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All Educational Materials for OMIS 2010 at York University (YORKU)

YORKOMIS 2010Linda LakatsWinter

OMIS 2010- Midterm Exam Guide - Comprehensive Notes for the exam ( 25 pages long!)

25 Page
11 Oct 2017
Omis 2010 assignment b1 winter 2017. Groups can not consist of students from other sections of the course: only one person uploads the assignment, addi
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YORKOMIS 2010allFall

OMIS 2010 Study Guide - Statistical Parameter, Statistic, Point Estimation

1 Page
3 Dec 2012
The objective is to determine the approximate value of a population partameter on the basis of a sample statistic. Eg the sample mean is used to estima
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YORKOMIS 2010AlexanderWinter

OMIS 2010 Study Guide - Final Guide: Mean Absolute Difference, Block Design, Load Management

16 Page
23 Oct 2013
Calculator; formula and tables book: please place your i. d. card on your desk. Instructions: you are not allowed to leave the examination room until o
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YORKOMIS 2010AlexanderWinter

Practice Final Exam.doc

15 Page
23 Oct 2013
Calculator; formula and tables book: please place your i. d. card on your desk. Instructions: you are not allowed to leave the examination room until o
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YORKOMIS 2010Henry KimFall

OMIS 2010 Study Guide - Final Guide: Digital Millennium Copyright Act, Chief Privacy Officer, Google Account

19 Page
15 Apr 2014
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YORKWinter

ITEC 1000 Lecture Notes - Lecture 8: Customer Retention, Call Centre, Customer Service

13 Page
25 Feb
True / false questions: crm systems store customer account data in multiple specialized databases and then make it available throughout a company via i
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YORKWinter

ITEC 2600 Quiz: ITEC2600 Exercise 2

1 Page
25 Feb
Lab exercise 2: redo all examples from class, create anonymous functions for the following math functions, where input argument(s) x or y can be a vect
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YORKWinter

ITEC 2600 Study Guide - Quiz Guide: Underweight, Moodle

2 Page
25 Feb
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YORKWinter

ITEC 2600 Study Guide - Quiz Guide: Cartesian Coordinate System, Matlab

2 Page
25 Feb
Re-write nding largest and smallest number as user-de ned function. Re-write a matlab script le to implement above by calling your function: generate a
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YORKWinter

ITEC 2600 Study Guide - Quiz Guide: Ellipse

2 Page
25 Feb
The remaining loan balance, b, of a xed payment n years mortgage after x years is given by: 12 )12x] where l is the loan amount, and r is the annual in
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YORKWinter

ITEC 2600 Study Guide - Quiz Guide: Matlab

1 Page
25 Feb
Lab exercise 5: pratice debugging techniques in the following questions, redo all examples from the lecture, write a user-de ned function to calculate
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YORKWinter

ITEC 1000 Lecture Notes - Lecture 4: Ebcdic, Extended Ascii, Pcx

12 Page
25 Feb
Chapter 4 data formats: input from a device that represents a continuous range of data is known as, metadata, analog data, various data , discrete data
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YORKWinter

ITEC 2600 Study Guide - Quiz Guide: Row And Column Vectors, Matlab, Exclusive Or

3 Page
25 Feb
Lab exercise 1: explain what the following matlab commands produce, then excute the following expressions in. 10 > 5 + 2 (10 > 5) + 2. "c"== "d"- 1 ||
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YORKWinter

ITEC 2600 Study Guide - Quiz Guide: Pie Chart, Matlab

1 Page
25 Feb
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YORKWinter

ITEC 2600 Study Guide - Quiz Guide: Binary Search Algorithm

1 Page
25 Feb
Lab exercise 6: redo all examples from the lecture, generate vectors v1, v2, v3 and v4 that contain 100, 1000, 10000, 100000 random integers ranging be
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YORKOMIS 2010Linda LakatsWinter

OMIS 2010 Lecture Notes - Lecture 10: Goat Cheese, Standard Deviation, Statistical Process Control

4 Page
2 May 2017
Omis 2010 assignment b4 winter 2017. Assignment instructions (please read carefully: submit your assignment to the link posted on moodle, make sure to
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YORKOMIS 2010Zhepeng LiFall

OMIS 2010 Lecture Notes - Lecture 9: Feasible Region, Shadow Price

3 Page
25 Mar 2016
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YORKOMIS 2010Linda LakatsWinter

OMIS 2010 Lecture Notes - Microsoft Excel, Contin

14 Page
5 Feb 2013
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YORKOMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 2: Feasible Region, Linear Programming, Audit

