International College of Economics and Finance Syllabus Probability Theory and Introductory Statistics

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "International College of Economics and Finance Syllabus Probability Theory and Introductory Statistics"

Transcription

1 International College of Economics and Finance Syllabus Probability Theory and Introductory Statistics Lecturer: Mikhail Zhitlukhin. 1. Course description Probability Theory and Introductory Statistics is a two-semester course for rst-year students of the ICEF specializing in economics. The course is taught in Russian and English. The course is devoted to basic notions of statistics: data collection methods, the notion of a population and a sample, descriptive statistics, statistical methods of parameter estimation and hypothesis testing, regression models, etc. The course also includes topics from Probability Theory, which are essential for a consistent delivery. 2. Course objectives The main objective of the course is to provide students with knowledge of basic statistics. By the end of the course the students should understand the subject of statistics and master its basic methods. They acquire skills of primary data analysis (how to nd a mean, a median, a standard deviation and other descriptive statistics), graphical representation of data (histograms, stem-and-leaf plots, dot plots, box plots). The students learn how to formulate and solve typical problems of basic statistics: point and interval parameter estimation, hypothesis testing, correlation analysis, regression models. An essential part of the course is devoted to basics of Probability Theory, which serves as a foundation of statistics. The students should understand the notion of a probability space, a random event, the probability of an event. They should know how to compute the probability of a complex event, solve basic combinatorial problems, understand the formula of total probability and the Bayes formula. The students should have a clear understanding of the concept of a random variable and its distribution. They should also understand the meaning of the Law of Large Numbers and the Central Limit Theorem. In classes students both solve theoretical problems and perform computer tasks with real data, develop practical skills and intuition. By the end of the course, students should understand the theory of statistical methods and be able to apply them in practice. In the course students obtain the amount of knowledge sucient for the AP Statistics test. 3. Methods The following methods and forms of study are used in the course: lectures (2 hours a week), classes (2 hours a week), weekly home assignments, oce hours, self-study. The course consists of 58 hours of lectures and 58 hours of classes. 4. Grade determination The students sit a written mid-term exam in the rst module and a nal semester exam in the end of the second module. The exams include multiple choice and free response questions. In the fourth module the students sit a mid-term exam of a similar form. After that the students have the AP Statistics exam. 1

2 The grade for the rst two modules is made up of the autumn mid-term exam grade (30%), the winter exam grade (60%), the average grade for home assignments, classroom activities and tests (10%). The nal course grade is made up of the grade for the rst two modules (25%), the grade for the spring mid-term exam (30%), the grade for the AP exam (35%), the average grade for home assignments, classroom activities and tests in the 3rd and 4th modules (10%). 5. Reading Textbook: 1. Wonnacott R. J., Wonnacott T. H. Introductory Statistics for Business and Economics. John Wiley & Sons, 4th edition, AP preparation: M. Sternstein. Barron's AP Statistics. 3. AP past problems and solutions: /exam_information/8357.html Advanced level reading: 1. A.N. Shiryaev. Probability. In Russian: À.Í. Øèðÿåâ. Âåðîÿòíîñòü-1. Èçä-âî ÌÖÍÌÎ. 2. Øèðÿåâ À. Í., Ýðëèõ È. Ã., ßñüêîâ Ï. À. Âåðîÿòíîñòü â òåîðåìàõ è çàäà àõ. ÌÖÍÌÎ, Ãìóðìàí Â. Å. Òåîðèÿ âåðîÿòíîñòåé è ìàòåìàòè åñêàÿ ñòàòèñòèêà. Âûñøàÿ øêîëà, Ãìóðìàí Â. Å. Ðóêîâîäñòâî ê ðåøåíèþ çàäà ïî òåîðèè âåðîÿòíîñòåé è ìàòåìàòè åñêîé ñòàòèñòèêå. Âûñøàÿ øêîëà, Hogg R. V. and Tanis E. A. Probability and Statistical Inference. Prentice Hall,

