Feedback. The Lost Art Of Agile. (v2)

Size: px
Start display at page:

Download "Feedback. The Lost Art Of Agile. (v2)"

Transcription

1 Feedback The Lost Art Of Agile (v2)

2 Software development has a history of loosing feedback

3 Why Lost? - Waterfall The implementation described above is risky and invites failure. Winston Royce, 1970

4 Why Lost? - Unit Testing 1985: book on structured programming talks about unit testing 1989: we sketched out a set of test cases before putting pencil to coding pad These were punched into cards and put in the permanent test case library Gerry Weinberg

5 Why Lost? - Agile early and continuous delivery Deliver working software frequently Business people and developers must work together daily face-to-face conversation

6 Feedback! - Found? Validate any assumption in maximum two weeks

7 Why Art? Not Science. Some science might be involved: Statistics, Psychology, Systems Theory.

8 Why feedback? The Thesis. Software development is on a quest for high quality, fast feedback

9 Why feedback?

10 Why? To validate decisions To improve processes To improve team work

11 Feedback is useful for... People Process

12 What? A process in which information about the past or the present influences the same phenomenon in the present or future Wikipedia

13 Feedback in Engineering Information by itself is not feedback unless translated into action Wikipedia

14 Feedback in Scrum

15 Feedback on Code

16 Personal Feedback - BAD You always make the same mistake Your code sucks John broke the build again

17 Personal Feedback - TOOL State the facts Future oriented Objective

18 Tool: Personal Feedback - GOOD I noticed that in the past week you were late 510' to the daily Scrum. 5 of your team mates had to wait for you to arrive. What can we do to avoid this in the future?

19 Management Feedback - BAD Yearly review 3 months ago your colleagues complained that...

20 Management Feedback - TOOL One To One (121) meeting every two weeks 360 evaluation every 3 months

21 Product feedback - BAD Build it and they will come I'm sure our users are happy but we have no data to show All the features are useful because I say so We will validate this feature in 6 months, after we make the release

22 Product feedback - Tools Lean UX use prototypes to validate features Measure usage, satisfaction Usability tests Feedback built in the product Release early, release often

23 Code Feedback - BAD [Test] public void FiveDimensionedArrays(){ int[,,,,] expected = new int[2, 2, 2, 2, 2] { { { { { 1, 2 }, { 3, 4 } }, { { 5, 6 }, { 7, 8 } } }, { { { 1, 2 }, { 3, 4 } }, { { 5, 6 }, { 7, 8 } } } }, { { { { 1, 2 }, { 3, 4 } }, { { 5, 6 }, { 7, 8 } } }, { { { 1, 2 }, { 3, 4 } }, { { 5, 6 }, { 7, 8 } } } } }; int[,,,,] actual = new int[2, 2, 2, 2, 2] { { { { { 1, 2 }, { 4, 3 } }, { { 5, 6 }, { 7, 8 } } }, { { { 1, 2 }, { 3, 4 } }, { { 5, 6 }, { 7, 8 } } } }, { { { { 1, 2 }, { 3, 4 } }, { { 5, 6 }, { 7, 8 } } }, { { { 1, 2 }, { 3, 4 } }, { { 5, 6 }, { 7, 8 } } } } }; var expectedmessage = " Expected and actual are both <System.Int32[2,2,2,2,2]>" + NL + " Values differ at index [0,0,0,1,0]" + NL + TextMessageWriter.Pfx_Expected + "3" + NL + TextMessageWriter.Pfx_Actual + "4" + NL; var ex = Assert.Throws<AssertionException>(() => Assert.That(actual, Is.EqualTo(expected))); Assert.That(ex.Message, Is.EqualTo(expectedMessage)); }

24 Code Feedback - GOOD [Test] public void AllItemsAreInRange(){ int[] c = new int[] { 12, 27, 19, 32, 45, 99, 26 }; Assert.That(c, new AllItemsConstraint(new RangeConstraint(10, 100))); }

25 Feedback Quiz!

26 Quiz #1 A team mate introduces bugs in the application every sprint. You: A)Don't care B)Tell him he should stop programming C)Review his code and tell him the problems D)Ask him how you can help to avoid it E)Pair with him, identify why he does that and help him

27 Quiz #2 The project you work on has automated tests. A)You don't run them, it's integration department's business B)50 tests fail from time to time C)When making a change, 20 tests fail D)At most two tests fail in case of a mistake E)All tests run nightly F)Fast tests are separate and run after each code change

28 Quiz #3 A team mate talks at every daily Scrum for 10' and delays the meeting. You are the Scrum Master. You: A)Think at something different while he speaks B)Find ways to leave earlier C)Tell him to stop talking because he's annoying D)Talk to him in private and tell him he should stop E)Do a retrospective at the end of the meeting

29 Quiz #4 You find a piece of complicated code at the end of the sprint, while modifying in other parts of the application. You: A)Ignore it, maybe you won't have to change it B)Write the issue down and forget about it C)Discuss it in the team and add it to the backlog D)Take 15' to refactor it and then move on

