OC87806

OC87806

University of Toronto St. George

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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Final Guide: Nelson Rockefeller, Routine Activity Theory, Moral Panic

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30 Apr 2016
20
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Final Guide: Heroin-Assisted Treatment, Prohibition Of Drugs, Methadone

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30 Apr 2016
6
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Final Guide: Annie Sprinkle, Mass Media, Sex Tourism

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30 Apr 2016
7
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Final Guide: Drug Education, Supervised Injection Site, Harm Principle

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30 Apr 2016
4
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Midterm Guide: Office Of National Drug Control Policy, Plan Colombia, Oxycodone

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30 Apr 2016
30
Walker, samuel (2015) chapter 13: sense and nonsense about drugs and. Crime in sense and nonsense about crime, drugs, and communities, pp. Drugs and dr
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Midterm Guide: Crack Cocaine, Elizabeth Cady Stanton, Moral Absolutism

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30 Apr 2016
29
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Midterm Guide: Marketo, Sodium Bicarbonate, Conditionality

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30 Apr 2016
18
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Midterm Guide: Worst-Case Scenario Series, American Medical Association, Moral Panic

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30 Apr 2016
18
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UTSGSOC313H1Alexander ShvartsWinter

SOC313H1 Study Guide - Midterm Guide: Larceny, Plea Bargain, Financial Statement

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30 Apr 2016
6
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UTSGCSC411H1Sanja FidlerWinter

CSC411H1 Study Guide - Final Guide: Tree Structure, Linear Separability, Simple Features

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30 Apr 2016
21
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UTSGCSC411H1Sanja FidlerWinter

CSC411H1 Study Guide - Final Guide: Matrix Calculus, Polynomial, Gradient Descent

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30 Apr 2016
18
Divide data into training / testing examples. Training examples construct function approximator (hypothesis) Maps input x to predict output t. Testing
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UTSGCSC411H1Sanja FidlerWinter

CSC411H1 Study Guide - Final Guide: Gradient Descent, Likelihood Function, Multiclass Classification

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30 Apr 2016
22
Lec 08 mutli-class classification: discriminant functions for k > 2 classes, using binary classifiers. One vs all (ova) classifier use k 1 classifiers.
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UTSGCSC411H1Sanja FidlerWinter

CSC411H1 Study Guide - Final Guide: Signal-To-Noise Ratio, Information Retrieval, Reinforcement Learning

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30 Apr 2016
35
Learn to predict output when gien an input vector. Classification: 1-of-n output: learning systems = incorporating training examples info to solve prob
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UTSGCSC428H1Olivier St- CyrWinter

CSC428H1 Chapter Notes - Chapter 7: Standard Deviation, Touchpad

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30 Apr 2016
18
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UTSGCSC428H1Olivier St- CyrWinter

CSC428H1 Chapter Notes - Chapter 6: Null Hypothesis, Statistical Hypothesis Testing, 2Degrees

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30 Apr 2016
20
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UTSGCSC428H1Olivier St- CyrWinter

CSC428H1 Chapter Notes - Chapter 5: Experimental Psychology, Input Device, Likert Scale

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30 Apr 2016
13
Ch 5: experimental design (week 5 02. 08, week 6 02. 22: methodology = way an experiment is designed, carried out, hci experimental research = factoria
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UTSGCSC428H1Olivier St- CyrWinter

CSC428H1 Chapter Notes - Chapter 3: Interaction Technique, Wysiwyg, Scrollbar

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30 Apr 2016
25
3d 6 degrees of freedom (dof) 3 dof for orientation ( x, y, z) Soft controls are also displays blurs display-control distinction. Congruent spatial map
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UTSGCSC428H1Olivier St- CyrWinter

CSC428H1 Chapter Notes - Chapter 2: Clothing, Visual Search, Retina

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30 Apr 2016
18
Ch 2: human factors (week 2 01. 25: newel"s time scale, (2) hearing = audition. Sound = cyclic fluctuations of pressure in a medium (air) Ex. sources:
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Final: 2 Interaction Design Process

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12 Jan 2016
15
Ch 9 the process of interaction design. What is involved in interaction design: interaction design, is a process. A goal- directed problem solving acti
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Final: 1 Intro

