The Foundations of Vital Statistics
|
|
|
- Roy Hardy
- 6 years ago
- Views:
Transcription
1 The Foundations of Vital Statistics Mathematics 15: Lecture 17 Dan Sloughter Furman University October 26, 2006 Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
2 John Graunt Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
3 John Graunt Haberdasher of small-wares (buttons, needles, and such) Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
4 John Graunt Haberdasher of small-wares (buttons, needles, and such) Elected Fellow of the Royal Society in 1662 at the special request of Charles II Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
5 Bills of Mortality Weekly accounts, issued by parish clerks, of all deaths, along with their causes, and Christenings in the parish for the week Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
6 Bills of Mortality Weekly accounts, issued by parish clerks, of all deaths, along with their causes, and Christenings in the parish for the week Graunt is the first to recognize the wealth of information, useful for both the state and for business, contained in these bills. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
7 Bills of Mortality Weekly accounts, issued by parish clerks, of all deaths, along with their causes, and Christenings in the parish for the week Graunt is the first to recognize the wealth of information, useful for both the state and for business, contained in these bills. Graunt (page 1421): Now having (I know not by what accident) engaged my thoughts upon the Bills of Mortality, and so far succeeded therein, as to have reduced several great confused Volumes into a few perspicuous Tables, and abridged such Observations as naturally flowed from them, into a few succinct Paragraphs... Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
8 Statistics Graunt (page 1435): I conclude, That a clear knowledge of all these particulars, and many more, whereat I have shot but at rovers, is necessary in order to good, certain, and easie Government, and even to balance Parties, and factions both in Church and State. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
9 Statistics Graunt (page 1435): I conclude, That a clear knowledge of all these particulars, and many more, whereat I have shot but at rovers, is necessary in order to good, certain, and easie Government, and even to balance Parties, and factions both in Church and State. See reasons on page 1434, and questions which may be answered on page Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
10 Statistics Graunt (page 1435): I conclude, That a clear knowledge of all these particulars, and many more, whereat I have shot but at rovers, is necessary in order to good, certain, and easie Government, and even to balance Parties, and factions both in Church and State. See reasons on page 1434, and questions which may be answered on page These data of the state became known as statistics. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
11 Examples Page 1429: Since few starve, wouldn t it be better for the State to keep them? Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
12 Examples Page 1429: Since few starve, wouldn t it be better for the State to keep them? Page 1430: There are some causes of death about which there be daily talk, but little effect. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
13 Edmond Halley Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
14 Edmond Halley Pushed Newton to complete and publish his Philosophiae naturalis principia mathematica Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
15 Edmond Halley Pushed Newton to complete and publish his Philosophiae naturalis principia mathematica Studied comets, and, in particular, predicted the time of return for the comet we now know as Halley s comet. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
16 Edmond Halley Pushed Newton to complete and publish his Philosophiae naturalis principia mathematica Studied comets, and, in particular, predicted the time of return for the comet we now know as Halley s comet. His tables of mortality rates, based on the birth and death records of Breslaw, provided the first firm data for calculating insurance and annuity rates. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
17 On average Although we cannot predict if a given individual will die during the year, or contract a certain disease, we can predict on average how many people of his or her age will die, or contract that disease. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
18 On average Although we cannot predict if a given individual will die during the year, or contract a certain disease, we can predict on average how many people of his or her age will die, or contract that disease. Similarly, although we cannot predict exactly the yield of a given field, we can say how much a field of this type should produce on average. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
19 Some statistics Given a list of data, the mean is the arithmetic average of the data, that is, the sum of the data divided by the number of data values. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
20 Some statistics Given a list of data, the mean is the arithmetic average of the data, that is, the sum of the data divided by the number of data values. Example: Given the data 5, 6, 13, 14, 3, 3, 3, 4, and 12, the mean is = 63 9 = 7. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
21 Some statistics Given a list of data, the mean is the arithmetic average of the data, that is, the sum of the data divided by the number of data values. Example: Given the data 5, 6, 13, 14, 3, 3, 3, 4, and 12, the mean is = = 7. The median of a list of data is the middle value when the data are listed in ascending order. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