30 Quiz #5 You manage a few Scrum teams and have to evaluate the people. You: A)Don't evaluate them, whoever asks for a raise might get it B)Do a yearly evaluation according to company policies C)Go at the team meetings to evaluate the people D)Do a 360º evaluation every 2 months E)Have weekly one-on-one meetings, monthly 360º and attend meetings from time to time

31 Feedback is AWEsome and AWEful

32 Main Ideas Software development is on a quest for more, higher quality feedback It is feedback only if you do something about it Tools: Introduce feedback cycle, Get more feedback, Get higher quality feedback

33 Questions

Abstract Machine for Software Process Models

Abstract Machine for Software Process Models Abstract Machine for Software Process Models Finite State Machine for SPM Waterfall Incremental Spiral Extreme Programming (XP) Scrum Generalized Abstract Machine for SPM Problem set: objectives with colors

More information

R E A D : E S S E N T I A L S C R U M : A P R A C T I C A L G U I D E T O T H E M O S T P O P U L A R A G I L E P R O C E S S. C H.

R E A D : E S S E N T I A L S C R U M : A P R A C T I C A L G U I D E T O T H E M O S T P O P U L A R A G I L E P R O C E S S. C H. R E A D : E S S E N T I A L S C R U M : A P R A C T I C A L G U I D E T O T H E M O S T P O P U L A R A G I L E P R O C E S S. C H. 5 S O F T W A R E E N G I N E E R I N G B Y S O M M E R V I L L E S E

More information

There Is Therefore Now No Condemnation Romans 8:1-12

There Is Therefore Now No Condemnation Romans 8:1-12 Lesson 314 There Is Therefore Now No Condemnation Romans 8:1-12 MEMORY VERSE ROMAN S 8:1 There is therefore now no c ondem nation to those w ho are in Christ Jesus, who do not walk according to the flesh,

More information

Calculator Exam 2009 University of Houston Math Contest. Name: School: There is no penalty for guessing.

Calculator Exam 2009 University of Houston Math Contest. Name: School: There is no penalty for guessing. Calculator Exam 2009 University of Houston Math Contest Name: School: Please read the questions carefully. Unless otherwise requested, round your answers to 8 decimal places. There is no penalty for guessing.

More information

Classification: Analyzing Sentiment

Classification: Analyzing Sentiment Classification: Analyzing Sentiment STAT/CSE 416: Machine Learning Emily Fox University of Washington April 17, 2018 Predicting sentiment by topic: An intelligent restaurant review system 1 It s a big

More information

Class 7 Preclass Quiz on MasteringPhysics

Class 7 Preclass Quiz on MasteringPhysics PHY131H1F Class 7 Today: Uncertainty Analysis Normal Distribution Standard Deviation Reading uncertainty Propagation of uncertainties Uncertainty in the Mean From The Lahman Baseball Database V.5.8 http://seanlahman.com/files/database/readme58.txt

More information

Math 5a Reading Assignments for Sections

Math 5a Reading Assignments for Sections Math 5a Reading Assignments for Sections 4.1 4.5 Due Dates for Reading Assignments Note: There will be a very short online reading quiz (WebWork) on each reading assignment due one hour before class on

More information

Complex Matrix Transformations

Complex Matrix Transformations Gama Network Presents: Complex Matrix Transformations By By Scott Johnson Gamasutra May 17, 2002 URL: http://www.gamasutra.com/features/20020510/johnson_01.htm Matrix transforms are a ubiquitous aspect

More information

THE SIMPLE PROOF OF GOLDBACH'S CONJECTURE. by Miles Mathis

THE SIMPLE PROOF OF GOLDBACH'S CONJECTURE. by Miles Mathis THE SIMPLE PROOF OF GOLDBACH'S CONJECTURE by Miles Mathis miles@mileswmathis.com Abstract Here I solve Goldbach's Conjecture by the simplest method possible. I do this by first calculating probabilites

More information

Degree (k)

Degree (k) 0 1 Pr(X k) 0 0 1 Degree (k) Figure A1: Log-log plot of the complementary cumulative distribution function (CCDF) of the degree distribution for a sample month (January 0) network is shown (blue), along

More information

June If you want, you may scan your assignment and convert it to a.pdf file and it to me.

June If you want, you may scan your assignment and convert it to a.pdf file and  it to me. Summer Assignment Pre-Calculus Honors June 2016 Dear Student: This assignment is a mandatory part of the Pre-Calculus Honors course. Students who do not complete the assignment will be placed in the regular

More information

3. If a forecast is too high when compared to an actual outcome, will that forecast error be positive or negative?

3. If a forecast is too high when compared to an actual outcome, will that forecast error be positive or negative? 1. Does a moving average forecast become more or less responsive to changes in a data series when more data points are included in the average? 2. Does an exponential smoothing forecast become more or

More information

MBF3C S3L1 Sine Law and Cosine Law Review May 08, 2018

MBF3C S3L1 Sine Law and Cosine Law Review May 08, 2018 MBF3C S3L1 Sine Law and Cosine Law Review May 08, 2018 Topic : Review of previous spiral I remember how to apply the formulas for Sine Law and Cosine Law Review of Sine Law and Cosine Law Remember when