3 6. Course outline 1. Elements of probability theory (WW, Ch. 3, 4) 1.1 Experiment with random outcomes. Notion of probability. 1.2 Space of elementary outcomes as a mathematical model of an experiment with random outcomes. Algebra of events. Disjoint events. 1.3 Probability in a space of elementary outcomes. Classical probability. Elementary combinatorics. Probability of the sum of events. 1.4 Conditional probability. Probability of the product of events. Independent events. 1.5 The formula of total probability. The Bayes formula. 2. Discrete random variables (WW, Ch. 3, 4) 2.1 Examples of discrete random variables. Distribution of a discrete random variable. Relative frequencies and cumulative frequencies. 2.2 Mean value (expectation). Variance. Standard deviation. 2.3 Sequence of independent experiments. The binomial distribution. The geometric distribution. 3. Continuous random variables (WW, Ch. 3, 4) 3.1 Examples of continuous random variables. Distribution function. Distribution density. Mean value (expectation). Variance. Standard deviation. 3.2 The normal distribution, its properties. Normal distribution tables. 3.3 Linear transformations of random variables. 4. Two-dimensional distributions (WW, Ch. 5) 4.1 Joint distribution of two random variables. Marginal distribution. Conditional distribution. Conditional expectation. 4.2 Independent random variables. 4.3 Covariation coecient. Correlation as a measure of the linear relationship between two random variables. Uncorrelated and independent random variables. The expectation and the variance of a linear combination of random variables. 5. Limit theorems 5.1 The Law of Large Numbers. 5.2 The Central Limit Theorem. Normal approximation of the binomial distribution. 6. Basic data analysis and descriptive statistics (WW, Ch.2) 6.1 Graphical representation of data. Dot plots. Steam-and-leaf plots. Histograms. 6.2 Characteristics of data. Outliers. Clusters. Histogram shape. 6.3 Descriptive statistics. Measures of center of a distribution: arithmetic average, median, mode. Measures of dispersion of a distribution: range, mean-square deviation, interquartile range, average absolute deviation, average relative deviation. Representation of data with box plots. 6.4 Transformation of basic statistics under a linear transform of data. 6.5 Measures of location in a sample: quartiles, percentiles, z-scale. 6.6 Computations with grouped data. 7. Data collection, planning and conducting an experiment (WW, Ch.1) 7.1 Methods of data collection: census, sample survey, experiment, observational study. 7.2 Population, sample, random sample. 7.3 Sources of bias in sampling and surveys. 7.4 Types of sampling: simple random sampling, stratied random sampling, cluster sampling. 7.5 Planning and conducting an experiment. 7.6 Control groups, random assignments, replication. 7.7 Sources of bias in experiments. Mixing factors, placebo eect, blinding. 7.8 Completely randomized design. Block design. 3

4 8. Sampling distributions (WW, Ch. 6) 8.1 The distribution of the sample mean and the sample proportion. 8.2 The distribution of the dierence of two proportions. The distribution of the dierence of two independent sample means. 8.3 Student's t-distribution, the chi-squared distribution. 9. Point parameter estimation (WW, Ch. 7) 9.1 Point estimation of population parameters. Examples of point estimates: sample mean and sample variance. 9.2 Properties of estimates: unbiasedness, eciency, consistency. 9.3 Estimates of mean and variance. 9.4 Estimates of proportion. 10. Interval parameter estimation (WW, Ch. 8) 10.1 The notion of a condence interval. The condence interval for the mean of a population. Normal approximation for large samples. Small samples (Student's distribution) Condence intervals for the dierence of two population means (independent and matched samples) Condence intervals for the dierence of two proportions Two-sided and one-sided condence intervals. 11. Hypothesis testing (WW, Ch. 9) 11.1 Hypothesis and statistical test. Test for a population mean. Using condence intervals and test-statistics Two-sided and one-sided tests. P -value Type I errors and type II errors. Signicance and power of a test Standard tests: population mean, population proportion, dierence of two independent and matched samples, dierence of proportions Pearson's chi-squared test. Contingency tables. 12. Pair regression (WW, Ch. 11, 12) 12.1 XY plot. Fitting a line. Ordinary least squares Transformations into a linear model Outliers Fitted values Errors and residuals Statistical properties of regression estimates. Condence interval for the slope. Testing hypothesis for the slope. 4

5 7. Distribution of hours for topics and types of work No. Topics Number of hours lectures classes 1 Elements of Probability Theory Discrete random variables Continuous random variables Two-dimensional distributions Limit theorems Basic data analysis Data collection, planning and conducting an experiment Sampling distributions Point parameter estimation Interval parameter estimation Hypothesis testing Pair regression 6 6 TOTAL

Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics

Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics Institute of Actuaries of India Subject CT3 Probability and Mathematical Statistics For 2015 Examinations Aim The aim of the Probability and Mathematical Statistics subject is to provide a grounding in

More information

Fairfield Public Schools

Fairfield Public Schools Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity

More information

Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.

Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics. Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGraw-Hill/Irwin, 2008, ISBN: 978-0-07-331988-9. Required Computing

More information

Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics

Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGraw-Hill/Irwin, 2010, ISBN: 9780077384470 [This

More information

AP Statistics: Syllabus 1

AP Statistics: Syllabus 1 AP Statistics: Syllabus 1 Scoring Components SC1 The course provides instruction in exploring data. 4 SC2 The course provides instruction in sampling. 5 SC3 The course provides instruction in experimentation.

More information

LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE

LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE MAT 119 STATISTICS AND ELEMENTARY ALGEBRA 5 Lecture Hours, 2 Lab Hours, 3 Credits Pre-

More information

STAT 360 Probability and Statistics. Fall 2012

STAT 360 Probability and Statistics. Fall 2012 STAT 360 Probability and Statistics Fall 2012 1) General information: Crosslisted course offered as STAT 360, MATH 360 Semester: Fall 2012, Aug 20--Dec 07 Course name: Probability and Statistics Number

More information

INTRODUCTORY STATISTICS

INTRODUCTORY STATISTICS INTRODUCTORY STATISTICS FIFTH EDITION Thomas H. Wonnacott University of Western Ontario Ronald J. Wonnacott University of Western Ontario WILEY JOHN WILEY & SONS New York Chichester Brisbane Toronto Singapore

More information

Curriculum Map Statistics and Probability Honors (348) Saugus High School Saugus Public Schools 2009-2010

Curriculum Map Statistics and Probability Honors (348) Saugus High School Saugus Public Schools 2009-2010 Curriculum Map Statistics and Probability Honors (348) Saugus High School Saugus Public Schools 2009-2010 Week 1 Week 2 14.0 Students organize and describe distributions of data by using a number of different

