7 Pages

# Organismal Biology - Graph Instructions

Course Number: BIO 1130, Fall 2009

College/University: University of Ottawa

Word Count: 1809

Rating:

###### Document Preview

APPENDIX Graphing Data Use a graph when you wish to: see overall trends, patterns or relationships in the data, compare two or more factors in a general or quantitative fashion, present large data sets in a comprehensible way and analyse data. General Principles of Graph Construction Towards a clear comprehension 1. 2. 3. Transform observations into graphical form. Proofread your graphs (at least three times)....

##### Unformatted Document Excerpt
Coursehero >> Canada >> University of Ottawa >> BIO 1130

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.

Data Use APPENDIX Graphing a graph when you wish to: see overall trends, patterns or relationships in the data, compare two or more factors in a general or quantitative fashion, present large data sets in a comprehensible way and analyse data. General Principles of Graph Construction Towards a clear comprehension 1. 2. 3. Transform observations into graphical form. Proofread your graphs (at least three times). Work towards clarity. Evaluation Criteria Evaluation criteria for graphs (include but are not limited to the following): Presentation: Graph type, Data : ink ratio, Layout Data: Symbols, Axes units, Axes labels Caption: Description, Analysis (If applies), nomenclature All graphs must be done by hand and on millimetre paper. Presentation I- Plot type When choosing the plot type one should consider whether the graph is appropriate for scientific presentation and the way that the data were collected. The simplicity of computers in plotting will raise questions that one should address: the appropriateness of histograms vs. pie charts, vs. the data points themselves. Which is appropriate, when and under what circumstances? Here are some examples of different graph or plot types: Bar graphs (horizontal or vertical) These are very simple graphs that consist of a number of proportional bars of equal width and variable length. Variations in quantity are scaled along one axis only (values may be scaled on the x-axis for horizontal bar graphs and on the y-axis for vertical bar graphs). Bars can represent a wide range of variables, i.e. places, areas, items of different types and time periods. They may be used on maps as alternatives to pie charts. Their bulk and clumsiness restrict their visual impact. They allow quantitative information to be scaled against time, distance or some other variable. Bar graphs should not be confused with histograms, which have quantitative scale along both axes. Histograms Histograms are similar to bar graphs in that they consist of a number of proportional bars of equal width and variable length. They differ in that histograms are used to analyse and study distributions. Also, histograms have a quantitative scale on both axes while bar graphs have a quantitative scale on only one axis. Typically, before data are plotted on a histogram, the data range must first be divided into a number of intervals and the number of observations falling into each interval recorded. The percent of observations in each interval can be calculated by dividing the number of observations in the interval by the total number of observations and multiplying the resultant term by 100. These results are then plotted with the intervals on the x-axis and the percent values on the y-axis, resulting in a series of vertical bars representing the intervals of the distribution. Pie charts A pie chart shows the relationship or proportion of parts to a whole. It is useful if one element makes up a significant portion of the whole. Its form is that of a circle divided up into sectors (pie slices). Since generally no scale is provided one must judge the sizes of the angles to infer percentages or proportions represented by a given slice. This type of chart is poor for determining exact values and according to Tufte (1983), "should never be used". Straight-line graphs They are generally used when many data points (n>30) are available at constant intervals, in order to see trends or changes in a variable through time. Points are connected by straight lines to indicate the fluctuation in values through time. One may also use running means to determine trends through time (this is simply the summing of several data points over several intervals and then dividing by the number of intervals). Transect graphs When using