22 Some statistics Given a list of data, the mean is the arithmetic average of the data, that is, the sum of the data divided by the number of data values. Example: Given the data 5, 6, 13, 14, 3, 3, 3, 4, and 12, the mean is = = 7. The median of a list of data is the middle value when the data are listed in ascending order. Note: there is a unique middle value for an odd number of data values, but two middle values for an even number of data values. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
23 Some statistics Given a list of data, the mean is the arithmetic average of the data, that is, the sum of the data divided by the number of data values. Example: Given the data 5, 6, 13, 14, 3, 3, 3, 4, and 12, the mean is = = 7. The median of a list of data is the middle value when the data are listed in ascending order. Note: there is a unique middle value for an odd number of data values, but two middle values for an even number of data values. In the latter case, the average of the two middle values is taken as the median. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
24 Some statistics Given a list of data, the mean is the arithmetic average of the data, that is, the sum of the data divided by the number of data values. Example: Given the data 5, 6, 13, 14, 3, 3, 3, 4, and 12, the mean is = = 7. The median of a list of data is the middle value when the data are listed in ascending order. Note: there is a unique middle value for an odd number of data values, but two middle values for an even number of data values. In the latter case, the average of the two middle values is taken as the median. Example: The previous data listed in order are 3, 3, 3, 4, 5, 6, 12, 13, and 14, so the median value is 5. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
25 Some statistics Given a list of data, the mean is the arithmetic average of the data, that is, the sum of the data divided by the number of data values. Example: Given the data 5, 6, 13, 14, 3, 3, 3, 4, and 12, the mean is = = 7. The median of a list of data is the middle value when the data are listed in ascending order. Note: there is a unique middle value for an odd number of data values, but two middle values for an even number of data values. In the latter case, the average of the two middle values is taken as the median. Example: The previous data listed in order are 3, 3, 3, 4, 5, 6, 12, 13, and 14, so the median value is 5. Example: The median of 4, 8, 9, 13, 14, 22 is = 11. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
26 Some statistics (cont d) The mode of a set a data is the value which occurs most frequently. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
27 Some statistics (cont d) The mode of a set a data is the value which occurs most frequently. Example: The mode of the data 5, 6, 13, 14, 3, 3, 3, 4, and 12 is 3. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
28 Some statistics (cont d) The mode of a set a data is the value which occurs most frequently. Example: The mode of the data 5, 6, 13, 14, 3, 3, 3, 4, and 12 is 3. Example Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
29 Some statistics (cont d) The mode of a set a data is the value which occurs most frequently. Example: The mode of the data 5, 6, 13, 14, 3, 3, 3, 4, and 12 is 3. Example Suppose a company has 100 employees with a salary of $30, 000 per year, 20 employees who make $50, 000 per year, 5 employees who make $100, 000 per year, and one employee who makes $5, 000, 000 per year. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
30 Some statistics (cont d) The mode of a set a data is the value which occurs most frequently. Example: The mode of the data 5, 6, 13, 14, 3, 3, 3, 4, and 12 is 3. Example Suppose a company has 100 employees with a salary of $30, 000 per year, 20 employees who make $50, 000 per year, 5 employees who make $100, 000 per year, and one employee who makes $5, 000, 000 per year. Then the mean salary is (100 30, 000) + (20 50, 000) + (5 100, 000) + 5, 000, , 500, 000 = = $75, 397 per year, 126 the median salary is $30, 000 per year, and the mode is also $30, 000 per year. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
31 Some statistics (cont d) The mode of a set a data is the value which occurs most frequently. Example: The mode of the data 5, 6, 13, 14, 3, 3, 3, 4, and 12 is 3. Example Suppose a company has 100 employees with a salary of $30, 000 per year, 20 employees who make $50, 000 per year, 5 employees who make $100, 000 per year, and one employee who makes $5, 000, 000 per year. Then the mean salary is (100 30, 000) + (20 50, 000) + (5 100, 000) + 5, 000, , 500, 000 = = $75, 397 per year, 126 the median salary is $30, 000 per year, and the mode is also $30, 000 per year. What is the average salary in this company? Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
32 Some statistics (cont d) Note: If the data are symmetrically distributed, then the median and the mean will be close to each other, but if the data are not symmetrically distributed they can be very different. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
33 Some statistics (cont d) Note: If the data are symmetrically distributed, then the median and the mean will be close to each other, but if the data are not symmetrically distributed they can be very different. In particular, like in the last example, a few very large data values will affect the mean but not the median. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
34 Some statistics (cont d) Note: If the data are symmetrically distributed, then the median and the mean will be close to each other, but if the data are not symmetrically distributed they can be very different. In particular, like in the last example, a few very large data values will affect the mean but not the median. The result is that for economic data like incomes or housing prices, the mean is often much larger than the median. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