More information

430 Statistics and Financial Mathematics for Business

430 Statistics and Financial Mathematics for Business Prescription: 430 Statistics and Financial Mathematics for Business Elective prescription Level 4 Credit 20 Version 2 Aim Students will be able to summarise, analyse, interpret and present data, make predictions

More information

Mathematics. Probability and Statistics Curriculum Guide. Revised 2010

Mathematics. Probability and Statistics Curriculum Guide. Revised 2010 Mathematics Probability and Statistics Curriculum Guide Revised 2010 This page is intentionally left blank. Introduction The Mathematics Curriculum Guide serves as a guide for teachers when planning instruction

More information

Tutor/(or Student) Guide to: Tutor-led Tutorials

Tutor/(or Student) Guide to: Tutor-led Tutorials Tutor/(or Student) Guide to: Tutor-led Tutorials (Module Code: Stat10050) Tutor Name: Module Co-ordinator: Dr. Patrick Murphy Description of Tutorials Introduction to Statistical Modelling Tutorials: Aim

More information

MAT 12O ELEMENTARY STATISTICS I

MAT 12O ELEMENTARY STATISTICS I LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE MAT 12O ELEMENTARY STATISTICS I 3 Lecture Hours, 1 Lab Hour, 3 Credits Pre-Requisite:

More information

PROBABILITY AND STATISTICS. Ma 527. 1. To teach a knowledge of combinatorial reasoning.

PROBABILITY AND STATISTICS. Ma 527. 1. To teach a knowledge of combinatorial reasoning. PROBABILITY AND STATISTICS Ma 527 Course Description Prefaced by a study of the foundations of probability and statistics, this course is an extension of the elements of probability and statistics introduced

More information

PCHS ALGEBRA PLACEMENT TEST

PCHS ALGEBRA PLACEMENT TEST MATHEMATICS Students must pass all math courses with a C or better to advance to the next math level. Only classes passed with a C or better will count towards meeting college entrance requirements. If

More information

NEW YORK CITY COLLEGE OF TECHNOLOGY The City University of New York

NEW YORK CITY COLLEGE OF TECHNOLOGY The City University of New York NEW YORK CITY COLLEGE OF TECHNOLOGY The City University of New York DEPARTMENT: Mathematics COURSE: MAT 1272/ MA 272 TITLE: DESCRIPTION: TEXT: Statistics An introduction to statistical methods and statistical

More information

Econometrics and Data Analysis I

Econometrics and Data Analysis I Econometrics and Data Analysis I Yale University ECON S131 (ONLINE) Summer Session A, 2014 June 2 July 4 Instructor: Doug McKee (douglas.mckee@yale.edu) Teaching Fellow: Yu Liu (dav.yu.liu@yale.edu) Classroom:

More information

Description. Textbook. Grading. Objective

Description. Textbook. Grading. Objective EC151.02 Statistics for Business and Economics (MWF 8:00-8:50) Instructor: Chiu Yu Ko Office: 462D, 21 Campenalla Way Phone: 2-6093 Email: kocb@bc.edu Office Hours: by appointment Description This course

More information

PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050

PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050 PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050 Class Hours: 2.0 Credit Hours: 3.0 Laboratory Hours: 2.0 Date Revised: Fall 2013 Catalog Course Description: Descriptive

More information

MATH BOOK OF PROBLEMS SERIES. New from Pearson Custom Publishing!

MATH BOOK OF PROBLEMS SERIES. New from Pearson Custom Publishing! MATH BOOK OF PROBLEMS SERIES New from Pearson Custom Publishing! The Math Book of Problems Series is a database of math problems for the following courses: Pre-algebra Algebra Pre-calculus Calculus Statistics

More information

UNIT 1: COLLECTING DATA

UNIT 1: COLLECTING DATA Core Probability and Statistics Probability and Statistics provides a curriculum focused on understanding key data analysis and probabilistic concepts, calculations, and relevance to real-world applications.

More information

Section Format Day Begin End Building Rm# Instructor. 001 Lecture Tue 6:45 PM 8:40 PM Silver 401 Ballerini

Section Format Day Begin End Building Rm# Instructor. 001 Lecture Tue 6:45 PM 8:40 PM Silver 401 Ballerini NEW YORK UNIVERSITY ROBERT F. WAGNER GRADUATE SCHOOL OF PUBLIC SERVICE Course Syllabus Spring 2016 Statistical Methods for Public, Nonprofit, and Health Management Section Format Day Begin End Building

More information

Probability and Statistics Vocabulary List (Definitions for Middle School Teachers)

Probability and Statistics Vocabulary List (Definitions for Middle School Teachers) Probability and Statistics Vocabulary List (Definitions for Middle School Teachers) B Bar graph a diagram representing the frequency distribution for nominal or discrete data. It consists of a sequence

More information

MTH 140 Statistics Videos

MTH 140 Statistics Videos MTH 140 Statistics Videos Chapter 1 Picturing Distributions with Graphs Individuals and Variables Categorical Variables: Pie Charts and Bar Graphs Categorical Variables: Pie Charts and Bar Graphs Quantitative