the transect method to collect data one can plot the information in the form of a graph with distance scaled along the horizontal axis. The important feature of any transect graph is that it represents variation in value or quantity along a line, which may or may not be straight. Scatterplots Scatterplots are used to investigate the relationship between two different sets of data. In these graphs variable quantities are scaled along both axes. Each item must have two values, one from each set of data. These are used as x and y co-ordinates, allowing the item to be plotted as a point on the graph. There should be some logical reason for expecting a relationship between the two variables concerned. Otherwise, any relationship found may be purely coincidental. Usually, there is a cause and effect association between the two data sets plotted. Where a causal factor or independent variable can be clearly defined, its customary to scale it on the horizontal axis (x axis), while the resultant factor or dependent variable is placed on the vertical axis (y axis). Scatter diagrams allow a subjective evaluation of the degree of relationship between the two variables. Trends or tendencies may be clear from the graph. At times one variable may increase while the other decreases or vice versa (an indirect relationship). If both variables increase or decrease in conjunction with each other, a direct relationship is present. The closer the points on a scatter diagram are to being on a straight or curved line, the greater the degree of relationship (correlation) between the two variables. A line of best fit (by eye) or a regression line may also be plotted to further illustrate the relationship between the two variables. Two panel bar or graph histogram (vertical layout): Y axis common for 2 panels Y axis scale and value range is the same for both panels X axis label is only written on lower panel axis (ticks marks on both axis). Only one symbol key is presented Data to ink ratio The data to ink ratio tries to emphasise the importance of the data itself relative to the other elements of the graph. Data-ink ratio = amount of ink used for the data / total amount of ink used to print the graph. Maximise the data to ink ratio by reducing the amount of non-data ink (grids, borders and 3D effects). Layout Layout should consider the size, placement and orientation of the graph. Typically the graph uses 2/3 of the page, the last 1/3 being used for the caption. II- Data Symbols 1. Make the data stand out. Avoid unnecessary or superfluous ink. 2. Use visually prominent plotting symbols to show the data. The size and appearance of the symbols should be considered. Open or filled circles, squares and triangles are, for example, appropriate. Data symbols should be more prominent than any line linking them or drawn through them. 3. Use a reference line when you wish to show an important value across the entire graph but it should be less prominent than the data. 4. Lessen the visual impact of data labels so they do not interfere with the data or disorder the graph. 5. Symbols that overlap must be distinguishable. 6. If data sets superpose, they should be visually separable. 7. If more than one series of data is plotted, a key for the symbols should be used. Place the symbol key within the rectangle of the graph in a space devoid of data. If this is not possible, place it either immediately above or to the right of the x-y axis area. 8. Don't fill the figure with too many details. 9. After reduction or reproduction, visual clarity must be maintained. Axis units and scale 1. Choose an interval for the x- and y- axis that includes the entire data range. Zero does not have to be in this interval. 2. Choose an interval so that the data occupy most of your figure. 3. If data are to be compared between different graphs, choose similar scales. 4. Don't put too many divisions (tick marks) on the axes. Three to five tick marks (excluding zero) are enough to give the measurement scale and allow accurate determination of data points. 5. Tick marks should point outwards so they do not obscure data points. 6. Only when necessary use a scale break (a break in the x- or y-axis). Do not connect the data points on each side of the break. Axis labels 1. Axes labels must be appropriate for the variables plotted and indicate the units that are involved. 