More information

1. If X has density. cx 3 e x ), 0 x < 0, otherwise. Find the value of c that makes f a probability density. f(x) =

1. If X has density. cx 3 e x ), 0 x < 0, otherwise. Find the value of c that makes f a probability density. f(x) = 1. If X has density f(x) = { cx 3 e x ), 0 x < 0, otherwise. Find the value of c that makes f a probability density. 2. Let X have density f(x) = { xe x, 0 < x < 0, otherwise. (a) Find P (X > 2). (b) Find

More information

18.05 Exam 1. Table of normal probabilities: The last page of the exam contains a table of standard normal cdf values.

18.05 Exam 1. Table of normal probabilities: The last page of the exam contains a table of standard normal cdf values. Name 18.05 Exam 1 No books or calculators. You may have one 4 6 notecard with any information you like on it. 6 problems, 8 pages Use the back side of each page if you need more space. Simplifying expressions:

More information

PSY 305. Module 3. Page Title. Introduction to Hypothesis Testing Z-tests. Five steps in hypothesis testing

PSY 305. Module 3. Page Title. Introduction to Hypothesis Testing Z-tests. Five steps in hypothesis testing Page Title PSY 305 Module 3 Introduction to Hypothesis Testing Z-tests Five steps in hypothesis testing State the research and null hypothesis Determine characteristics of comparison distribution Five

More information

W E P RO V I D E W E B & M O B I L E S O LU T I O N S. COMPETENTLY.

W E P RO V I D E W E B & M O B I L E S O LU T I O N S. COMPETENTLY. W E P RO V I D E W E B & M O B I L E S O LU T I O N S. COMPETENTLY. M O B I L E D E V E L O P M E N T - W E B D E V E L O P M E N T - D E S I G N - T E A M A U G M E N T A T I O N WHY U S? B E C A U S

More information

Workshop 1a: Software Measurement. Dietmar Pfahl

Workshop 1a: Software Measurement. Dietmar Pfahl Software Economics Fall 2015 Workshop 1a: Software Measurement Dietmar Pfahl (based on slides by Marlon Dumas & Anton Litvinenko) Main Message Software measures can be misleading, so Either you don t use

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science 6.262 Discrete Stochastic Processes Midterm Quiz April 6, 2010 There are 5 questions, each with several parts.

More information

Classification: Analyzing Sentiment

Classification: Analyzing Sentiment Classification: Analyzing Sentiment STAT/CSE 416: Machine Learning Emily Fox University of Washington April 17, 2018 Predicting sentiment by topic: An intelligent restaurant review system 1 4/16/18 It

More information

But You Knew That Already: What A Psychic Can Teach You About Life By Dougall Fraser READ ONLINE

But You Knew That Already: What A Psychic Can Teach You About Life By Dougall Fraser READ ONLINE But You Knew That Already: What A Psychic Can Teach You About Life By Dougall Fraser READ ONLINE If you are searched for the ebook by Dougall Fraser But You Knew That Already: What a Psychic Can Teach

More information

OXFORD CAMBRIDGE AND RSA EXAMINATIONS A2 GCE 4733/01. MATHEMATICS Probability & Statistics 2 QUESTION PAPER

OXFORD CAMBRIDGE AND RSA EXAMINATIONS A2 GCE 4733/01. MATHEMATICS Probability & Statistics 2 QUESTION PAPER OXFORD CAMBRIDGE AND RSA EXAMINATIONS A2 GCE 4733/01 MATHEMATICS Probability & Statistics 2 QUESTION PAPER TUESDAY 10 JUNE 2014: Morning DURATION: 1 hour 30 minutes plus your additional time allowance

More information

CH 16 LIKE TERMS AND EQUATIONS. Ch 16 Like Terms and Equations = 10 10

CH 16 LIKE TERMS AND EQUATIONS. Ch 16 Like Terms and Equations = 10 10 143 CH 16 LIKE TERMS AND EQUATIONS Introduction As promised in the previous chapter, we now have the tool -- combining like terms -- that we need to solve equations like x 2x 9 12x + 1. This chapter will

More information

Predicting Long-Term Telemetry Behavior for Lunar Orbiting, Deep Space, Planetary and Earth Orbiting Satellites

Predicting Long-Term Telemetry Behavior for Lunar Orbiting, Deep Space, Planetary and Earth Orbiting Satellites Predicting Long-Term Telemetry Behavior for Lunar Orbiting, Deep Space, Planetary and Earth Orbiting Satellites Item Type text; Proceedings Authors Losik, Len Publisher International Foundation for Telemetering

More information

CIVL Continuous Distributions

CIVL Continuous Distributions CIVL 3103 Continuous Distributions Learning Objectives - Continuous Distributions Define continuous distributions, and identify common distributions applicable to engineering problems. Identify the appropriate

More information

Section 2.3 Objectives

Section 2.3 Objectives Section 2.3 Objectives Use the inequality symbols to compare two numbers. Determine if a given value is a solution of an inequality. Solve simple inequalities. Graph the solutions to inequalities on the

