of a single trial of a probability experiment. Julien Dompierre 20 Outline Set Theory Probability Theory Sample Space (p. 179) The sample space of an experiment, denoted by S, is the set of all possible outcomes of that experiment. Experiment Sample space Toss a coin S = {Head, Tail} Toss two coins S = {(H, H), (H, T ), (T , H), (T , T )} Roll a die S = {1, 2, 3, 4, 5, 6} Answer a true/false question S = {True, False} Have a baby S = {Boy, Girl} Have two babies S = {(B, B), (B, G ), (G , B), (G , G )} Julien Dompierre 21 Outline Set Theory Probability Theory Sample Space (p. 180) The experiment is rolling two dice. The sample space S of all possible outcomes is Julien Dompierre 22 Outline Set Theory Probability Theory Sample Space (p. 180) The experiment is drawing one card from an ordinary deck of card. Since there are 4 suits (hearts, clubs, diamonds, and spades) and 13 cards for each suit (ace through king), there are 52 outcomes in the sample space S: Julien Dompierre 23 Outline Set Theory Probability Theory Tree Diagram (p. 181) A tree diagram is a device consisting of line segments emanating from a starting point and also from the outcome point. It is used to determine the sample space S of all possible outcomes of a probability experiment. Julien Dompierre 24 Outline Set Theory Probability Theory Event (p. 181) An event is any subset E of outcomes contained in the sample space S. An event is said to be a simple event if it consists of exactly one outcome. An event is said to be a compound event if it consists of more than one outcome. Julien Dompierre 25 Outline Set Theory Probability Theory Classical Probability (p. 182) Classical probability uses sample spaces to determine the numerical probability that an event will happen. One does not actually have to perform the experiment to determine that probability. We suppose the events are equally likely, i.e., they have the same probability of occurring. Denition The probability P(E ) of an event E S is dened as P(E ) = n(E ) n(S) Julien Dompierre 26 Outline Set Theory Probability Theory Probability Rules (p. 184) Th...

Textbooks related to the document above:
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.

Below is a small sample set of documents:

Cuyamaca College - MATH - 3233
R code required for the question: &gt; dat = read.table(&quot;a2data_q5.txt&quot;, head=FALSE); &gt; names(dat) = c(&quot;gpa&quot;,&quot;score&quot;); &gt; attach(dat); &gt; fit1 = lm(gpa~score); &gt; plot(score, gpa,type=&quot;p&quot;); &gt; abline(fit1);(a) By typing &quot;fit1&quot; on the R command prompt you
Cuyamaca College - MATH - 3233
Assignment 7 - Math 3233Due: Nov 18, 2008 1. [4 points] State the number of degrees of freedom that are associated with each of the following extra sum of squares: (a) SSR(X1 |X2 ) (b) SSR(X2 |X1 , X3 ) (c) SSR(X1 , X3 |X2 , X4 ) (d) SSR(X1 , X2 , X
Cuyamaca College - MATH - 3233
Solution: (a) df = 1 Assuming that the full model is E(y | X1,X2) = b0 + b1*X1 + b2*X2 [SSR(X1|X2) /1] / MSE(X1,X2) ~ F(1,n-3) and the hypothesis being tested here H0: E(y | X1,X2) = b0 + b1*X1 vs Ha: E(y | X1,X2) = b0 + b1*X1 + b2*X2 (b) df = 1 Assu
Cuyamaca College - MATH - 3233
Assignment 2 (Math 3233)Due date: September 23 I will grade all the questions of the assignment. Show your work, including all the intermediate steps. Do not copy the entire output given by any package. Include only the relevant output and explain i
Cuyamaca College - MATH - 3233
Assignment 5 (Math 3233)Due date: October 16 I will grade all the questions of the assignment. Show your work, including all the intermediate steps. Do not copy the entire output given by any package. Include only the relevant output and explain it