2. Appropriate SI abbreviations for units must be used (see appendix) 3. If you plot logarithms of a variable, the axis label should correspond to the tick mark labels. Error Bars 1. If means are plotted, error bars must be indicated. Error bars may be either the sample standard deviation, the standard error of the mean or the 95% confidence interval. 2. The error bars should be slightly less prominent than the data points. 3. If a bar graph is used, only present the means + the error bars. III- Caption Under almost all circumstances, a graph presented for publication must have a caption. It must be placed immediately below the graph. It should begin with a figure no. (e.g. Figure 2). What should be included in the caption? 1. The first sentence in the caption should be a specific and informative title. If the graph presents a comparison, the first sentence should mention it. 2. The body of the caption should be sufficient enough to explain briefly the mechanism by which the data were collected, analysed and the number of samples involved (e.g. n=30 or n=10 to 15). 3. If only two symbols are used they may be explained here or in a key. For more than 2 symbol types use a key (see Symbols). Binomial nomenclature of Organisms In addition to common name(s) given to organisms, each of them possesses a unique name based on phylogenetic relationships it shares with all other organisms. The most common way to name an organism is to use the binomial nomenclature initiated by the 18th century biologist Linnaeus. This nomenclature indicates the genus and species, the two most specific characteristics in the hierarchy of designations. Specific typography rules apply: only the first letter of the genus is capitalized (not the species name) and both genus and species are printed in italics (or underlined when hand written). Ex: dog (common name) is Canis domesticus or Canis domesticus. Binomial nomenclature must be used in captions. Analysis 1. If means are presented this should be stated. 2. If data are transformed (if you did calculation), the type of transformation should be indicated. 3. Where statistical significance has been determined, the result and the level of probability should be included. 4. The method of curve fitting should also be mentioned here. 5. Clearly explain error bars. One of the following three statements should unambiguously explain your error bars: Means one sample standard deviation. Means one standard error. Means the 95% confidence interval. A Sample Line Graph 5000 Abundance (no./10 ml) 4000 3000 2000 1000 0 0 DO NOT PRINT THIS GRAPH 3 6 9 TSeconds (s) ime (days) 12 Figure 1: Population growth of Paramecium aurelia at 20oC in a sterile solution of 1% (w/v) proteose peptone. Mean totals ( one standard error) of 20 counts are presented. A least squares polynomial is fitted to the data (y=25.88x2 + 51.76x + 5, R2=0.98)

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:

University of Ottawa - BIO - 1130
Marking Bio1130 Introduction to Organismal BiologyIn General The answer grids that you receive will also be posted for the students to see. You do not need to add any comments, correct answers or additional comments on the students exams. There will be
University of Ottawa - BIO - 1130
CHM2132B Midterm Friday October 28th, 2004 Name: _ Student #: _ This is a closed book exam with no notes allowed. Calculators are permitted. Write all the formulas that you use to solve the questions and show all your work. Remember to include units in al
University of Ottawa - BIO - 1130
CHM2132 Midterm Friday October 26th, 2007 Name: _ Student #: _ This is a closed book exam with no notes allowed. Calculators are permitted. Write all the formulas that you use to solve the questions and show all your work. Remember to include units in all
University of Ottawa - PHY - 1321
PHY 1321 and PHY 1331Summer 2009Professor: D r. Selahattin CelebiASSIGNMENT 3Due date: JL 30, 2009 3:30 PM5.10.A9.00kghangingblockisconnectedbyastringoverapulleytoa5.00kgblockthatissliding onaflattable(Fig.P5.10).Thestringislightanddoesnotstretch;the
University of Ottawa - MAT - 2378
Q2A)B) n=36 thus, Root(36)=6 classes, interval = max-min/root(n), (57-20)/6 = ~6.2 Interval [20, 26.2[ [26.2, 32.4[ [32.4, 38.6[ [38.6, 44.8[ [44.8, 51[ [51, 57.2] Frequency 7 12 8 3 2 4C) D) Median: 30.5 M ean: Sum(all data)/36 = 33.75E)
University of Ottawa - MAT - 2378
MAT2378B: Assignment 1Due date: 23 September 2009Total number of points: 33Q1. (2.1 in the textbook) For parts (a) and (b), (i) identify the variables in the study; (ii) for each variable, write the type of variable (cathegorical/ordinal, discrete etc.