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12 Jan 2016
14
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Study Guide - Final Guide: Spreadsheet, Data Analysis, Conversation Analysis

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12 Jan 2016
6
Ch 7 data gathering. Five key issues of data gathering: 1. Identifying participants: identify specific goals for study before gathering data. Goals inf
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Study Guide - Final Guide: Exact Sequence, Goms, Jargon

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12 Jan 2016
12
May determine areas for improvement, inform new products: when to evaluate. Reduce outside influences, distractions methods in a controlled setting; us
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 12: Focus Group, Web Analytics, Iterative Design

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12 Jan 2016
9
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 14: Null Hypothesis, Usability, Dependent And Independent Variables

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12 Jan 2016
10
Usability testing test whether product being developed is usable by the indeded user population to achiueve the tasks for which it was designed: may in
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 15: Google Analytics, Web Analytics, Exact Sequence

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12 Jan 2016
10
Inspections evaluation by experts role-playing the users for whom the product is designed for: analyze aspects of interface, identify potential usabili
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 13: Heuristic Evaluation

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12 Jan 2016
22
Determine the goals: what are the high-level goals of the evaluation, goals guide evaluation determines scope, affect methods. Personal records incl. d
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 11: Mockup

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12 Jan 2016
17
Evaluation and feedback are central to interaction. Stakeholders can see, hold, interact with a prototype more easily than a document or a drawing: tea
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 10: Interaction Design

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12 Jan 2016
10
Users" reactions and performance to scenarios, manuals, simulations & prototypes are observed, recorded and analysed: 3. When problems are found in use
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter 9: 2014.02.04

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12 Jan 2016
11
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 8: Web Analytics, Jargon, Preempt

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12 Jan 2016
7
Setting goals: need to id specific goals for study before gathering data. Goals influence nature of data gathering sessions, techniques used, anaylsis
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 7: Spreadsheet, Nvivo, Critical Incident Technique

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12 Jan 2016
9
Quatitative data numbers, or can be expressed as number: quantitative analysis numerical methods to acertain size, magnitude, amount images. Qualitativ
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 3-p1: Written Language, Bmw S38, Text Display

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12 Jan 2016
11
Cognition definitions: (general) modes of cognition (norman, 1993) Experiential cognition state of mind which one perceives, acts, reacts to surroundin
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter 3-p2: 2014.01.21

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12 Jan 2016
18
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter Notes - Chapter 2: Wii, Augmented Reality, Kinect

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12 Jan 2016
13
Designing for a new user experience, how does the proposed design ideas support, change, or extend current ways of doing things: having a good understa
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UTSGCSC318H1Olivier St- CyrWinter

CSC318H1 Chapter 1: 2014.01.07

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12 Jan 2016
12
Good and bad design: why is tivo remote so much better designed. Creeping featurism the ongoing expansim or addition of new features in a product, goin
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UTSGCSC302H1Matt MedlandWinter

CSC302H1 Final: notes

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12 Jan 2016
16
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UTSGCSC302H1Matt MedlandWinter

CSC302H1 Study Guide - Midterm Guide: If And Only If, 2-Step Garage, Vital Signs

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12 Jan 2016
17
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UTSGCSC302H1Matt MedlandWinter

CSC302H1 Lecture 23: 2014.04.01

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12 Jan 2016
15
Estimates: in planning, neet to estimate f, n, and t; such that estimated (f ) estimated ( n ) estimated (t , estimates never 100% certain. Ex. feature
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UTSGCSC302H1Matt MedlandWinter

CSC302H1 Lecture Notes - Lecture 24: Capability Maturity Model, Random Variable, Reverse Engineering

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12 Jan 2016
11
O given code, reverse engineer class files from it. Can you use conway"s law to your advantage. If so how (what) to look for to show that it really is
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UTSGCSC302H1Matt MedlandWinter

CSC302H1 Lecture 22: 2014.03.27

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12 Jan 2016
13
Hofstadter"s law: it always takes longer than you expect, even when you take into account hofstadter"s. Developer leave the team decrease n. # vacation
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