35 Some statistics (cont d) Note: If the data are symmetrically distributed, then the median and the mean will be close to each other, but if the data are not symmetrically distributed they can be very different. In particular, like in the last example, a few very large data values will affect the mean but not the median. The result is that for economic data like incomes or housing prices, the mean is often much larger than the median. In such cases, the median is more indicative of the average than is the mean. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
36 Problems 1. In 1798 Henry Cavendish repeated an experiment for measuring the density of the earth 23 times. His results were a. Find the mean of this data. b. Find the median of this data. c. Find the mode of this data. Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
37 Problems (cont d) 2. The number of home runs hit by the American League home run leaders for the years 1972 to 1991 are as follows: 37, 32, 32, 36, 32, 39, 46, 45, 41, 22, 39, 39, 43, 40, 40, 49, 42, 36, 51, 44. a. Find the mean of this data. b. Find the median of this data. c. Find the mode of this data. d. One of the numbers in this data set appears to be inconsistent with the other values. Remove this value and recompute the mean, median, and mode for the remaining data. Can you think of an explanation for the unusual value? 3. Suppose you read in one newspaper that the average salary of an NBA basketball player is $1,000,000 and you read in another newspaper that the average salary of an NBA basketball player is $4,000,000. Which one of these numbers is the mean salary and which one is the median salary? Dan Sloughter (Furman University) The Foundations of Vital Statistics October 26, / 12
Chapter 3: Elements of Chance: Probability Methods
Chapter 3: Elements of Chance: Methods Department of Mathematics Izmir University of Economics Week 3-4 2014-2015 Introduction In this chapter we will focus on the definitions of random experiment, outcome,
Contemporary Mathematics Math 1030 Sample Exam I Chapters Time Limit: 90 Minutes No Scratch Paper Calculator Allowed: Scientific
Contemporary Mathematics Math 1030 Sample Exam I Chapters 13-15 Time Limit: 90 Minutes No Scratch Paper Calculator Allowed: Scientific Name: The point value of each problem is in the left-hand margin.
MAT Mathematics in Today's World
MAT 1000 Mathematics in Today's World Last Time 1. Three keys to summarize a collection of data: shape, center, spread. 2. The distribution of a data set: which values occur, and how often they occur 3.
Symmetric (Mean and Standard Deviation)
Summary: Unit 2 & 3 Distributions for Quantitative Data Topics covered in Module 2: How to calculate the Mean, Median, IQR Shapes of Histograms, Dotplots, Boxplots Know the difference between categorical
Realizing Strategies for winning games. Senior Project Presented by Tiffany Johnson Math 498 Fall 1999
Realizing Strategies for winning games Senior Project Presented by Tiffany Johnson Math 498 Fall 1999 Outline of Project Briefly show how math relates to popular board games in playing surfaces & strategies
1. Activities (from Guidelines in Number)
Teach Early Years Number page 16 13 Count all to add (two collections) Targets Children usually start to add by recounting both numbers of objects as an entirely new set to be counted. The next step is
2. The value of the middle term in a ranked data set is called: A) the mean B) the standard deviation C) the mode D) the median
1. An outlier is a value that is: A) very small or very large relative to the majority of the values in a data set B) either 100 units smaller or 100 units larger relative to the majority of the values
Univariate Descriptive Statistics
Univariate Descriptive Statistics Displays: pie charts, bar graphs, box plots, histograms, density estimates, dot plots, stemleaf plots, tables, lists. Example: sea urchin sizes Boxplot Histogram Urchin
36, 21, 27, 24, 54, 28,36, 43, 22, 29, 37, 40, 26, 25, 38, 23, 44, 30, 26, 39, 37, 40, 38, 36, 41, 45, 52, 42, 43, 42, 48, 50, 53
Frequency and Data Distribution - Step-by-Step Lesson A police officer monitored the speed (mph) of the cars in a particular traffic area. 36, 21, 27, 24, 54, 28,36, 43, 22, 29, 37, 40, 26, 25, 38, 23,
Math 227 Elementary Statistics. Bluman 5 th edition
Math 227 Elementary Statistics Bluman 5 th edition CHAPTER 4 Probability and Counting Rules 2 Objectives Determine sample spaces and find the probability of an event using classical probability or empirical
The Red and the Black
The Red and the Black Mathematics 15: Lecture 15 Dan Sloughter Furman University October 18, 2006 Dan Sloughter (Furman University) The Red and the Black October 18, 2006 1 / 9 Charles Sanders Peirce Max
Junior Circle Meeting 5 Probability. May 2, ii. In an actual experiment, can one get a different number of heads when flipping a coin 100 times?
Junior Circle Meeting 5 Probability May 2, 2010 1. We have a standard coin with one side that we call heads (H) and one side that we call tails (T). a. Let s say that we flip this coin 100 times. i. How
16.1 Introduction Numbers in General Form
16.1 Introduction You have studied various types of numbers such as natural numbers, whole numbers, integers and rational numbers. You have also studied a number of interesting properties about them. In
Two congruences involving 4-cores
Two congruences involving 4-cores ABSTRACT. The goal of this paper is to prove two new congruences involving 4- cores using elementary techniques; namely, if a 4 (n) denotes the number of 4-cores of n,
Math 1070 Sample Exam 1
University of Connecticut Department of Mathematics Math 1070 Sample Exam 1 Exam 1 will cover sections 4.1-4.7 and 5.1-5.4. This sample exam is intended to be used as one of several resources to help you
MATH , Summer I Homework - 05
MATH 2300-02, Summer I - 200 Homework - 05 Name... TRUE/FALSE. Write 'T' if the statement is true and 'F' if the statement is false. Due on Tuesday, October 26th ) True or False: If p remains constant
Probability and Statistics - Grade 5
Probability and Statistics - Grade 5. If you were to draw a single card from a deck of 52 cards, what is the probability of getting a card with a prime number on it? (Answer as a reduced fraction.) 2.