3 Page
22 Sep 2017
To complete / lay out the graph: formulate the model, all within excel. Invoke the solver tool: solves the linear program, sensitivity analysis. Inputs
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YORKOMIS 2010Hila CohenFall

OMIS 2010 Lecture Notes - Work Breakdown Structure, Level Set, Feasible Region

1 Page
17 Dec 2012
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OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 12: Control Chart, Statistical Process Control, Six Sigma

4 Page
20 Aug 2016
Six sigma - dmaic approach: define critical outputs and identify gaps for improvement, measure the work and collect process data, analyze the data. 4:
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YORKOMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 1: Feasible Region, Matrix Ring, Minimax

2 Page
11 Sep 2017
Helps determine how to effectively convert inputs into outputs: how to economize the resources that we are provided. Linear programming: has many restr
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YORKOMIS 2010Hila CohenSummer

OMIS 2010 Lecture Notes - Feasible Region, Level Set, Work Breakdown Structure

1 Page
17 Dec 2012
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YORKOMIS 2010Joan JudgeWinter

Medterm GREAT!

3 Page
16 Oct 2011
Countries were in a race to become the most powerful strongest richest country in the world. How was this done? (slavery, natural resources and reconst
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OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 11: Service Level, Standard Deviation, Stockout

6 Page
20 Aug 2016
Four categories of inventory costs: ordering or setup costs - result of the work involved in placing purchase orders with suppliers or configuring tool
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YORKOMIS 2010Alan MarshallWinter

OMIS 2010 Chapter Notes -Frequency Distribution

2 Page
18 Mar 2014
The derivation of sturges" rule is not terribly complex, but not suitable for an introductory statistics course. 2 one statement of the rule is to choo
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YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes -Descriptive Statistics, Level Of Measurement, Frequency Distribution

7 Page
10 Aug 2014
Descriptive statistics: deals with methods of organizing, summarizing and presenting data in convenient and informative way (ie. graphing techniques) U
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YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes - Chapter 15: Null Hypothesis, Standard Deviation, Contingency Table

3 Page
10 Aug 2014
Applied to multinomial experiment; generalization of a binomial experiment. In multinomial experiment: there are two or more possible outcomes per tria
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YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes - Chapter 14: Dependent And Independent Variables, Royal Institute Of Technology, Ssab

7 Page
10 Aug 2014
This chapter helps compare two or more populations of interval data. Determines whether differences exist between populations means. Anova tests to det
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YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes -Sampling Distribution, Standard Error, Central Limit Theorem

3 Page
10 Aug 2014
Is created by sampling draw sample of same size from a population or use rules of probability and laws of expected value and variance to derive samplin
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YORKOMIS 2010Alan MarshallWinter

OMIS 2010 Chapter Notes - Chapter 1-4: Univariate, Skewness, Unimodality

5 Page
18 Mar 2014
Make a table that lists each person, his number or letter: count the number of times that each combination occurs, see if there is a relationship conve
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YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes - Chapter 1: Pie Chart, Bar Chart, Level Of Measurement

24 Page
23 Nov 2012
Deals with methods of organizing, summarizing, and presenting data in a convenient and graphical techniques for easy extraction of useful information (
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YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes - Chapter 06: Ford Tempo, Mutual Exclusivity, Probability Distribution

22 Page
6 Oct 2011
This chapter introduced the basic concepts of probability. It outlined rules and techniques for assigning probabilities to events. How to recognize whe
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YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes - Chapter 10&11: Probability Distribution, Interval Estimation, Consistent Estimator

4 Page
10 Aug 2014
Can make inferences about populations through estimations and hypothesis testing. Estimation: determine approx. value of population parameter on basis
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YORKOMIS 2010Alan MarshallWinter

Notes of Chapters 5-.docx

3 Page
18 Mar 2014
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YORKOMIS 2010Linda LakatsWinter

OMIS 2010- Midterm Exam Guide - Comprehensive Notes for the exam ( 25 pages long!)