Cuyamaca College - MATH - 3233
3.201209(3.061384, 3.341033)(3.061, 3.341)(1.959355, 4.443063)(1.959, 4.443)Note: A confidence interval `tries to catch' the population mean. (Thus it has a `fixed target'.) In contrast, a prediction interval `tries to catch' ONE SINGLE NEW
East Los Angeles College - CE - 00227
Practical Worksheet 6OPNET v9Pt1Student Download VersionNetwork Security - Firewalls and Virtual Private Networks Please Note For this worksheet, in addition to answering the questions at the end, you will have to submit screenshots of the grap
Cuyamaca College - MATH - 3233
Assignment 1 [3233 and 3293](Due: September 16)[1+1+3+2+2+2 = 11 points] Use the existing data &quot;cars&quot; [you can find all existing data on R by typing &quot;data()&quot;] for answering the following questions. a. Find the total number of observations. b. Find
Cuyamaca College - MATH - 3233
CSU Fullerton - SRT - 0801
SRT210Week TwoWeek OverviewDisaster Recovery Data Backup Tools Types of Backup Backup Storage MySQL AdministrationDisaster RecoveryDisaster Recovery is a process meant to reverse the effects of a natural and/or human-caused disasterThe list
Cuyamaca College - MATH - 3233
Cuyamaca College - MATH - 3233
Chapter 2Matrices, Random Variables, and Distributions2.1 Some Matrix Algebraan r c matrix given by a1c a2c . . . arcA matrix A = (aij ), i = 1, 2, . . . , r, j = 1, 2, . . . , c is said to be a11 a12 . . . a21 a22 . . . A= . . . . . .
Cuyamaca College - MATH - 3233
(1) Start with the model with no predictors (2) Add the predictor which gives maximum increase in your criterion (e.g., Cp, AIC) (3) Update the model (4) Repeat (2) and (3) until there is no significant increase in your criterion.Example: Cereal da
Cuyamaca College - MATH - 3233
2. RANDOM VARIABLE RESULTS Let Y be a random variable. Associated with Y is : A (cumulative) distribution function (DF or CDF), F (y) = P (Y y). A probability density function, f (y) = lim0P (y &lt; Y &lt; y + ) if Y is continuous, or a probabilit
Laurentian - C - 2206
COSC 2206 Internet ToolsThe HTTP Protocol http:/www.w3.org/Protocols/What is TCP/IP?TCP: Transmission Control Protocol IP: Internet Protocol These network protocols provide a standard method for sending and receiving messages over the Internet/ H
Allan Hancock College - CS - 7933
DISTRIBUTED AND HIGH-PERFORMANCE COMPUTING DISTRIBUTED COMPUTING IPaul Coddington Distributed &amp; High Performance Computing Research Group Department of Computer Science University of Adelaide Room 1052 http:/dhpc.adelaide.edu.au paulc@cs.adelaide.ed
Allan Hancock College - CS - 7933
Distribution, Time and CausalityFrancis VaughanLord Chief High Executioner &amp; CurmudgeonDHPC HPC Lecture Series 2000Relativity Events propagate at finite speed Simultaneity is a significant problem Actually it does not exist Minkowski Space-
Allan Hancock College - CS - 7933
BEOWULF PC CLUSTERSPaul Coddington Distributed and High-Performance Computing Group Department of Computer Science University of Adelaide paulc@cs.adelaide.edu.au October 2000Clusters of Workstations In the last few years, improved networking and
CSU Fullerton - OPS - 335
OPS335 Open System Application Server Midterm Test October 15, 2007 set by John SelmysStudent Name _ANSWERS_ 9 Digit Seneca ID _ Class Section (A/B/C) _This is a closed book test. Students are allowed to use one letter-size original reference s
Allan Hancock College - CS - 7933
DISTRIBUTED AND HIGH-PERFORMANCE COMPUTINGHPC ARCHITECTURESPaul Coddington Department of Computer Science University of Adelaide Room 1052 http:/www.dhpc.adelaide.edu.au/ paulc@cs.adelaide.edu.au July - October 2000HPC ARCHITECTURESDHPCHPC A