University of Ottawa - MAT - 2378
Assignment 3Due date: 21 October 2009Total number of points: 32Q1. A medical research team wished to evaluate a proposed screening test for Alzheimers disease. The test was given to a random sample of 450 patients with Alzheimers disease, in 436 cases
University of Ottawa - MAT - 2378
MAT2378Pawel Lorek (based on Rafal Kuliks slides) (Updated) version: September 15, 2009MAT2378 Probability and Statistics for the Natural SciencesChapter 2Comments These slides cover material from Chapter 2, Sections 2.1-2.6. They are almost complete
University of Ottawa - MAT - 2378
1Q1. (2.23) As a part of a classic experiment on mutations, ten aliquots of identical size were taken from the same culture of the bacterium E.coli. For each aliquot, the number of bacteria resistant to a certain virus was determined. The results were as
University of Ottawa - MAT - 2378
Multiple choice set 1INFO: practice multiple choice questions related to slides for chapter 2, 3 and assignments 1, 2.Q1. (2.20) The weight gains of beef steers were measured over a 140-day test period. The average daily gains (lb/day) of 9 steers on th
University of Ottawa - MAT - 2378
Multiple choice set 2INFO: practice multiple choice questions related to chapters 3, 4, 5 and assignment 3.Q1. A factory employs several thousand workers, of whom 30% are from non-English speaking background. If 15 members of the union executive committ
University of Ottawa - BCH - 3170
B CH/B IO 3170 Molecular Biology second mid-te rm November 2010 Dr. Odette Laneuville P a r t 1. M ultiple Choices Questions (20 at 2 pts each): P a r t 2. Essay Questions Short (4 at 5 pts each): SELECT 4 OF T H E 6 QUEST IONS P a r t 3. Essay Questions
University of Ottawa - BPS - 3101
BPS3101PRACTICE QUESTIONS #3Fall 2010QUESTION 1 Suppose that the human gene X encodes an enzyme which binds drug D through a domain encoded within exon 2. The gene X region is shown below: exons = black, introns = dotted lines; intron sequence = lower
University of Ottawa - BPS - 3101
Practice set #2, question 1black bars = exons so arrows show positions of UTRsNorthern analysisSouthern analysis B E H E+H B E H E+H~2 kb6 kb 5 kb 3 kb 1 kb -Probe: exon 3intron 2Probe: exon 3intron 2Practice set #2, Question 2.TCCGA.GAGAATCTC
University of Ottawa - BPS - 3101
Practice set #3, Question 2150 bp 200 bp 300 bp 250 bp50 bpWild type (no IS in gene A) Strain with IS at position #1 Strain with IS at position #2 Strain with IS at position #3 Strain with IS at position #4Response to drug M Sensitive Resistant Resist
University of Ottawa - BPS - 3101
BPS3101PRACTICE QUESTIONS #1FALL 2010QUESTION 1 Does the sequence shown below have the potential of encoding part of a protein?5. GCAAAGTTGTAGGGGAAGCTAAGCTCGAAATAAGGTGTGCCTATT. 3 3. CGTTTCAACATCCCCTTCGATTCGAGCTTTATTCCACACGGATAA. 5Tip: To check your a
University of Ottawa - BPS - 3101
BPS3101PRACTICE QUESTIONS #2FALL 2010QUESTION 1 You have sequenced the region of an insect genome containing gene X, shown on the restriction map below (black bars = exons, dotted lines = introns). Arrows show the positions of short stretches of that s
University of Ottawa - BPS - 3101
Question 1cE550 bpRFLP analysisA420 bpEA800 bpA250 bpE750 bpE170 bpthese fragments will be samesame in any rabbitSo if PCR amplify just blue region &amp; then restrict with enzyme A &amp; run on gel. we can ignore other restriction fragmentsHomo
University of Ottawa - BPS - 3101