25 Page
11 Oct 2017
Omis 2010 assignment b1 winter 2017. Groups can not consist of students from other sections of the course: only one person uploads the assignment, addi
View Document
YORKOMIS 2010AlexanderWinter

OMIS 2010 Study Guide - Final Guide: Mean Absolute Difference, Block Design, Load Management

16 Page
23 Oct 2013
Calculator; formula and tables book: please place your i. d. card on your desk. Instructions: you are not allowed to leave the examination room until o
View Document
YORKOMIS 2010Linda LakatsWinter

OMIS 2010 Lecture Notes - Lecture 10: Goat Cheese, Standard Deviation, Statistical Process Control

4 Page
2 May 2017
Omis 2010 assignment b4 winter 2017. Assignment instructions (please read carefully: submit your assignment to the link posted on moodle, make sure to
View Document
YORKOMIS 2010AlexanderWinter

Practice Final Exam.doc

15 Page
23 Oct 2013
Calculator; formula and tables book: please place your i. d. card on your desk. Instructions: you are not allowed to leave the examination room until o
View Document
YORKOMIS 2010Henry KimFall

OMIS 2010 Study Guide - Final Guide: Digital Millennium Copyright Act, Chief Privacy Officer, Google Account

19 Page
15 Apr 2014
View Document
YORKOMIS 2010Alan MarshallWinter

OMIS 2010 Chapter Notes -Frequency Distribution

2 Page
18 Mar 2014
The derivation of sturges" rule is not terribly complex, but not suitable for an introductory statistics course. 2 one statement of the rule is to choo
View Document
YORKOMIS 2010Zhepeng LiFall

OMIS 2010 Lecture Notes - Lecture 9: Feasible Region, Shadow Price

3 Page
25 Mar 2016
View Document
YORKOMIS 2010Linda LakatsWinter

OMIS 2010 Lecture Notes - Microsoft Excel, Contin

14 Page
5 Feb 2013
View Document
YORKOMIS 2010Alan MarshallFall

OMIS 2010 Chapter Notes -Descriptive Statistics, Level Of Measurement, Frequency Distribution

7 Page
10 Aug 2014
Descriptive statistics: deals with methods of organizing, summarizing and presenting data in convenient and informative way (ie. graphing techniques) U
View Document
YORKOMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 2: Feasible Region, Linear Programming, Audit

3 Page
22 Sep 2017
To complete / lay out the graph: formulate the model, all within excel. Invoke the solver tool: solves the linear program, sensitivity analysis. Inputs
View Document

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YORKOMIS 2010Linda LakatsWinter

OMIS 2010- Midterm Exam Guide - Comprehensive Notes for the exam ( 25 pages long!)

25 Page
11 Oct 2017
Omis 2010 assignment b1 winter 2017. Groups can not consist of students from other sections of the course: only one person uploads the assignment, addi
View Document
YORKOMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 2: Feasible Region, Linear Programming, Audit

3 Page
22 Sep 2017
To complete / lay out the graph: formulate the model, all within excel. Invoke the solver tool: solves the linear program, sensitivity analysis. Inputs
View Document
YORKOMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 1: Feasible Region, Matrix Ring, Minimax

2 Page
11 Sep 2017
Helps determine how to effectively convert inputs into outputs: how to economize the resources that we are provided. Linear programming: has many restr
View Document
YORKOMIS 2010Linda LakatsWinter

OMIS 2010 Lecture Notes - Lecture 10: Goat Cheese, Standard Deviation, Statistical Process Control

4 Page
2 May 2017
Omis 2010 assignment b4 winter 2017. Assignment instructions (please read carefully: submit your assignment to the link posted on moodle, make sure to
View Document
OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 12: Control Chart, Statistical Process Control, Six Sigma

4 Page
20 Aug 2016
Six sigma - dmaic approach: define critical outputs and identify gaps for improvement, measure the work and collect process data, analyze the data. 4:
View Document
OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 13: Collectively Exhaustive Events, Weighted Arithmetic Mean, Emv

3 Page
20 Aug 2016
A good decision is one that: uses analytic decision making. Is based on logic and considers all available data and possible alternatives. Alternative a
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OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 5: Cubic Foot, Shadow Price, Dialog Box

7 Page
20 Aug 2016
Part 1: organize your information for solving an optimization problem in excel: an objective function, decision variables, and. It is simplest to organ
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OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 11: Service Level, Standard Deviation, Stockout

6 Page
20 Aug 2016
Four categories of inventory costs: ordering or setup costs - result of the work involved in placing purchase orders with suppliers or configuring tool
View Document
OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 10: Eastern Orthodox Liturgical Calendar, Standard Deviation, Airline Ticket

6 Page
20 Aug 2016
Waiting line systems: arrivals/inputs, population size, behavior of arrivals, statistical distribution of arrivals, queue (actual waiting line, limited
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OMIS 2010Linda LakatsFall

OMIS 2010 Lecture Notes - Lecture 5: Dependent And Independent Variables, Time Series, Exponential Smoothing

5 Page
20 Aug 2016
A time-series is a set of observations on a quantitative variable collected over time. In time series analysis, we analyze the past behavior of a varia
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