More information

LETTER TO PARENTS SCIENCE NEWS. Dear Parents,

LETTER TO PARENTS SCIENCE NEWS. Dear Parents, LETTER TO PARENTS Cut here and paste onto school letterhead before making copies. Dear Parents, SCIENCE NEWS Our class is beginning a new science unit using the FOSS Earth Materials Module. We will investigate

More information

Lesson 32. The Grain of Wheat. John 12:20-26

Lesson 32. The Grain of Wheat. John 12:20-26 L i f e o f C h r i s t from the gospel of J o h n Lesson 32 The Grain of Wheat John 12:20-26 Mission Arlington Mission Metroplex Curriculum 2010 Created for use with young, unchurched learners Adaptable

More information

Statics - TAM 210 & TAM 211. Spring 2018

Statics - TAM 210 & TAM 211. Spring 2018 Statics - TAM 210 & TAM 211 Spring 2018 Course distribution Required TAM 210 TAM 211 Aerospace Engineering 31 1 Agricultural & Biological 12 3 Bioengineering 2 6 Civil Engineering 41 Engineering Mechanics

More information

hypotheses. P-value Test for a 2 Sample z-test (Large Independent Samples) n > 30 P-value Test for a 2 Sample t-test (Small Samples) n < 30 Identify α

hypotheses. P-value Test for a 2 Sample z-test (Large Independent Samples) n > 30 P-value Test for a 2 Sample t-test (Small Samples) n < 30 Identify α Chapter 8 Notes Section 8-1 Independent and Dependent Samples Independent samples have no relation to each other. An example would be comparing the costs of vacationing in Florida to the cost of vacationing

More information

Explorers 3 Teacher s notes for the Comprehension Test: The Magic Flute

Explorers 3 Teacher s notes for the Comprehension Test: The Magic Flute Explorers 3 Teacher s notes for the Comprehension Test: The Magic Flute Do this test after you have read the whole book with the class. Ask the children to fill in their name and the date at the top of

More information

CS 160: Lecture 16. Quantitative Studies. Outline. Random variables and trials. Random variables. Qualitative vs. Quantitative Studies

CS 160: Lecture 16. Quantitative Studies. Outline. Random variables and trials. Random variables. Qualitative vs. Quantitative Studies Qualitative vs. Quantitative Studies CS 160: Lecture 16 Professor John Canny Qualitative: What we ve been doing so far: * Contextual Inquiry: trying to understand user s tasks and their conceptual model.

More information

MTAT Software Engineering

MTAT Software Engineering MTAT.03.094 Software Engineering Lecture 14: Measurement Dietmar Pfahl Fall 2015 email: dietmar.pfahl@ut.ee Schedule of Lectures Week 01: Introduction to SE Week 02: Requirements Engineering I Week 03:

More information

Old Testament. Part Two. Created for use with young, unchurched learners Adaptable for all ages including adults

Old Testament. Part Two. Created for use with young, unchurched learners Adaptable for all ages including adults Old Testament Part Two Created for use with young, unchurched learners Adaptable for all ages including adults Mission Arlington Mission Metroplex Curriculum Lesson 66 Page 1 M ISSION ARLINGTON MISSION

More information

But, there is always a certain amount of mystery that hangs around it. People scratch their heads and can't figure

But, there is always a certain amount of mystery that hangs around it. People scratch their heads and can't figure MITOCW 18-03_L19 Today, and for the next two weeks, we are going to be studying what, for many engineers and a few scientists is the most popular method of solving any differential equation of the kind

More information

Physics Motion Math. (Read objectives on screen.)

Physics Motion Math. (Read objectives on screen.) Physics 302 - Motion Math (Read objectives on screen.) Welcome back. When we ended the last program, your teacher gave you some motion graphs to interpret. For each section, you were to describe the motion

More information

GPS :: VSAT :: Earth Observation :: Satellites & Communications :: Unmanned Aerial Vehicles :: Aerospace :: Launchers :: Analysis :: Jobs in Space ::

GPS :: VSAT :: Earth Observation :: Satellites & Communications :: Unmanned Aerial Vehicles :: Aerospace :: Launchers :: Analysis :: Jobs in Space :: T R A D E A D V E R T I S I N G 2 0 0 6 D E M O G R A P H I C S : : I N D U S T R Y P O S I T I O N S : : S P O N S O R S H I P R A T E S Reach out to the engineers of space at SpaceDaily.com. G L O B

More information

Solar Open House Toolkit

Solar Open House Toolkit A Solar Open House is an informal meet and greet at a solar homeowner s home. It is an opportunity for homeowners who are considering going solar to see solar energy at work, ask questions about the process

More information

Extrema and the Extreme Value Theorem

Extrema and the Extreme Value Theorem Extrema and the Extreme Value Theorem Local and Absolute Extrema. Extrema are the points where we will find a maximum or minimum on the curve. If they are local or relative extrema, then they will be the

More information

GIS for the Beginner on a Budget

GIS for the Beginner on a Budget GIS for the Beginner on a Budget Andre C. Bally, RLA, GIS Coordinator, Harris County Public Infrastructure Department Engineering Division This presentation, GIS for Beginners on a Budget. will briefly