Allan Hancock College - CS - 7933
DISTRIBUTED AND HIGH-PERFORMANCE COMPUTING DISTRIBUTED COMPUTING MIDDLEWAREKen Hawick &amp; Paul Coddington Department of Computer Science University of Adelaide Room 1052 http:/www.dhpc.adelaide.edu.au {khawick,paulc}@cs.adelaide.edu.au July - October
CSU Fullerton - OPS - 335
Domain Name SystemThis diagram is a model of the Domain Name System (DNS), a system vital to the smooth operation of the Internet. The goal of the diagram is to explain what DNS is, how it works, and how its governed. The diagram knits together many
CSU Fullerton - IPC - 144
Assignment #2 - IPC144A DUE: Friday, March 9, 2007 Submit a hard copy of program and output as per teacher requirements. NOT email. This is a WEEKLY pay calculating and writing program. The program accepts input from the user and generates pay stub f
East Los Angeles College - RC - 0708
Unit 10 Writing conclusions and recommendationsResearch paper 64Unit 10 Writing conclusions and recommendations Aim The aim of this unit is to provide you with the knowledge to write the conclusions section for your research paper. Objectives At
CSU Fullerton - OPS - 335
NetworkmanglePREROUTINGnew connection? NYnatPREROUTINGRoutingY forwarding? NmangleINPUTfilterINPUTmangleFORWARDProcessfilterFORWARDmangleOUTPUTnew connection? NYnatOUTPUTfilterOUTPUTRe-RoutingmanglePOSTROUT
CSU Fullerton - OPS - 335
OPS335 Open System Application Server Midterm Test 1 October 15, 2007 set by John SelmysStudent Name _ANSWERS_ 9 Digit Seneca ID _ Class Section (A/B/C) _This is a closed book test. Students are allowed to use one letter-size original reference
CSU Fullerton - UNX - 122
UNICS september 1969UNIX Time-Sharing System First Edition (V1) november 3, 1971UNIX Time-Sharing System Second Edition (V2) june 12, 1972UNIX Time-Sharing System Third Edition (V3) february 1973 ric Lvnez 1998-2001Open Systems august 23, 2
East Los Angeles College - RC - 0708
Research PaperAuthor: Dr Russell Campion Editor: John Stockwell Copyright: Staffordshire UniversityContents Unit 1 Module Overview 1.1. Introduction 1.2. Learning Outcomes 1.3. Learning units of the module 1.4. Important milestones 1.5. Assessme
CSU Fullerton - SEC - 830
Enter PAMRead LineRun Module success/ignore/failRequisite &amp; FailureYesNoSufficient &amp; SuccessYesPrior Required FailureNoNoYesSufficient becomes OptionalDiscard SufficientNoLast Line ?YesOptional only one for type ?No
East Los Angeles College - RC - 0708
Section 9 Bibliography, references, appendices, and glossary sections Aim and objectives of the section This section has the following aim and objectives. Aim The aim of this section is to teach you about the last elements that complete the disserta
CSU Fullerton - IPC - 144
Subject Code and Section Assignment Number Teacher's Name Due Date Date Submitted Student Name Identification Number: IPC144A : LAB1 : JOHN SELMYS : : : KUBILAY DAGDELEN : xxxxxxxxx#include &lt;stdio.h&gt; main() { float abc(); int i; printf(&quot;Enter a v
CSU Fullerton - IPC - 144
Subject Code and Section Assignment Number Teacher's Name Due Date Date Submitted Student Name: IPC144A : LAB2 : JOHN SELMYS : : : Xiaoning Liu#include &lt;stdio.h&gt; main() { char a[9]; doit(a); printf(&quot;%s&quot;,a); } doit(char z[9]) { int i=0; while(i&lt;8)
Laurentian - BD - 891
Ministry of Training, Colleges and UniversitiesOntario Special Bursary ProgramWHAT IS THE ONTARIO SPECIAL BURSARY PROGRAM? The Ontario Special Bursary Program (OSBP) is a student financial aid program that offers bursary assistance to help cover
CSU Fullerton - OPS - 335