1. How many subsets are there for the set of cards in a standard playing card deck? How many subsets are there of size 8?
Math 1711-A Summer 2016 Final Review 1 August 2016 Time Limit: 170 Minutes Name: 1. How many subsets are there for the set of cards in a standard playing card deck? How many subsets are there of size 8?
Test 2 SOLUTIONS (Chapters 5 7)
Test 2 SOLUTIONS (Chapters 5 7) 10 1. I have been sitting at my desk rolling a six-sided die (singular of dice), and counting how many times I rolled a 6. For example, after my first roll, I had rolled
(a) Suppose you flip a coin and roll a die. Are the events obtain a head and roll a 5 dependent or independent events?
Unit 6 Probability Name: Date: Hour: Multiplication Rule of Probability By the end of this lesson, you will be able to Understand Independence Use the Multiplication Rule for independent events Independent
Basic Probability Concepts
6.1 Basic Probability Concepts How likely is rain tomorrow? What are the chances that you will pass your driving test on the first attempt? What are the odds that the flight will be on time when you go
SAMPLE. This chapter deals with the construction and interpretation of box plots. At the end of this chapter you should be able to:
find the upper and lower extremes, the median, and the upper and lower quartiles for sets of numerical data calculate the range and interquartile range compare the relative merits of range and interquartile
CCS Algebra I Assessment Test 1B Name Per
CCS Algebra I Assessment Test 1B Name Per Do this test carefully showing all of your work and, in the case of multiple choice items, filling in the circle of the letter of the correct response. Note which
As we rapidly approach summer you should be aware of your right to apply for unemployment benefits (UIB).
Greetings Fellow Lecturers, As we rapidly approach summer you should be aware of your right to apply for unemployment benefits (UIB). All temporary faculty (i.e., contingent part-time lecturers - PTLs),
Unit 1B-Modelling with Statistics. By: Niha, Julia, Jankhna, and Prerana
Unit 1B-Modelling with Statistics By: Niha, Julia, Jankhna, and Prerana [ Definitions ] A population is any large collection of objects or individuals, such as Americans, students, or trees about which
Math 1070 Sample Exam 2
University of Connecticut Department of Mathematics Math 1070 Sample Exam 2 Exam 2 will cover sections 4.6, 4.7, 5.2, 5.3, 5.4, 6.1, 6.2, 6.3, 6.4, F.1, F.2, F.3 and F.4. This sample exam is intended to
, -the of all of a probability experiment. consists of outcomes. (b) List the elements of the event consisting of a number that is greater than 4.
4-1 Sample Spaces and Probability as a general concept can be defined as the chance of an event occurring. In addition to being used in games of chance, probability is used in the fields of,, and forecasting,
Ex 1: A coin is flipped. Heads, you win $1. Tails, you lose $1. What is the expected value of this game?
AFM Unit 7 Day 5 Notes Expected Value and Fairness Name Date Expected Value: the weighted average of possible values of a random variable, with weights given by their respective theoretical probabilities.
They Grow Up So Fast: A Project on Budgeting
They Grow Up So Fast: A Project on Budgeting Task Due date 1) Your family 5/28 2) Get a Job 5/28 3) Death and Taxes 5/28 4) Roof Over Your Head 6/3 5) Get Your Motor 6/3 Running 6) Oh My Darling Babies
Statistical Measures
Statistical Measures Pre-Algebra section 10.1 Statistics is an area of math that deals with gathering information (called data). It is often used to make predictions. Important terms: Population A population
University of Connecticut Department of Mathematics
University of Connecticut Department of Mathematics Math 1070 Sample Exam 2 Fall 2014 Name: Instructor Name: Section: Exam 2 will cover Sections 4.6-4.7, 5.3-5.4, 6.1-6.4, and F.1-F.3. This sample exam