More information

business statistics using Excel OXFORD UNIVERSITY PRESS Glyn Davis & Branko Pecar

business statistics using Excel OXFORD UNIVERSITY PRESS Glyn Davis & Branko Pecar business statistics using Excel Glyn Davis & Branko Pecar OXFORD UNIVERSITY PRESS Detailed contents Introduction to Microsoft Excel 2003 Overview Learning Objectives 1.1 Introduction to Microsoft Excel

More information

The Big 50 Revision Guidelines for S1

The Big 50 Revision Guidelines for S1 The Big 50 Revision Guidelines for S1 If you can understand all of these you ll do very well 1. Know what is meant by a statistical model and the Modelling cycle of continuous refinement 2. Understand

More information

I ~ 14J... <r ku...6l &J&!J--=-O--

I ~ 14J... <r ku...6l &J&!J--=-O-- City College of San Francisco Technology-Mediated Course Proposal Course Outline Addendum I. GENERAL DESCRIPTION A. Date B. Department C. Course Identifier D. Course Title E. Addendum Preparer F. Chairperson

More information

Numerical Summarization of Data OPRE 6301

Numerical Summarization of Data OPRE 6301 Numerical Summarization of Data OPRE 6301 Motivation... In the previous session, we used graphical techniques to describe data. For example: While this histogram provides useful insight, other interesting

More information

Elementary Statistics. Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination

Elementary Statistics. Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination What is a Scatter Plot? A Scatter Plot is a plot of ordered pairs (x, y) where the horizontal axis is used

More information

Elementary Statistics

Elementary Statistics Elementary Statistics MATH 1342-42073 Syllabus Instructor: Scott Tyson E-mail: styson@austincc.edu Office: TBA Office Hours: TBA Meeting time: TTH 2:50pm-4:05pm Room: SAC 1301 1 The Course 1.1 Course Description

More information

Texas A&M University Central Texas Math 311 Probability and Statistics Online

Texas A&M University Central Texas Math 311 Probability and Statistics Online Texas A&M University Central Texas Math 311 Probability and Statistics Online Instructor: Mienie de Kock (Ph.D) Office: Warrior Hall Room 412- B Phone: (903) 705-9703 Email: dekock@tamuct.edu Office Hours:

More information

MATH 140 HYBRID INTRODUCTORY STATISTICS COURSE SYLLABUS

MATH 140 HYBRID INTRODUCTORY STATISTICS COURSE SYLLABUS MATH 140 HYBRID INTRODUCTORY STATISTICS COURSE SYLLABUS Instructor: Mark Schilling Email: mark.schilling@csun.edu (Note: If your CSUN email address is not one you use regularly, be sure to set up automatic

More information

Economic Statistics (ECON2006), Statistics and Research Design in Psychology (PSYC2010), Survey Design and Analysis (SOCI2007)

Economic Statistics (ECON2006), Statistics and Research Design in Psychology (PSYC2010), Survey Design and Analysis (SOCI2007) COURSE DESCRIPTION Title Code Level Semester Credits 3 Prerequisites Post requisites Introduction to Statistics ECON1005 (EC160) I I None Economic Statistics (ECON2006), Statistics and Research Design

More information

Geostatistics Exploratory Analysis

Geostatistics Exploratory Analysis Instituto Superior de Estatística e Gestão de Informação Universidade Nova de Lisboa Master of Science in Geospatial Technologies Geostatistics Exploratory Analysis Carlos Alberto Felgueiras cfelgueiras@isegi.unl.pt

More information

NEW YORK STATE TEACHER CERTIFICATION EXAMINATIONS

NEW YORK STATE TEACHER CERTIFICATION EXAMINATIONS NEW YORK STATE TEACHER CERTIFICATION EXAMINATIONS TEST DESIGN AND FRAMEWORK September 2014 Authorized for Distribution by the New York State Education Department This test design and framework document

More information

RARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS

RARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS RARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS I. Basic Course Information A. Course Number and Title: MATH 111H Statistics II Honors B. New or Modified Course:

More information

Quantitative Methods for Finance

Quantitative Methods for Finance Quantitative Methods for Finance Module 1: The Time Value of Money 1 Learning how to interpret interest rates as required rates of return, discount rates, or opportunity costs. 2 Learning how to explain

More information

A Correlation of. to the. South Carolina Data Analysis and Probability Standards

A Correlation of. to the. South Carolina Data Analysis and Probability Standards A Correlation of to the South Carolina Data Analysis and Probability Standards INTRODUCTION This document demonstrates how Stats in Your World 2012 meets the indicators of the South Carolina Academic Standards

More information

Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo

Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo Readings: Ha and Ha Textbook - Chapters 1 8 Appendix D & E (online) Plous - Chapters 10, 11, 12 and 14 Chapter 10: The Representativeness Heuristic Chapter 11: The Availability Heuristic Chapter 12: Probability

More information

Diablo Valley College Catalog 2014-2015

Diablo Valley College Catalog 2014-2015 Mathematics MATH Michael Norris, Interim Dean Math and Computer Science Division Math Building, Room 267 Possible career opportunities Mathematicians work in a variety of fields, among them statistics,

More information

Technology Step-by-Step Using StatCrunch

Technology Step-by-Step Using StatCrunch Technology Step-by-Step Using StatCrunch Section 1.3 Simple Random Sampling 1. Select Data, highlight Simulate Data, then highlight Discrete Uniform. 2. Fill in the following window with the appropriate