#1 What is your full name and Seneca student ID?My name is Open Suse and my 9-digit Seneca ID is 012-234-678.#2 Show the RSA public key generated on pc2. i.e. the file called id_rsa.pub.This is different for everyone but should be something
CSU Fullerton - OPS - 335
#!/bin/bashecho Welcome to Gateway Configurationechoecho -n &quot;Please enter the external interface: &quot;read efaceneface=\$(echo \$eface | tr '[A-Z]' '[a-z]')eface=\$nefacefp=\$(echo \$eface | cut -c1-3)lp=\$(echo \$eface | cut -c4-)if [ \$fp = eth ]the
CSU Fullerton - BIF - 703
Student Name: Thomas Nalpathamkalam.Lab5 Answers=a) END { print NR } This command print total number of lines/records in a file. NR is a special variable to store the number of lines. b) NR = 10 This command will print the 10
Allan Hancock College - CS - 7933
7045 DHPC Course 2002 Assignment 2Research a topic and write a report: - Choose *ONE* of the following topics and write a technical report on it. - Worth 20% of the final grade for the course. - Expect to spend around 20-30 hou
Laurentian - B - 638
This article was published in: Canadian Journal of Science, Mathematics, and Technology Education/ Revue Canadienne de lenseignement des sciences, des mathmatiques et des technologies, 4(4), 551-556; 2004.Review From Truth to Efficiency: Comments o
Cuyamaca College - GEOL - 3213
SAMPLING: NETS, GRAB SAMPLES, &amp; CORESGEOL 3213 MicropaleontologyMarine Sampling Devices Nets Grab samplers Corers Gravity corer Piston corer Cores Split lengthwise (working and archival halves) Photographed Sampled Stored in &quot;core librar
Laurentian - STAT - 2246
OutlineAddition and Multiplication Rules for Probability Lecture 10, STAT 2246Julien DompierreDpartement de mathmatiques et dinformatique e e Universit Laurentienne e30 janvier 2007, SudburyJulien Dompierre1OutlineAddition Rules Multipl
Laurentian - ECONOMICS - 22565
SUMMER STUDENTEMPLOYMENT APPLICATIONFor summer employment with the Greater Sudbury Police ServiceCOMPLETED APPLICATION FORMTo be left with the Information Officer at: or mail to: 190 Brady Street, Sudbury Human Resources Greater Sudbury Police
East Los Angeles College - ECON - 3010
EC3010 (2005/06). Problem Set 1. 1. Assume that the production function is of the Cobb-Douglas form, Y (t) = K(t) [A(t)L(t)]1 with A &gt; 0, 0 &lt; &lt; 1. (i) Find the steady-state capita/labor ratio (or capital per unit of labor) and output per head. (ii)
East Los Angeles College - EZ - 412
UNIVERSITY OF SOUTHAMPTONELEC6014W1SEMESTER II EXAMINATIONS 2007/08 RADIO COMMUNICATION NETWORKS AND SYSTEMSDuration: 120 minsAnswer THREE questions out of FIVE. University approved calculators may be used. An approximate marking scheme is in
East Los Angeles College - EL - 334
ELEC3028 Digital Transmission MODEMS ChenRevision of Lecture 1 Major blocks of digital communication system MODEM functions Channel has finite bandwidth and introduces noise: two main factors to consider in design Transmitted signal must hav
East Los Angeles College - EL - 334
ELEC3028 Digital Transmission MODEMS ChenRevision of Lecture 4 We have discussed all basic components of MODEM Pulse shaping Tx/Rx lter pair Modulator/demodulator map Bits symbols Discussions assume ideal channel, and for dispersive channe
East Los Angeles College - EL - 334
UNIVERSITY OF SOUTHAMPTONELEC3028ASEMESTER 1 EXAMINATION 2005/06 DIGITAL TRANSMISSIONDuration: 120 minsAnswer THREE questions, at least ONE from EACH of the two sections Calculators without text storage may be used. An approximate marking sch
CSU Fullerton - BIF - 703
BIF 703 - LAB61) Name: Edith Marcelle Siatchoua2) 1. /^[0-9]+\$/ Returns all the lines that contain only digits repeated 1 or more times. 2. /^[0-9][0-9][0-9]\$/: retuns all the lines that contain only three digits. 3. /^(\+|-)?[0-9]+\.?[0-9