5. Aprimenumberisanumberthatisdivisibleonlyby1anditself. Theprimenumbers less than 100 are listed below.
1. (a) Let x 1,x 2,...,x n be a given data set with mean X. Now let y i = x i + c, for i =1, 2,...,n be a new data set with mean Ȳ,wherecisaconstant. What will be the value of Ȳ compared to X? (b) Let
Partial Answers to the 2005 Final Exam
Partial Answers to the 2005 Final Exam Econ 159a/MGT522a Ben Polak Fall 2007 PLEASE NOTE: THESE ARE ROUGH ANSWERS. I WROTE THEM QUICKLY SO I AM CAN'T PROMISE THEY ARE RIGHT! SOMETIMES I HAVE WRIT- TEN
The Haberdashers Aske s Boys School Elstree. 11+ Entrance Examination 2010
The Haberdashers Aske s Boys School Elstree 11+ Entrance Examination 2010 MATHEMATICS One Hour Full Name... Examination Number... INSTRUCTIONS 1. DO NOT OPEN THIS PAPER UNTIL YOU ARE TOLD TO DO SO. 2.
Inequality as difference: A teaching note on the Gini coefficient
Inequality as difference: A teaching note on the Gini coefficient Samuel Bowles Wendy Carlin SFI WORKING PAPER: 07-0-003 SFI Working Papers contain accounts of scienti5ic work of the author(s) and do not
(Notice that the mean doesn t have to be a whole number and isn t normally part of the original set of data.)
One-Variable Statistics Descriptive statistics that analyze one characteristic of one sample Where s the middle? How spread out is it? Where do different pieces of data compare? To find 1-variable statistics
Multiple Integrals. Advanced Calculus. Lecture 1 Dr. Lahcen Laayouni. Department of Mathematics and Statistics McGill University.
Lecture epartment of Mathematics and Statistics McGill University January 4, 27 ouble integrals Iteration of double integrals ouble integrals Consider a function f(x, y), defined over a rectangle = [a,
Individual 5 th Grade
5 th Grade Instructions: Problems 1 10 are multiple choice and count towards your team score. Bubble in the letter on your answer sheet. Be sure to erase all mistakes completely. 1. Which of the following
Workout 5 Solutions. Peter S. Simon. Quiz, December 8, 2004
Workout 5 Solutions Peter S. Simon Quiz, December 8, 2004 Problem 1 Marika shoots a basketball until she makes 20 shots or until she has made 60% of her shots, whichever happens first. After she has made
A Mathematical Analysis of Oregon Lottery Keno
Introduction A Mathematical Analysis of Oregon Lottery Keno 2017 Ted Gruber This report provides a detailed mathematical analysis of the keno game offered through the Oregon Lottery (http://www.oregonlottery.org/games/draw-games/keno),
Block 1 - Sets and Basic Combinatorics. Main Topics in Block 1:
Block 1 - Sets and Basic Combinatorics Main Topics in Block 1: A short revision of some set theory Sets and subsets. Venn diagrams to represent sets. Describing sets using rules of inclusion. Set operations.
ENGLAND FOR BEGINNERS
ENGLAND FOR BEGINNERS Christine Hitchmough 2017 Like all genealogical research, searching for ancestors in England begins at home. Look for records with information of your ancestors, certificates, letters,
Math 4610, Problems to be Worked in Class
Math 4610, Problems to be Worked in Class Bring this handout to class always! You will need it. If you wish to use an expanded version of this handout with space to write solutions, you can download one
CHAPTER 7 Probability
CHAPTER 7 Probability 7.1. Sets A set is a well-defined collection of distinct objects. Welldefined means that we can determine whether an object is an element of a set or not. Distinct means that we can
7.1 Chance Surprises, 7.2 Predicting the Future in an Uncertain World, 7.4 Down for the Count
7.1 Chance Surprises, 7.2 Predicting the Future in an Uncertain World, 7.4 Down for the Count Probability deals with predicting the outcome of future experiments in a quantitative way. The experiments
Unemployment Workshop
Unemployment Workshop Santa Monica College Faculty Association Spring 2011 Essentials Why File: It is your right (Cervisi v. Unemployment Ins. Appeals Bd. (1989)) When To File: Wednesday, June 15th Where
Finding Ancestors Using the Family History Research Wiki
Finding Ancestors Using the Family History Research Wiki The Family History Research Wiki is an extremely valuable tool we can use to learn how to find information on our ancestors. It offers information
copyright amberpasillas2010 What is Divisibility? Divisibility means that after dividing, there will be No remainder.