QUESTION 1aBioinformatics: ORF finder - potential reading frame? BLAST - homologues in protein data banks? Check for codon bias ? Experimental: Is this region of genome transcribed? Is there a phenotypic effect if knock-out of putative gene? Zoo blot (to
University of Ottawa - CHM - 3120
University of Ottawa - BCH - 3356
BCH3356 MolecularBiology LaboratoryFinal exam: This exam is worth 30 % of the final mark for the course BCH3356Name:_ Student number:_InstructionsAll questions should be answered within the space provided on THIS COPY EXAM. You may use the endorsemen
University of Ottawa - CHM - 3122
Answers for Student Exercises 1.1 to 1.5Atom Type Hydrogen Carbon Nitrogen Oxygen Sulfur Bromine # of Atoms Mass 1.00783 22 10 12.00000 14.0031 0 15.9949 0 31.9721 0 78.9183 0 Exact Mass Total Mass 22.17226 120.00000 0.00000 0.00000 0.00000 0.00000 142.1
University of Ottawa - CHM - 3122
Answers for Student Exercise 2.1 2.912.1. Since the indicated carbon of phenylacetonitrile is sp3 hybridized, it is reasonable for this compound to show CH stretching at less than 3000 cm-1 (2960-2940 cm-1). Where as benzonitrile has only aromatic CH st
University of Ottawa - CHM - 3120
University of Ottawa - CHM - 3120
CHM 3120 Assignment #1:1) Synthesize the syn and anti isomers of the following molecule:CH3 PhOH2) Predict the major product in each of the following reactions:a)ONaBH4Ob)O1) LDAO Et2)NBn2 H Oc)OH+ (cat.)HN Hd)1)O N H2) 3) H+/H2OCH
University of Ottawa - CHM - 3120
University of Ottawa - CHM - 3120
University of Ottawa - CHM - 3122
Chemistry 3122 Applied Spectroscopy Infrared Spectroscopy ModuleProf. Fogg Fall 2010Infrared Spectrophotometer Requirements: source of IR radiation, sample, detector2IR Spectrophotometer3Absorption Spectrum measure change in intensity of light at ra
University of Ottawa - CHM - 3122
Chemistry 3122: Applied SpectroscopyMass Spectrometry ModuleProf. D.E. Fogg Fall 2010Mass Spectrometry form beam of ions; separate into different mass-to-charge ratios (m/z) by applying electrostatic or magnetic elds or both. nominal mass = integer ma
University of Ottawa - CHM - 3122
IR Lecture 4 problem 1H(cm-1)assignment sp ( C-H) sp3 (C-H) (C C) C-H bend (sym, asym, CH3 and CH2) C-H bend fundamental - strong; expect to see an overtone (first harmonic) at ca. 124013314 (s) 2850-3000 (s) 2126 (m) [1463 (s)] 637 (s)IR Lecture 4
University of Ottawa - CHM - 3122
IR Lecture 5 (problem 8)OO( C(O)O), ( OCC) (cm-1)assignment sp2 (C-H) - no sp3 (C-H)? (C=O) looks like ester (1750-1735) with C=O strengthened by conjugation on the &quot;ether&quot; end (C=C) for aromatic C-H, C=C oop bend; monosubstituted phenyl13075, 3052
University of Ottawa - BCH - 3356
BCH3356 MolecularBiology LaboratoryFinal exam: This exam is worth 40 % of the final mark for BCH3356Name:_ Student number:_InstructionsAll questions should be answered within the space provided on THIS COPY EXAM. You may use the endorsement of pages
University of Ottawa - CHM - 3120
University of Ottawa - CHM - 3120
University of Ottawa - CHM - 3120
Name: Student #:/\fCf/\JCHM 3120 Intermediate Organic Chemistry (Fall 2007)EXAM#1Instructions: Please answer all questions in the space provided. If you require additional space use the back pages. Model kits are permitted. There are 5 questions plus
University of Ottawa - CHM - 3122
SJ*ur'*&quot;CHM3 lZZ _p ractice xam _ 2 010 eI N otet hatthis s ample xami s l ongerthanhe m idterm fOctober 0w ill b el e t o 2l. S hort nswers a :(a) D etermine he d egreeo f u nsaturation f a c ompound t o w ith m olecularormulaC rH3ClrOr. f3 2 r l -