More information

RUTHERFORD HIGH SCHOOL Rutherford, New Jersey COURSE OUTLINE STATISTICS AND PROBABILITY

RUTHERFORD HIGH SCHOOL Rutherford, New Jersey COURSE OUTLINE STATISTICS AND PROBABILITY RUTHERFORD HIGH SCHOOL Rutherford, New Jersey COURSE OUTLINE STATISTICS AND PROBABILITY I. INTRODUCTION According to the Common Core Standards (2010), Decisions or predictions are often based on data numbers

More information

Moraine Valley Community College Course Syllabus

Moraine Valley Community College Course Syllabus Moraine Valley Community College Course Syllabus Course Title: Business Statistics Course Number: MTH 212 Semester: Fall 2006 I Faculty Information A. Instructor: Kevin M. Riordan, M.A. B. Office Hours:

More information

Course Syllabus MATH 110 Introduction to Statistics 3 credits

Course Syllabus MATH 110 Introduction to Statistics 3 credits Course Syllabus MATH 110 Introduction to Statistics 3 credits Prerequisites: Algebra proficiency is required, as demonstrated by successful completion of high school algebra, by completion of a college

More information

Indiana Academic Standards Mathematics: Probability and Statistics

Indiana Academic Standards Mathematics: Probability and Statistics Indiana Academic Standards Mathematics: Probability and Statistics 1 I. Introduction The college and career ready Indiana Academic Standards for Mathematics: Probability and Statistics are the result of

More information

4. Introduction to Statistics

4. Introduction to Statistics Statistics for Engineers 4-1 4. Introduction to Statistics Descriptive Statistics Types of data A variate or random variable is a quantity or attribute whose value may vary from one unit of investigation

More information

Exploratory Data Analysis

Exploratory Data Analysis Exploratory Data Analysis Johannes Schauer johannes.schauer@tugraz.at Institute of Statistics Graz University of Technology Steyrergasse 17/IV, 8010 Graz www.statistics.tugraz.at February 12, 2008 Introduction

More information

Statistics I for QBIC. Contents and Objectives. Chapters 1 7. Revised: August 2013

Statistics I for QBIC. Contents and Objectives. Chapters 1 7. Revised: August 2013 Statistics I for QBIC Text Book: Biostatistics, 10 th edition, by Daniel & Cross Contents and Objectives Chapters 1 7 Revised: August 2013 Chapter 1: Nature of Statistics (sections 1.1-1.6) Objectives

More information

Mathematics within the Psychology Curriculum

Mathematics within the Psychology Curriculum Mathematics within the Psychology Curriculum Statistical Theory and Data Handling Statistical theory and data handling as studied on the GCSE Mathematics syllabus You may have learnt about statistics and

More information

Chapter 3 Descriptive Statistics: Numerical Measures. Learning objectives

Chapter 3 Descriptive Statistics: Numerical Measures. Learning objectives Chapter 3 Descriptive Statistics: Numerical Measures Slide 1 Learning objectives 1. Single variable Part I (Basic) 1.1. How to calculate and use the measures of location 1.. How to calculate and use the

More information

Teaching Biostatistics to Postgraduate Students in Public Health

Teaching Biostatistics to Postgraduate Students in Public Health Teaching Biostatistics to Postgraduate Students in Public Health Peter A Lachenbruch - h s hgeles, California, USA 1. Introduction This paper describes how biostatistics is taught in US Schools of Public

More information

Cleveland State University NAL/PAD/PDD/UST 504 Section 51 Levin College of Urban Affairs Fall, 2009 W 6 to 9:50 pm UR 108

Cleveland State University NAL/PAD/PDD/UST 504 Section 51 Levin College of Urban Affairs Fall, 2009 W 6 to 9:50 pm UR 108 Cleveland State University NAL/PAD/PDD/UST 504 Section 51 Levin College of Urban Affairs Fall, 2009 W 6 to 9:50 pm UR 108 Department of Urban Studies Email: w.weizer @csuohio.edu Instructor: Winifred Weizer

More information

Notes on Probability and Statistics

Notes on Probability and Statistics Notes on Probability and Statistics Andrew Forrester January 28, 2009 Contents 1 The Big Picture 1 2 Counting with Combinatorics 2 2.1 Possibly Useful Notation...................................... 2 2.2

More information

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number 1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x - x) B. x 3 x C. 3x - x D. x - 3x 2) Write the following as an algebraic expression

More information

E3: PROBABILITY AND STATISTICS lecture notes

E3: PROBABILITY AND STATISTICS lecture notes E3: PROBABILITY AND STATISTICS lecture notes 2 Contents 1 PROBABILITY THEORY 7 1.1 Experiments and random events............................ 7 1.2 Certain event. Impossible event............................