What is Divisibility? Divisibility means that after dividing, there will be No remainder. 1 356,821 Can you tell by just looking at this number if it is divisible by 2? by 5? by 10? by 3? by 9? By 6? The
Grade 8 Math Assignment: Probability
Grade 8 Math Assignment: Probability Part 1: Rock, Paper, Scissors - The Study of Chance Purpose An introduction of the basic information on probability and statistics Materials: Two sets of hands Paper
ECON 282 Final Practice Problems
ECON 282 Final Practice Problems S. Lu Multiple Choice Questions Note: The presence of these practice questions does not imply that there will be any multiple choice questions on the final exam. 1. How
Session 5 Variation About the Mean
Session 5 Variation About the Mean Key Terms for This Session Previously Introduced line plot median variation New in This Session allocation deviation from the mean fair allocation (equal-shares allocation)
Lessons for conflict resolution and postconflict reconstruction: The case of the 5 th Population Census of the Sudan
Lessons for conflict resolution and postconflict reconstruction: The case of the 5 th Population Census of the Sudan Pali Lehohla Statistician-General South Africa 25-02-2009 Concluding Remarks Census
1. For which of the following sets does the mean equal the median?
1. For which of the following sets does the mean equal the median? I. {1, 2, 3, 4, 5} II. {3, 9, 6, 15, 12} III. {13, 7, 1, 11, 9, 19} A. I only B. I and II C. I and III D. I, II, and III E. None of the
AP Statistics Ch In-Class Practice (Probability)
AP Statistics Ch 14-15 In-Class Practice (Probability) #1a) A batter who had failed to get a hit in seven consecutive times at bat then hits a game-winning home run. When talking to reporters afterward,
Topic : ADDITION OF PROBABILITIES (MUTUALLY EXCLUSIVE EVENTS) TIME : 4 X 45 minutes
Worksheet 6 th Topic : ADDITION OF PROBABILITIES (MUTUALLY EXCLUSIVE EVENTS) TIME : 4 X 45 minutes STANDARD COMPETENCY : 1. To use the statistics rules, the rules of counting, and the characteristic of
MA10103: Foundation Mathematics I. Lecture Notes Week 3
MA10103: Foundation Mathematics I Lecture Notes Week 3 Indices/Powers In an expression a n, a is called the base and n is called the index or power or exponent. Multiplication/Division of Powers a 3 a
15,504 15, ! 5!
Math 33 eview (answers). Suppose that you reach into a bag and randomly select a piece of candy from chocolates, 0 caramels, and peppermints. Find the probability of: a) selecting a chocolate b) selecting
Unit Five Answer Keys
Probability & Data Analysis Unit Five Unit Five Answer Keys Session Blacklines A. A., Unit Five Pre-Assessment a 7 7 7 7 b range = mode = median = c Graphs may vary slightly. xample: Number of Students
Math 152: Applicable Mathematics and Computing
Math 152: Applicable Mathematics and Computing April 16, 2017 April 16, 2017 1 / 17 Announcements Please bring a blue book for the midterm on Friday. Some students will be taking the exam in Center 201,
10. Because the order of selection doesn t matter: selecting 3, then 5 is the same as selecting 5, then 3. 25! 24 = 300
Chapter 6 Answers Lesson 6.1 1. li, lo, ln, ls, il, io, in, is, ol, oi, on, os, nl, ni, no, ns, sl, si, so, sn 2. 5, 4, 5 4 = 20, 6 5 = 30 3. (1,2) (1,3) (1,4) (1,5) (1,6) (1,7) (1,8) (1,9) (2,3) (2,4)
out one marble and then a second marble without replacing the first. What is the probability that both marbles will be white?
Example: Leah places four white marbles and two black marbles in a bag She plans to draw out one marble and then a second marble without replacing the first What is the probability that both marbles will
University of Connecticut Department of Mathematics
University of Connecticut Department of Mathematics Math 070Q Exam A Fall 07 Name: TA Name: Discussion: Read This First! This is a closed notes, closed book exam. You cannot receive aid on this exam from
Western Australian Junior Mathematics Olympiad 2007
Western Australian Junior Mathematics Olympiad 2007 Individual Questions 100 minutes General instructions: Each solution in this part is a positive integer less than 100. No working is needed for Questions
1. Let X be a continuous random variable such that its density function is 8 < k(x 2 +1), 0 <x<1 f(x) = 0, elsewhere.
Lebanese American University Spring 2006 Byblos Date: 3/03/2006 Duration: h 20. Let X be a continuous random variable such that its density function is 8 < k(x 2 +), 0
Three Pile Nim with Move Blocking. Arthur Holshouser. Harold Reiter.
Three Pile Nim with Move Blocking Arthur Holshouser 3600 Bullard St Charlotte, NC, USA Harold Reiter Department of Mathematics, University of North Carolina Charlotte, Charlotte, NC 28223, USA hbreiter@emailunccedu
Math Exam 2 Review. NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5.
Math 166 Fall 2008 c Heather Ramsey Page 1 Math 166 - Exam 2 Review NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5. Section 3.2 - Measures of Central Tendency
Math Exam 2 Review. NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5.