University of Ottawa - CHM - 3122
University of Ottawa - CHM - 3122
Practice problems No. 1CHM3122 - 20101. Exercise 3.10 B in Silverstein (pages 177 &amp; 186).2. Exercise 3.1 (c), (h), (i) in Silverstein (pages 177 &amp; 178).3. For each molecule, indicate the number of different groups of protons which exhibit chemical equ
University of Ottawa - CHM - 3122
-&amp;8&quot;2 z 'L t &gt;A C.'-y41. z zI) (\i( 1 uz\' , &quot;y+A fo / P&quot;'t '^'[ cfw_ nz). /BrukerB iospinBRUKERL'.^5 trr)tr1a\BrukerB ioSpin'[5t3*shrK]ly*f'BrukerB ioSpinBRUI(ERCTLQ -= C VtiBrukerB ioSpin
University of Ottawa - CHM - 3122
Practice problems No. 2CHM3122 - 2010(a) Describe the proton (1H) spin systems in the following molecules using Pople notation. (i) chlorobenzene at high field (ii) CH2=CHF(b) Do the methylene protons in the following molecules exhibit chemical equival
FIU - HR - 550
Analyzing Buyer Behavior Instructions: In this scenario-based activity, you will need to review the scenario presented to you, your role in the process, and then read the viewpoints of the key employees that have been assigned to help you with this activi
Iowa State - ACCT - 284
McGraw-Hill/IrwinCopyright 2011 by The McGraw-Hill Companies, Inc. All rights reserved.Chapter 1Business Decisions and Financial AccountingPowerPoint Authors: Susan Coomer Galbreath, Ph.D., CPA Charles W. Caldwell, D.B.A., CMA Jon A. Booker, Ph.D., CP
Iowa State - ACCT - 284
McGraw-Hill/IrwinCopyright 2011 by The McGraw-Hill Companies, Inc. All rights reserved.Chapter 2Reporting Investing and Financing Results on the Balance SheetPowerPoint Authors: Susan Coomer Galbreath, Ph.D., CPA Charles W. Caldwell, D.B.A., CMA Jon A
UBC - ECON - 326
Economics 326 Methods of Empirical Research in Economics Lecture 1: IntroductionHiro Kasahara University of British Columbia January 4, 2010What is Econometrics?Econometrics is concerned with the development of statistical methods for:I I IEstimating
University of Phoenix - CRT - 205
Axia College MaterialAppendix E Critical Analysis FormsFill out one form for each source.Source 1 Title and Citation: Domestic Violence Often Leads to Homelessness &quot;Domestic Violence Often Leads to Homelessness.&quot; The Homeless. Ed. Louise Gerdes. Detroi
Bryant & Stratton - ACCT - 101
Brawn Demolition Co Work Sheet For year ended April 30, 2009Unadjusted Trial BalanceAdjustmentsNo. Accounts 101 Cash 126 Supplies 128 Prepaid Insurance 167 Equipment 168 Accumulated Dep. Equip. 201 Accounts payable 203 Interest payable 208 Rent payable
City University of Hong Kong - CS - CS3283
CS3283 Distributed SystemsLecturer: K Y Lam Rm: Y6414 Tel: 2788-9807 Email: cskylam@cityu.edu.hk http:/www.cs.cityu.edu.hk/~kylamCourse web page: http:/www.cs.cityu.edu.hk/~cs32831Course Objectives To introduce the important basic concepts, problems
City University of Hong Kong - CS - CS3283
CS3283 Distributed Systems Mid-term Test (1 hr 10min) Semester A, 2010/11 Name: _ Student ID: __Answer ALL questions. Write your answers on the space provided. (Totally 58 marks)Please ensure that your handwritings are readable and grammatically correc
City University of Hong Kong - CS - CS3283
CS3283 Distributed Systems Mid-term Test (1 hr 10min) Semester A, 2010/11 Name: _ Student ID: __Answer ALL questions. Write your answers on the space provided. (Totally 58 marks)Please ensure that your handwritings are readable and grammatically correc
City University of Hong Kong - CS - CS3283