More information

GCSE HIGHER Statistics Key Facts

GCSE HIGHER Statistics Key Facts GCSE HIGHER Statistics Key Facts Collecting Data When writing questions for questionnaires, always ensure that: 1. the question is worded so that it will allow the recipient to give you the information

More information

3818 - Introduction to Statistics (Online) Syllabus/Course Information

3818 - Introduction to Statistics (Online) Syllabus/Course Information 3818 - Introduction to Statistics (Online) Syllabus/Course Information Course Description Econ 3818 is a first course in probability and statistical methods, with an introduction to econometrics. This

More information

Algebra 1 2008. Academic Content Standards Grade Eight and Grade Nine Ohio. Grade Eight. Number, Number Sense and Operations Standard

Algebra 1 2008. Academic Content Standards Grade Eight and Grade Nine Ohio. Grade Eight. Number, Number Sense and Operations Standard Academic Content Standards Grade Eight and Grade Nine Ohio Algebra 1 2008 Grade Eight STANDARDS Number, Number Sense and Operations Standard Number and Number Systems 1. Use scientific notation to express

More information

Street Address: 1111 Franklin Street Oakland, CA 94607. Mailing Address: 1111 Franklin Street Oakland, CA 94607

Street Address: 1111 Franklin Street Oakland, CA 94607. Mailing Address: 1111 Franklin Street Oakland, CA 94607 Contacts University of California Curriculum Integration (UCCI) Institute Sarah Fidelibus, UCCI Program Manager Street Address: 1111 Franklin Street Oakland, CA 94607 1. Program Information Mailing Address:

More information

2013 MBA Jump Start Program. Statistics Module Part 3

2013 MBA Jump Start Program. Statistics Module Part 3 2013 MBA Jump Start Program Module 1: Statistics Thomas Gilbert Part 3 Statistics Module Part 3 Hypothesis Testing (Inference) Regressions 2 1 Making an Investment Decision A researcher in your firm just

More information

ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE. School of Mathematical Sciences

ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE. School of Mathematical Sciences ! ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE School of Mathematical Sciences New Revised COURSE: COS-MATH-252 Probability and Statistics II 1.0 Course designations and approvals:

More information

2. Filling Data Gaps, Data validation & Descriptive Statistics

2. Filling Data Gaps, Data validation & Descriptive Statistics 2. Filling Data Gaps, Data validation & Descriptive Statistics Dr. Prasad Modak Background Data collected from field may suffer from these problems Data may contain gaps ( = no readings during this period)

More information

STAT 2300: BUSINESS STATISTICS Section 002, Summer Semester 2009

STAT 2300: BUSINESS STATISTICS Section 002, Summer Semester 2009 STAT 2300: BUSINESS STATISTICS Section 002, Summer Semester 2009 Instructor: Bill Welbourn Office: Lund 117 Email: bill.welbourn@aggiemail.usu.edu Lectures: MWF 7:30AM 9:40AM in ENGR 104 Office Hours:

More information

Education & Training Plan Accounting Math Professional Certificate Program with Externship

Education & Training Plan Accounting Math Professional Certificate Program with Externship University of Texas at El Paso Professional and Public Programs 500 W. University Kelly Hall Ste. 212 & 214 El Paso, TX 79968 http://www.ppp.utep.edu/ Contact: Sylvia Monsisvais 915-747-7578 samonsisvais@utep.edu

More information

Education & Training Plan. Accounting Math Professional Certificate Program with Externship

Education & Training Plan. Accounting Math Professional Certificate Program with Externship Office of Professional & Continuing Education 301 OD Smith Hall Auburn, AL 36849 http://www.auburn.edu/mycaa Contact: Shavon Williams 334-844-3108; szw0063@auburn.edu Auburn University is an equal opportunity

More information

Alabama Department of Postsecondary Education

Alabama Department of Postsecondary Education Date Adopted 1998 Dates reviewed 2007, 2011, 2013 Dates revised 2004, 2008, 2011, 2013, 2015 Alabama Department of Postsecondary Education Representing Alabama s Public Two-Year College System Jefferson

More information

Manhattan Center for Science and Math High School Mathematics Department Curriculum

Manhattan Center for Science and Math High School Mathematics Department Curriculum Content/Discipline Algebra 1 Semester 2: Marking Period 1 - Unit 8 Polynomials and Factoring Topic and Essential Question How do perform operations on polynomial functions How to factor different types

More information

Course Description. Learning Objectives

Course Description. Learning Objectives STAT X400 (2 semester units in Statistics) Business, Technology & Engineering Technology & Information Management Quantitative Analysis & Analytics Course Description This course introduces students to

More information

Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization. Learning Goals. GENOME 560, Spring 2012

Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization. Learning Goals. GENOME 560, Spring 2012 Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization GENOME 560, Spring 2012 Data are interesting because they help us understand the world Genomics: Massive Amounts

More information

Big Ideas in Mathematics

Big Ideas in Mathematics Big Ideas in Mathematics which are important to all mathematics learning. (Adapted from the NCTM Curriculum Focal Points, 2006) The Mathematics Big Ideas are organized using the PA Mathematics Standards

More information

Business Analytics. Methods, Models, and Decisions. James R. Evans : University of Cincinnati PEARSON

Business Analytics. Methods, Models, and Decisions. James R. Evans : University of Cincinnati PEARSON Business Analytics Methods, Models, and Decisions James R. Evans : University of Cincinnati PEARSON Boston Columbus Indianapolis New York San Francisco Upper Saddle River Amsterdam Cape Town Dubai London

More information

Bowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition

Bowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition Bowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition Online Learning Centre Technology Step-by-Step - Excel Microsoft Excel is a spreadsheet software application