More information

Introduction to Algebra: The First Week

Introduction to Algebra: The First Week Introduction to Algebra: The First Week Background: According to the thermostat on the wall, the temperature in the classroom right now is 72 degrees Fahrenheit. I want to write to my friend in Europe,

More information

MITOCW ocw lec8

MITOCW ocw lec8 MITOCW ocw-5.112-lec8 The following content is provided by MIT OpenCourseWare under a Creative Commons license. Additional information about our license and MIT OpenCourseWare in general is available at

More information

Section 3.3: Discrete-Event Simulation Examples

Section 3.3: Discrete-Event Simulation Examples Section 33: Discrete-Event Simulation Examples Discrete-Event Simulation: A First Course c 2006 Pearson Ed, Inc 0-13-142917-5 Discrete-Event Simulation: A First Course Section 33: Discrete-Event Simulation

More information

Words to avoid in proposals

Words to avoid in proposals Crutch words used when writers don t understand what to say We understand Leverage our experience Thank you for the opportunity We look forward to state-of-the-art the right choice Never use the word understand

More information

Good Hours. We all have our good hours. Whether it be in the early morning on a hot summer

Good Hours. We all have our good hours. Whether it be in the early morning on a hot summer Jennifer Kuiken Kim Groninga Poetry Explication 11/20/06 Good Hours We all have our good hours. Whether it be in the early morning on a hot summer day or in the evening on a cold winter night, we seem

More information

Quality Assurance Questionnaire Spring 2014 The Haven

Quality Assurance Questionnaire Spring 2014 The Haven 1 , Next of Kin & Care Manager s Satisfaction Survey Spring 2014 Introduction Providing quality care and service is our aim at all times, as part of our quality assurance procedure we have developed a

More information

Relationships Between Quantities

Relationships Between Quantities Algebra 1 Relationships Between Quantities Relationships Between Quantities Everyone loves math until there are letters (known as variables) in problems!! Do students complain about reading when they come

More information

Objective: Recognize halves within a circular clock face and tell time to the half hour.

Objective: Recognize halves within a circular clock face and tell time to the half hour. Lesson 13 1 5 Lesson 13 Objective: Recognize halves within a circular clock face and tell time to the half Suggested Lesson Structure Fluency Practice Application Problem Concept Development Student Debrief

More information

E23: Hotel Management System Wen Yunlu Hu Xing Chen Ke Tang Haoyuan Module: EEE 101

E23: Hotel Management System Wen Yunlu Hu Xing Chen Ke Tang Haoyuan Module: EEE 101 E23: Hotel Management System Author: 1302509 Zhao Ruimin 1301478 Wen Yunlu 1302575 Hu Xing 1301911 Chen Ke 1302599 Tang Haoyuan Module: EEE 101 Lecturer: Date: Dr.Lin December/22/2014 Contents Contents

More information

Chapter 2: Linear Functions

Chapter 2: Linear Functions Chapter 2: Linear Functions Chapter one was a window that gave us a peek into the entire course. Our goal was to understand the basic structure of functions and function notation, the toolkit functions,

More information

11 CHI-SQUARED Introduction. Objectives. How random are your numbers? After studying this chapter you should

11 CHI-SQUARED Introduction. Objectives. How random are your numbers? After studying this chapter you should 11 CHI-SQUARED Chapter 11 Chi-squared Objectives After studying this chapter you should be able to use the χ 2 distribution to test if a set of observations fits an appropriate model; know how to calculate

More information

Deadlock (2) Dave Eckhardt Brian Railing Roger Dannenberg

Deadlock (2) Dave Eckhardt Brian Railing Roger Dannenberg Deadlock () Dave Eckhardt Brian Railing Roger Dannenberg 1 1-410, S'18 Synchronization P You should really have, today: Drawn pictures of thread stacks (even if not perfect) Figured out where stubs belong,

More information

1. (+5) x ( 6) = 2. ( 6) x ( 7) = 3. ( 9) x ( 10) = 4. ( 10) x (+12) = 5. ( 5) x ( 8) = 6. ( 16) x ( 11) = 7. (+4) x ( 15) = 8.

1. (+5) x ( 6) = 2. ( 6) x ( 7) = 3. ( 9) x ( 10) = 4. ( 10) x (+12) = 5. ( 5) x ( 8) = 6. ( 16) x ( 11) = 7. (+4) x ( 15) = 8. LESSON PRACTICE Multiply. A. (+5) x ( 6) =. ( 6) x ( ) =. ( 9) x ( 0) =. ( 0) x (+) = 5. ( 5) x ( 8) = 6. ( 6) x ( ) =. (+) x ( 5) = 8. ( 8) x ( 6) = 9. ( 6) x (+) = 0. ( ) x (+) =. ( 8) x ( ) =. ( ) x

More information

Economics 390 Economic Forecasting

Economics 390 Economic Forecasting Economics 390 Economic Forecasting Prerequisite: Econ 410 or equivalent Course information is on website Office Hours Tuesdays & Thursdays 2:30 3:30 or by appointment Textbooks Forecasting for Economics

More information

MITOCW Investigation 4, Part 3

MITOCW Investigation 4, Part 3 MITOCW Investigation 4, Part 3 The following content is provided under a Creative Commons license. Your support will help MIT OpenCourseWare continue to offer high quality educational resources for free.