CSU Fullerton - BIF - 703
BIF703 Lab #1 Answers (Lab was done using TUX)1. Name: Susan Fong Seneca Student ID: xxx xxx xxx 2. Some restrictions on passwords:Too shortToo simpleIf password is longer than 8 characters, it will be truncated to 8 characters R
CSU Fullerton - INT - 213
INT213 Assignment 4 This assignment contains a login page similar to the one you developed in Lab 8. It extends what lab 8 did by actually checking the user entered password against a password stored in a database. New users can register with the sys
CSU Fullerton - INT - 428
AgendaPerl Review Subroutines Break!Seneca College - INT428 Perl June 20, 2002Perl References DBIReviewPerl - Review - I/OWhat is the CGI method used to find out the names and values of CGI parameters? We talked about four different uses
Allan Hancock College - A - 52773640
SELF APPRAISALI came into this term not knowing what to expect. We had just finished a demanding, but rewarding first half of the year. It was going to be an interesting term, as we had an opportunity to collaborate with the Landscape students, some
Allan Hancock College - DCDB - 932
Broken head eco education centreWeeks ItineraryClients: Date: Flight Arrival: Departure: Numbers: Nutritional Requirements:OneSteel Off Site 13 September 20th September 2004 12:45 Ballina Byron DJ885 13:25 Ballina Byron DJ884 22 able bodied, 4
Universität St. Gallen (HSG) - D - 1441
CSU Fullerton - INT - 428
1. Describe what the HTTP protocol is used for. 2. (a) Which of the following colours are members of the so-called browsersafe palate? #003366 #000000 #123456 #87ad09 (b) State the general rule for enumerating members of the browser-safe palate. 3. S
Allan Hancock College - DCDB - 932
Site TourThe following is a site tour intended to be taken by a staff member as an introductory activity to walk new clients through the complex describing its attributes and unique features The tour starts at the main reception, after the clients
CSU Fullerton - INT - 428
AgendaReview CGI overviewSeneca College - INT428 Intro to CGI and HTML Forms May 30, 2002Break! Introduction to Perl Data types Statements BlocksForms - Review questionsForms - URL encodingHow many &lt;form&gt; tags can you put in an HTML page?
CSU Fullerton - INT - 428
AgendaAnnouncements Review Navigator object The location and history objectsSeneca College - INT428 JavaScript July 18, 2002Break! Document object Event handlersAnnouncementsJavaScript - Review QuestionsThe second (last) test will be on T
CSU Fullerton - INT - 428
AgendaReview Colours Tables Break!Seneca College - INT428 Introduction to HTML May 21, 2002More tablesReview exercisesGetting fancier - ColoursWhat were the six basic rules of HTML that we will follow in this course? What tag is used to i
CSU Fullerton - INT - 428
AgendaAnnouncements Document Object Break!Seneca College - INT428 JavaScript July 23, 2002Event handlers CSSAnnouncementsJavaScript - Review QuestionsThe second (last) test will be on Tuesday, August 6, 2002 The third (last) assignment wi
CSU Fullerton - INT - 428
AgendaIntroduction Class standards Accounts MovieSeneca College - INT428 Course introduction May 9, 2002INT428 - IntroductionINT428 - Topics coveredINT428 - Internet Content Development And Management The curriculum can be broken down into
Allan Hancock College - AF - 6959
James Pearse Domestic Scale Construction Project #P1 GazeboFloor details F loor Joists 120x45mm Bear er s 190x45m m F loor Beams 240x45mmD eck ing 70x18mm Post 110x110m m Galvanized stirrupsRoof detailsBr acing 30mm st eel st r apAll Timber