Math 166 Fall 2008 c Heather Ramsey Page 1 Math 166 - Exam 2 Review NOTE: For reviews of the other sections on Exam 2, refer to the first page of WIR #4 and #5. Section 3.2 - Measures of Central Tendency
The study of human populations involves working not PART 2. Cemetery Investigation: An Exercise in Simple Statistics POPULATIONS
PART 2 POPULATIONS Cemetery Investigation: An Exercise in Simple Statistics 4 When you have completed this exercise, you will be able to: 1. Work effectively with data that must be organized in a useful
CSI 23 LECTURE NOTES (Ojakian) Topics 5 and 6: Probability Theory
CSI 23 LECTURE NOTES (Ojakian) Topics 5 and 6: Probability Theory 1. Probability Theory OUTLINE (References: 5.1, 5.2, 6.1, 6.2, 6.3) 2. Compound Events (using Complement, And, Or) 3. Conditional Probability
Midterm 2 Practice Problems
Midterm 2 Practice Problems May 13, 2012 Note that these questions are not intended to form a practice exam. They don t necessarily cover all of the material, or weight the material as I would. They are
What is a Z-Code Almanac?
ZcodeSystem.com Presents Guide v.2.1. The Almanac Beta is updated in real time. All future updates are included in your membership What is a Z-Code Almanac? Today we are really excited to share our progress
Demographic and Social Statistics in the United Nations Demographic Yearbook*
UNITED NATIONS SECRETARIAT Background document Department of Economic and Social Affairs September 2008 Statistics Division English only United Nations Expert Group Meeting on the Scope and Content of
Lesson 10: Using Simulation to Estimate a Probability
Lesson 10: Using Simulation to Estimate a Probability Classwork In previous lessons, you estimated probabilities of events by collecting data empirically or by establishing a theoretical probability model.
Multiples and Divisibility
Multiples and Divisibility A multiple of a number is a product of that number and an integer. Divisibility: A number b is said to be divisible by another number a if b is a multiple of a. 45 is divisible
CHAPTERS 14 & 15 PROBABILITY STAT 203
CHAPTERS 14 & 15 PROBABILITY STAT 203 Where this fits in 2 Up to now, we ve mostly discussed how to handle data (descriptive statistics) and how to collect data. Regression has been the only form of statistical
Chapter 2. Describing Distributions with Numbers. BPS - 5th Ed. Chapter 2 1
Chapter 2 Describing Distributions with Numbers BPS - 5th Ed. Chapter 2 1 Numerical Summaries Center of the data mean median Variation range quartiles (interquartile range) variance standard deviation
Lecture 16 Sections Tue, Feb 10, 2009
s Lecture 16 Sections 5.3.1-5.3.3 Hampden-Sydney College Tue, Feb 10, 2009 Outline s 1 2 3 s 4 5 6 7 s Exercise 5.6, p. 311. salaries of superstar professional athletes receive much attention in the media.
Game Theory. Chapter 2 Solution Methods for Matrix Games. Instructor: Chih-Wen Chang. Chih-Wen NCKU. Game Theory, Ch2 1
Game Theory Chapter 2 Solution Methods for Matrix Games Instructor: Chih-Wen Chang Chih-Wen Chang @ NCKU Game Theory, Ch2 1 Contents 2.1 Solution of some special games 2.2 Invertible matrix games 2.3 Symmetric
Lecture Start
Lecture -- 4 -- Start Outline 1. Science, Method & Measurement 2. On Building An Index 3. Correlation & Causality 4. Probability & Statistics 5. Samples & Surveys 6. Experimental & Quasi-experimental Designs
Grade 6 Math Circles Fall Oct 14/15 Probability
1 Faculty of Mathematics Waterloo, Ontario Centre for Education in Mathematics and Computing Grade 6 Math Circles Fall 2014 - Oct 14/15 Probability Probability is the likelihood of an event occurring.
AP Statistics Composition Book Review Chapters 1 2
AP Statistics Composition Book Review Chapters 1 2 Terms/vocabulary: Explain each term with in the STATISTICAL context. Bar Graph Bimodal Categorical Variable Density Curve Deviation Distribution Dotplot
They Grow up so Fast: A project on budgeting
They Grow up so Fast: A project on budgeting The objective of this project is for you to set up a budget that would allow you to live the type of life you would like, as well as to understand what skills
ITEC 2600 Introduction to Analytical Programming. Instructor: Prof. Z. Yang Office: DB3049
ITEC 2600 Introduction to Analytical Programming Instructor: Prof. Z. Yang Office: DB3049 Lecture Eleven Monte Carlo Simulation Monte Carlo Simulation Monte Carlo simulation is a computerized mathematical
BUSINESS EMPLOYMENT DYNAMICS
BUSINESS EMPLOYMENT DYNAMICS First Quarter 2018 Office of Research Kurt Westby, Commissioner Andrew Condon, Director of Research WETHERSFIELD, November 7th, 2018 - (BED) data published quarterly by the
MEP Practice Book ES5. 1. A coin is tossed, and a die is thrown. List all the possible outcomes.