More information

Twin paradox and Einstein mistake

Twin paradox and Einstein mistake Twin paradox and Einstein mistake a mathematical approach Based on the book: Logic in the Universe Victor Orsini The Michelson-Morley experiment showed inadvertently that the speed of light is constant.

More information

The Early Church Acts 2:42-47; 4:32-37

The Early Church Acts 2:42-47; 4:32-37 Lesson 286 The Early Church Acts 2:42-47; 4:32-37 MEMORY VERSE ACTS 2:42 And they continued steadfastly in the apostles' doctrine and fellowship, in the breaking of bread, and in prayers. WHAT YOU WILL

More information

Mathematical Logic Part Three

Mathematical Logic Part Three Mathematical Logic Part Three Recap from Last Time What is First-Order Logic? First-order logic is a logical system for reasoning about properties of objects. Augments the logical connectives from propositional

More information

Mathematical Logic Part Three

Mathematical Logic Part Three Mathematical Logic Part Three Recap from Last Time What is First-Order Logic? First-order logic is a logical system for reasoning about properties of objects. Augments the logical connectives from propositional

More information

Money spell pay after results whatsapp

Money spell pay after results whatsapp Money spell pay after results whatsapp EFFECTIVE RESULTS http://powerfulspellscaster.com/ Call or WhatsApp:Tel spell for getting your ex back,spell to make more money real fast, ways to get.. Make your

More information

P vs. NP. Data Structures and Algorithms CSE AU 1

P vs. NP. Data Structures and Algorithms CSE AU 1 P vs. NP Data Structures and Algorithms CSE 373-18AU 1 Goals for today Define P, NP, and NP-complete Explain the P vs. NP problem -why it s the biggest open problem in CS. -And what to do when a problem

More information

Physics 2020 Laboratory Manual

Physics 2020 Laboratory Manual Physics 00 Laboratory Manual Department of Physics University of Colorado at Boulder Spring, 000 This manual is available for FREE online at: http://www.colorado.edu/physics/phys00/ This manual supercedes

More information

The First Derivative Test

The First Derivative Test The First Derivative Test We have already looked at this test in the last section even though we did not put a name to the process we were using. We use a y number line to test the sign of the first derivative

More information

Math 1 Variable Manipulation Part 4 Word Problems

Math 1 Variable Manipulation Part 4 Word Problems Math 1 Variable Manipulation Part 4 Word Problems 1 TRANSLATING FROM ENGLISH INTO ALGEBRA (PLUG IN) The next part of variable manipulation problems is to figure out the problem from real life situations.

More information

ECO 199 GAMES OF STRATEGY Spring Term 2004 Precepts Week 7 March Questions GAMES WITH ASYMMETRIC INFORMATION QUESTIONS

ECO 199 GAMES OF STRATEGY Spring Term 2004 Precepts Week 7 March Questions GAMES WITH ASYMMETRIC INFORMATION QUESTIONS ECO 199 GAMES OF STRATEGY Spring Term 2004 Precepts Week 7 March 22-23 Questions GAMES WITH ASYMMETRIC INFORMATION QUESTIONS Question 1: In the final stages of the printing of Games of Strategy, Sue Skeath

More information

(Refer Slide Time: 00:10)

(Refer Slide Time: 00:10) Chemical Reaction Engineering 1 (Homogeneous Reactors) Professor R. Krishnaiah Department of Chemical Engineering Indian Institute of Technology Madras Lecture No 10 Design of Batch Reactors Part 1 (Refer

More information

Grade 4 supplement. Set D8 Measurement: Temperature. Includes. Skills & Concepts

Grade 4 supplement. Set D8 Measurement: Temperature. Includes. Skills & Concepts Grade 4 supplement Set D8 Measurement: Temperature Includes Activity 1: What s the Temperature? D8.1 Activity 2: How Does the Temperature Change During the Day? D8.5 Activity 3: Forecast & Actual Temperatures

More information

MITOCW MIT6_041F11_lec15_300k.mp4

MITOCW MIT6_041F11_lec15_300k.mp4 MITOCW MIT6_041F11_lec15_300k.mp4 The following content is provided under a Creative Commons license. Your support will help MIT OpenCourseWare continue to offer high quality educational resources for

More information

Chapter Three. Deciphering the Code. Understanding Notation

Chapter Three. Deciphering the Code. Understanding Notation Chapter Three Deciphering the Code Mathematics has its own vocabulary. In addition to words, mathematics uses its own notation, symbols that stand for more complicated ideas. Some of these elements are

More information

Mathematical Practices

Mathematical Practices Mathematical Practices 8.MP.1. Make sense of problems and persevere in solving them. 8.MP.2. Reason abstractly and quantitatively. 8.MP.5. Use appropriate tools strategically. 8.MP.6. Attend to precision.