More information

Prentice Hall Algebra 2 2011 Correlated to: Colorado P-12 Academic Standards for High School Mathematics, Adopted 12/2009

Prentice Hall Algebra 2 2011 Correlated to: Colorado P-12 Academic Standards for High School Mathematics, Adopted 12/2009 Content Area: Mathematics Grade Level Expectations: High School Standard: Number Sense, Properties, and Operations Understand the structure and properties of our number system. At their most basic level

More information

MATH. ALGEBRA I HONORS 9 th Grade 12003200 ALGEBRA I HONORS

MATH. ALGEBRA I HONORS 9 th Grade 12003200 ALGEBRA I HONORS * Students who scored a Level 3 or above on the Florida Assessment Test Math Florida Standards (FSA-MAFS) are strongly encouraged to make Advanced Placement and/or dual enrollment courses their first choices

More information

Lecture 2: Descriptive Statistics and Exploratory Data Analysis

Lecture 2: Descriptive Statistics and Exploratory Data Analysis Lecture 2: Descriptive Statistics and Exploratory Data Analysis Further Thoughts on Experimental Design 16 Individuals (8 each from two populations) with replicates Pop 1 Pop 2 Randomly sample 4 individuals

More information

Applied Statistics Handbook

Applied Statistics Handbook Applied Statistics Handbook Phil Crewson Version 1. Applied Statistics Handbook Copyright 006, AcaStat Software. All rights Reserved. http://www.acastat.com Protected under U.S. Copyright and international

More information

Prentice Hall Connected Mathematics 2, 7th Grade Units 2009

Prentice Hall Connected Mathematics 2, 7th Grade Units 2009 Prentice Hall Connected Mathematics 2, 7th Grade Units 2009 Grade 7 C O R R E L A T E D T O from March 2009 Grade 7 Problem Solving Build new mathematical knowledge through problem solving. Solve problems

More information

Prentice Hall Mathematics Courses 1-3 Common Core Edition 2013

Prentice Hall Mathematics Courses 1-3 Common Core Edition 2013 A Correlation of Prentice Hall Mathematics Courses 1-3 Common Core Edition 2013 to the Topics & Lessons of Pearson A Correlation of Courses 1, 2 and 3, Common Core Introduction This document demonstrates

More information

Truman College-Mathematics Department Math 125-CD: Introductory Statistics Course Syllabus Fall 2012

Truman College-Mathematics Department Math 125-CD: Introductory Statistics Course Syllabus Fall 2012 Instructor: Dr. Abdallah Shuaibi Office #: 3816 Email: ashuaibi1@ccc.edu URL: http://faculty.ccc.edu/ashuaibi/ Phone #: (773)907-4085 Office Hours: Truman College-Mathematics Department Math 125-CD: Introductory

More information

Chicago Booth BUSINESS STATISTICS 41000 Final Exam Fall 2011

Chicago Booth BUSINESS STATISTICS 41000 Final Exam Fall 2011 Chicago Booth BUSINESS STATISTICS 41000 Final Exam Fall 2011 Name: Section: I pledge my honor that I have not violated the Honor Code Signature: This exam has 34 pages. You have 3 hours to complete this

More information

Algebra 1 Course Information

Algebra 1 Course Information Course Information Course Description: Students will study patterns, relations, and functions, and focus on the use of mathematical models to understand and analyze quantitative relationships. Through

More information

6. Methods 6.8. Methods related to outputs, Introduction

6. Methods 6.8. Methods related to outputs, Introduction 6. Methods 6.8. Methods related to outputs, Introduction In order to present the outcomes of statistical data collections to the users in a manner most users can easily understand, a variety of statistical

More information

Governors State University College of Business and Public Administration. Course: STAT 361-03 Statistics for Management I (Online Course)

Governors State University College of Business and Public Administration. Course: STAT 361-03 Statistics for Management I (Online Course) Governors State University College of Business and Public Administration Course: STAT 361-03 Statistics for Management I (Online Course) Instructor: Kevin M. Riordan, M.A. Session: Fall Semester 2011 Prerequisite:

More information

Introductory Statistics Notes

Introductory Statistics Notes Introductory Statistics Notes Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 35487-0348 Phone: (205) 348-4431 Fax: (205) 348-8648 August

More information

Glencoe. correlated to SOUTH CAROLINA MATH CURRICULUM STANDARDS GRADE 6 3-3, 5-8 8-4, 8-7 1-6, 4-9

Glencoe. correlated to SOUTH CAROLINA MATH CURRICULUM STANDARDS GRADE 6 3-3, 5-8 8-4, 8-7 1-6, 4-9 Glencoe correlated to SOUTH CAROLINA MATH CURRICULUM STANDARDS GRADE 6 STANDARDS 6-8 Number and Operations (NO) Standard I. Understand numbers, ways of representing numbers, relationships among numbers,

More information

Statistical Functions in Excel

Statistical Functions in Excel Statistical Functions in Excel There are many statistical functions in Excel. Moreover, there are other functions that are not specified as statistical functions that are helpful in some statistical analyses.