CS3283 Distributed Systems Seating Plan for Mid-term Quiz Name CHAN Ho Chun CHEUNG Lam Yuen CHUNG Wing Ho FUNG Yung Kam GAO Wei HUNG Tin Wai HUNG Yuk Man KO Chun Kit LEE Hin Yeung LEE Shun Kan LI Shun Fung LIU Ka Fai LOUIE Ting Kit Terris MAARLEV Mads Slo
City University of Hong Kong - CS - CS3283
CS 3283 Distributed System Assignment 2 ReportLee Hin Yeung Eric Gao Wei Gavin Fung Yung Kam Wang Xuwei ChaosHistory of Cloud ComputingBefore we look deeper on how the cloud computing design and operate, we need to know the history of that. The term cl
City University of Hong Kong - CS - CS3283
L ee Hin Yeung Eric Gao Wei Gavin Fung Yung Kam Wang Xuwei ChaosOutlineHistory of Cloud Computing and Service OrientedA rchitecture Cloud Computing Service Oriented Architecture Relationship between Cloud Computing and Service Oriented Architecture Con
City University of Hong Kong - CS - CS3283
Cloud Computing and Services Oriented ArchitectureCS3283 Distributed System Assignment Two Topic 150629258 51269295 50808088 51013947 Cheng Chi Shing Cheung Hiu Lun Lau Chun Yin Wong Wing YinTable of Contents1. Introduction . 3 History . 3 Background
City University of Hong Kong - CS - CS3283
Topic 1Cloud Computing and Services Oriented ArchitectureChengChiShing50629258 CheungHiuLun51269295 LauChunYin50808088 WongWingYin510139471Content Background Pros and Cons Definition of Cloud Computing Components of Cloud Computing Definition of Serv
City University of Hong Kong - CS - CS3283
CS3283 Distributed Systems Assignment 2Replication management and Google file systemsLecturer: Chung Wing Ho Hung Yuk Man Louie Ting Kit Yip Kai WingDr. K.Y. Lam 51320867 51241471 51265825 51369534Table of Content1. 2. 3. Abstract . 3 Introduction .
City University of Hong Kong - CS - CS3283
REPLICATION MANAGEMENT AND GOOGLE FILE SYSTEMSCS3283 Distributed SystemsLecturer: Dr. K. Y. LamChung Wing Ho Hung Yuk Man Louie Ting Kit Yip Kai Wing51320867 51241471 51265825 51369534REPLICATION Creating and maintaining multiple copies of data/obje
City University of Hong Kong - CS - CS3283
CS3283 Distributed System Assignment 2CS3283 Distributed SystemReport for Team WorksTopic 2: Replication Management and Google file systemsI declare that the materials presented in this assignment are original except explicitly acknowledged.Group Mem
City University of Hong Kong - CS - CS3283
CS3283Distributed SystemTopic2:Replication management&amp; GoogleFileSystemPresentedby: LEEHOMING (51306210) TSANGTSZKIT (51274232) CHEUKHIUKING (51362570)1DistributedFileSystem GoogleFileSystem=DistributedFileSystem? Jointogetherthefilesystemofindividua
City University of Hong Kong - CS - CS3283
CS 3283 Distributed Systems Assignment 2Topic:P2P middlewareWong Chong Yun 50667496 What is Peer-to-peer (P2P)? P2P systems represent a model for the construction of distributed applications architecture in which data and computational resources are con
City University of Hong Kong - CS - CS3283
P2P middlewareCS3283WhatisPeerto Peer(P2P)?AimAims sharingresourcesonaverylargescale byeliminatinganyrequirementWhyP2P? Own and manage themselves Share resources Scalability of the usersHistory 1st generation o Napster music exchange service 2nd g
City University of Hong Kong - CS - CS3283
CS3283 Distributed Systems (Assignment Two)Group 2: Topic 3 Middleware Services for Peer-to-Peer ComputingStudent Name: Cheng Kai Yee, Martin Leung Chi Chung, Oliver Wong Ka Wing, TigerStudent ID: 50768560 50744408 50792707Date of Submission: 29-Nov-2