More information

Mathematical Logic Part Three

Mathematical Logic Part Three Mathematical Logic Part Three Recap from Last Time What is First-Order Logic? First-order logic is a logical system for reasoning about properties of objects. Augments the logical connectives from propositional

More information

Name: Class: Date: ID: A. Find the mean, median, and mode of the data set. Round to the nearest tenth. c. mean = 9.7, median = 8, mode =15

Name: Class: Date: ID: A. Find the mean, median, and mode of the data set. Round to the nearest tenth. c. mean = 9.7, median = 8, mode =15 Class: Date: Unit 2 Pretest Find the mean, median, and mode of the data set. Round to the nearest tenth. 1. 2, 10, 6, 9, 1, 15, 11, 10, 15, 13, 15 a. mean = 9.7, median = 10, mode = 15 b. mean = 8.9, median

More information

3.6.1 Building Functions from Context. Warm Up

3.6.1 Building Functions from Context. Warm Up Name: # Honors Coordinate Algebra: Period Ms. Pierre Date: 3.6.1 Building Functions from Context Warm Up 1. Willem buys 4 mangoes each week, and mango prices vary from week to week. Write an equation that

More information

- a value calculated or derived from the data.

- a value calculated or derived from the data. Descriptive statistics: Note: I'm assuming you know some basics. If you don't, please read chapter 1 on your own. It's pretty easy material, and it gives you a good background as to why we need statistics.

More information

June Dear Future Algebra 2 Trig Student,

June Dear Future Algebra 2 Trig Student, June 016 Dear Future Algebra Trig Student, Welcome to Algebra /Trig! Since we have so very many topics to cover during our 016-17 school year, it is important that each one of you is able to complete these

More information

4.4 MONTHLY WEATHER SUMMARY

4.4 MONTHLY WEATHER SUMMARY 4.4 1 4.4 MONTHLY WEATHER SUMMARY OBJECTIVES The students Collect and summarize monthly weather data about local weather conditions including wind speed and direction, rainfall, temperature, humidity (optional),

More information

Machine Learning. Module 3-4: Regression and Survival Analysis Day 2, Asst. Prof. Dr. Santitham Prom-on

Machine Learning. Module 3-4: Regression and Survival Analysis Day 2, Asst. Prof. Dr. Santitham Prom-on Machine Learning Module 3-4: Regression and Survival Analysis Day 2, 9.00 16.00 Asst. Prof. Dr. Santitham Prom-on Department of Computer Engineering, Faculty of Engineering King Mongkut s University of

More information

The Indiana Data Sharing Initiative and the IndianaMap. Cross-Boundary Collaboration and Partnerships. State of Indiana

The Indiana Data Sharing Initiative and the IndianaMap. Cross-Boundary Collaboration and Partnerships. State of Indiana The Indiana Data Sharing Initiative and the IndianaMap Cross-Boundary Collaboration and Partnerships State of Indiana Brian Arrowood, CIO James Sparks, GIO EXECUTIVE SUMMARY Under the collaboration oriented

More information

MITOCW MITRES18_005S10_DerivOfSinXCosX_300k_512kb-mp4

MITOCW MITRES18_005S10_DerivOfSinXCosX_300k_512kb-mp4 MITOCW MITRES18_005S10_DerivOfSinXCosX_300k_512kb-mp4 PROFESSOR: OK, this lecture is about the slopes, the derivatives, of two of the great functions of mathematics: sine x and cosine x. Why do I say great

More information

Name: Period: V = lwh

Name: Period: V = lwh Density Unit Packet Name: Period: To begin we are going to start with volume. Volume is the amount of space something takes up. It is measured in units like cubic centimeters or milliliters. Those units

More information

The SAB Medium Term Sales Forecasting System : From Data to Planning Information. Kenneth Carden SAB : Beer Division Planning

The SAB Medium Term Sales Forecasting System : From Data to Planning Information. Kenneth Carden SAB : Beer Division Planning The SAB Medium Term Sales Forecasting System : From Data to Planning Information Kenneth Carden SAB : Beer Division Planning Planning in Beer Division F Operational planning = what, when, where & how F

More information

Forecasting without Fear

Forecasting without Fear Forecasting without Fear How to keep the business informed and keep your cool NY SPIN December 15, 2015 Drivers, Challenges why you have to forecast, and why it s not easy what you forecast Refinement

More information

Astronomy 9 Concepts of the Cosmos

Astronomy 9 Concepts of the Cosmos Astronomy 9 Concepts of the Cosmos Monday/Wednesday, 1:30-2:45 pm, Cabot Auditorium LECTURE 2: I.Our Place in the Universe Lecture on Mon., Feb. 1 st Pre-course Test - REQUIRED! (if you want the attendance

More information

Activity Book Made just for me by the Santa Cruz Consolidated Emergency Communications Center

Activity Book Made just for me by the Santa Cruz Consolidated Emergency Communications Center - - Activity Book Made just for me by the Santa Cruz Consolidated Emergency Communications Center Words In This Book B D F J L M N O W O N K F S W E F A R L F A S K M S V Q R K B I M H N I M M Y Z C I

More information

Mt. Douglas Secondary

Mt. Douglas Secondary Foundations of Math 11 Calculator Usage 207 HOW TO USE TI-83, TI-83 PLUS, TI-84 PLUS CALCULATORS FOR STATISTICS CALCULATIONS shows it is an actual calculator key to press 1. Using LISTS to Calculate Mean,

More information

Math 354 Summer 2004 Solutions to review problems for Midterm #1

Math 354 Summer 2004 Solutions to review problems for Midterm #1 Solutions to review problems for Midterm #1 First: Midterm #1 covers Chapter 1 and 2. In particular, this means that it does not explicitly cover linear algebra. Also, I promise there will not be any proofs.