More information

Gouvernement du Québec Ministère de l Éducation, 2004 04-00811 ISBN 2-550-43541-9

Gouvernement du Québec Ministère de l Éducation, 2004 04-00811 ISBN 2-550-43541-9 Gouvernement du Québec Ministère de l Éducation, 2004 04-00811 ISBN 2-550-43541-9 Legal deposit Bibliothèque nationale du Québec, 2004 1. INTRODUCTION This Definition of the Domain for Summative Evaluation

More information

Data Mining Part 2. Data Understanding and Preparation 2.1 Data Understanding Spring 2010

Data Mining Part 2. Data Understanding and Preparation 2.1 Data Understanding Spring 2010 Data Mining Part 2. and Preparation 2.1 Spring 2010 Instructor: Dr. Masoud Yaghini Introduction Outline Introduction Measuring the Central Tendency Measuring the Dispersion of Data Graphic Displays References

More information

Course Descriptions for 7 th & 8 th Grade Mathematics

Course Descriptions for 7 th & 8 th Grade Mathematics Course Descriptions for 7 th & 8 th Grade Mathematics 7 th Grade Academic Math This course is based upon the 7 th grade PA core standards to prepare students for future algebra based understandings. The

More information

BNG 202 Biomechanics Lab. Descriptive statistics and probability distributions I

BNG 202 Biomechanics Lab. Descriptive statistics and probability distributions I BNG 202 Biomechanics Lab Descriptive statistics and probability distributions I Overview The overall goal of this short course in statistics is to provide an introduction to descriptive and inferential

More information

Overview... 2. Accounting for Business (MCD1010)... 3. Introductory Mathematics for Business (MCD1550)... 4. Introductory Economics (MCD1690)...

Overview... 2. Accounting for Business (MCD1010)... 3. Introductory Mathematics for Business (MCD1550)... 4. Introductory Economics (MCD1690)... Unit Guide Diploma of Business Contents Overview... 2 Accounting for Business (MCD1010)... 3 Introductory Mathematics for Business (MCD1550)... 4 Introductory Economics (MCD1690)... 5 Introduction to Management

More information

Probability and Statistics

Probability and Statistics CHAPTER 2: RANDOM VARIABLES AND ASSOCIATED FUNCTIONS 2b - 0 Probability and Statistics Kristel Van Steen, PhD 2 Montefiore Institute - Systems and Modeling GIGA - Bioinformatics ULg kristel.vansteen@ulg.ac.be

More information

South Carolina College- and Career-Ready (SCCCR) Probability and Statistics

South Carolina College- and Career-Ready (SCCCR) Probability and Statistics South Carolina College- and Career-Ready (SCCCR) Probability and Statistics South Carolina College- and Career-Ready Mathematical Process Standards The South Carolina College- and Career-Ready (SCCCR)

More information

The right edge of the box is the third quartile, Q 3, which is the median of the data values above the median. Maximum Median

The right edge of the box is the third quartile, Q 3, which is the median of the data values above the median. Maximum Median CONDENSED LESSON 2.1 Box Plots In this lesson you will create and interpret box plots for sets of data use the interquartile range (IQR) to identify potential outliers and graph them on a modified box

More information

Name of the module: Multivariate biostatistics and SPSS Number of module: 471-8-4081

Name of the module: Multivariate biostatistics and SPSS Number of module: 471-8-4081 Name of the module: Multivariate biostatistics and SPSS Number of module: 471-8-4081 BGU Credits: 1.5 ECTS credits: Academic year: 4 th Semester: 15 days during fall semester Hours of instruction: 8:00-17:00

More information

Utah Core Curriculum for Mathematics

Utah Core Curriculum for Mathematics Core Curriculum for Mathematics correlated to correlated to 2005 Chapter 1 (pp. 2 57) Variables, Expressions, and Integers Lesson 1.1 (pp. 5 9) Expressions and Variables 2.2.1 Evaluate algebraic expressions

More information

Statistics 104: Section 6!

Statistics 104: Section 6! Page 1 Statistics 104: Section 6! TF: Deirdre (say: Dear-dra) Bloome Email: dbloome@fas.harvard.edu Section Times Thursday 2pm-3pm in SC 109, Thursday 5pm-6pm in SC 705 Office Hours: Thursday 6pm-7pm SC

More information

Statistical Foundations: Measures of Location and Central Tendency and Summation and Expectation

Statistical Foundations: Measures of Location and Central Tendency and Summation and Expectation Statistical Foundations: and Central Tendency and and Lecture 4 September 5, 2006 Psychology 790 Lecture #4-9/05/2006 Slide 1 of 26 Today s Lecture Today s Lecture Where this Fits central tendency/location

More information

Course Syllabus STA301 Statistics for Economics and Business (6 ECTS credits)

Course Syllabus STA301 Statistics for Economics and Business (6 ECTS credits) Course Syllabus STA301 Statistics for Economics and Business (6 ECTS credits) Instructor: Luc Hens Telephone: +32 2 629 11 92 e-mail: luc.hens@vub.ac.be Web site: http://homepages.vub.ac.be/~lmahens/ Course

More information

DATA INTERPRETATION AND STATISTICS

DATA INTERPRETATION AND STATISTICS PholC60 September 001 DATA INTERPRETATION AND STATISTICS Books A easy and systematic introductory text is Essentials of Medical Statistics by Betty Kirkwood, published by Blackwell at about 14. DESCRIPTIVE

More information