5 Probability MEP Practice Book ES5 5. Outcome of Two Events 1. A coin is tossed, and a die is thrown. List all the possible outcomes. 2. A die is thrown twice. Copy the diagram below which shows all the
How Do I Start My Family History?
How Do I Start My Family History? Step 1. Write Down What You Already Know about Your Family Using the example below, fill out the attached Pedigree Work Sheet with the information you already know about
Find the following for the Weight of Football Players. Sample standard deviation n=
Find the following for the Weight of Football Players x Sample standard deviation n= Fun Coming Up! 3-3 Measures of Position Z-score Percentile Quartile Outlier Bluman, Chapter 3 3 Measures of Position:
n(s)=the number of ways an event can occur, assuming all ways are equally likely to occur. p(e) = n(e) n(s)
The following story, taken from the book by Polya, Patterns of Plausible Inference, Vol. II, Princeton Univ. Press, 1954, p.101, is also quoted in the book by Szekely, Classical paradoxes of probability
What numbers can we make?
Meeting Student s Booklet What numbers can we make? October 12, 2016 @ UCI Contents 1 Even or odd? 2 New currency A present for Dad 4 A present for Mom 5 Challenges 6 Crystal Ball UC IRVINE MATH CEO http://www.math.uci.edu/mathceo/
Starting Family Tree: Navigating, adding, standardizing, printing
Starting Family Tree: Navigating, adding, standardizing, printing The FamilySearch logo on the upper left is a functioning icon. Clicking on this takes you back to the home page for the website. The website
Ace of diamonds. Graphing worksheet
Ace of diamonds Produce a screen displaying a the Ace of diamonds. 2006 Open University A silver-level, graphing challenge. Reference number SG1 Graphing worksheet Choose one of the following topics and
Live Casino game rules. 1. Live Baccarat. 2. Live Blackjack. 3. Casino Hold'em. 4. Generic Rulette. 5. Three card Poker
Live Casino game rules 1. Live Baccarat 2. Live Blackjack 3. Casino Hold'em 4. Generic Rulette 5. Three card Poker 1. LIVE BACCARAT 1.1. GAME OBJECTIVE The objective in LIVE BACCARAT is to predict whose
Introduction to R Software Prof. Shalabh Department of Mathematics and Statistics Indian Institute of Technology, Kanpur
Introduction to R Software Prof. Shalabh Department of Mathematics and Statistics Indian Institute of Technology, Kanpur Lecture - 03 Command line, Data Editor and R Studio Welcome to the lecture on introduction
RIPPLES. 14 Patterns/Functions Grades 7-8 ETA.hand2mind. Getting Ready. The Activity On Their Own (Part 1) What You ll Need.
RIPPLES Pattern recognition Growth patterns Arithmetic sequences Writing algebraic expressions Getting Ready What You ll Need Pattern Blocks, set per pair Colored pencils or markers Activity master, page
Stat 20: Intro to Probability and Statistics
Stat 20: Intro to Probability and Statistics Lecture 17: Using the Normal Curve with Box Models Tessa L. Childers-Day UC Berkeley 23 July 2014 By the end of this lecture... You will be able to: Draw and
Digital Image Processing. Digital Image Fundamentals II 12 th June, 2017
Digital Image Processing Digital Image Fundamentals II 12 th June, 2017 Image Enhancement Image Enhancement Types of Image Enhancement Operations Neighborhood Operations on Images Spatial Filtering Filtering
Median and Mode. Focus on. Early in the school year, Melanie and Amir had the exact same scores. How do you determine median and mode?
Median and Mode Early in the school year, Melanie and Amir had the exact same scores Focus on on five weekly math quizzes. Their scores out of 10 were 8, 9, 4, 5, 9. Their teacher asked them to report
Chapter 6: Descriptive Statistics
Chapter 6: Descriptive Statistics Problem (01): Make a frequency distribution table for the following data using 5 classes. 5 10 7 19 25 12 15 7 6 8 17 17 22 21 7 7 24 5 6 5 Problem (02): Annual Salaries
Foundations of Probability Worksheet Pascal
Foundations of Probability Worksheet Pascal The basis of probability theory can be traced back to a small set of major events that set the stage for the development of the field as a branch of mathematics.
MATH 13150: Freshman Seminar Unit 4
MATH 1150: Freshman Seminar Unit 1. How to count the number of collections The main new problem in this section is we learn how to count the number of ways to pick k objects from a collection of n objects,