More information

MITOCW watch?v=7q32wnm4dew

MITOCW watch?v=7q32wnm4dew MITOCW watch?v=7q32wnm4dew BARTON ZWIEBACH: Hydrogen atom is the beginning of our analysis. It still won't solve differential equations, but we will now two particles, a proton, whose coordinates are going

More information

MITOCW ocw-18_02-f07-lec17_220k

MITOCW ocw-18_02-f07-lec17_220k MITOCW ocw-18_02-f07-lec17_220k The following content is provided under a Creative Commons license. Your support will help MIT OpenCourseWare continue to offer high quality educational resources for free.

More information

Section 3.4 Library of Functions; Piecewise-Defined Functions

Section 3.4 Library of Functions; Piecewise-Defined Functions Section. Library of Functions; Piecewise-Defined Functions Objective #: Building the Library of Basic Functions. Graph the following: Ex. f(x) = b; constant function Since there is no variable x in the

More information

Math 301 Final Exam. Dr. Holmes. December 17, 2007

Math 301 Final Exam. Dr. Holmes. December 17, 2007 Math 30 Final Exam Dr. Holmes December 7, 2007 The final exam begins at 0:30 am. It ends officially at 2:30 pm; if everyone in the class agrees to this, it will continue until 2:45 pm. The exam is open

More information

Watching the Weather

Watching the Weather Watching the Weather Topic Observing the weather Key Question What is the weather like today? Focus Students will observe and record weather conditions over a long period of time. Guiding Documents NCTM

More information

43603F. (NOV F01) WMP/Nov12/43603F. General Certificate of Secondary Education Foundation Tier November Unit F

43603F. (NOV F01) WMP/Nov12/43603F. General Certificate of Secondary Education Foundation Tier November Unit F Centre Number Surname Candidate Number For Examiner s Use Other Names Candidate Signature Examiner s Initials General Certificate of Secondary Education Foundation Tier November 2012 Pages 3 4 5 Mark Mathematics

More information

Twin Case Study: Treatment for Articulation Disabilities

Twin Case Study: Treatment for Articulation Disabilities Twin Case Study: Treatment for Articulation Disabilities Sirius Qin and Jun Chen November 5, 010 Department of Statistics University of British Columbia For Angela Feehan M.Sc student Audiology and Speech

More information

If two different people are randomly selected from the 991 subjects, find the probability that they are both women. Round to four decimal places.

If two different people are randomly selected from the 991 subjects, find the probability that they are both women. Round to four decimal places. Math 227 Name 5 pts*20=100pts 1) A bin contains 67 light bulbs of which 8 are defective. If 3 light bulbs are randomly selected from the bin with replacement, find the probability that all the bulbs selected

More information

Numerical and Algebraic Expressions and Equations

Numerical and Algebraic Expressions and Equations Numerical and Algebraic Expressions and Equations Sometimes it's hard to tell how a person is feeling when you're not talking to them face to face. People use emoticons in emails and chat messages to show

More information

Finite Mathematics : A Business Approach

Finite Mathematics : A Business Approach Finite Mathematics : A Business Approach Dr. Brian Travers and Prof. James Lampes Second Edition Cover Art by Stephanie Oxenford Additional Editing by John Gambino Contents What You Should Already Know

More information

Validating Software Evolution of Agile Projects Using Lehman Laws

Validating Software Evolution of Agile Projects Using Lehman Laws Validating Software Evolution of Agile Projects Using Lehman Laws A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF THE DEGREE OF MASTER OF TECHNOLOGY IN COMPUTER SCIENCE

More information

Some Introduction Proto-Nubar Meeting 28/Feb/2006 Caius Howcroft 1

Some Introduction Proto-Nubar Meeting 28/Feb/2006 Caius Howcroft 1 1 At the march meeting I wandered what analysis we might be able to do with the anti-neutrino content of the beam. What I actual was looking for was good thesis topics. Transitions nu->nubar. Beam systematics.

More information

Terminating Employees

Terminating Employees Terminating Employees 1 Agenda Validating the termination Correct coding and paperwork TWC Paperwork TWC Hearing 2 Validating Termination Has employee been coached and counseled Coaching and corrective

More information

MEP Y7 Practice Book B

MEP Y7 Practice Book B 8 Quantitative Data 8. Presentation In this section we look at how vertical line diagrams can be used to display discrete quantitative data. (Remember that discrete data can only take specific numerical

More information