MAT 12O ELEMENTARY STATISTICS I

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "MAT 12O ELEMENTARY STATISTICS I"

Transcription

1 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: MAT 096 or Waiver Catalog Description: This course serves as a study of fundamental concepts and computational techniques of elementary statistics. Among the topics studied are: measures of central tendency, standard deviation, percentiles, statistical graphs, binomial and normal distributions, probability, correlation, regression, confidence intervals, and hypothesis testing. A statistical software package will be used to obtain basic sample statistics, to simulate fundamental theorems, study correlation and regression, and to assist with hypothesis testing. Purposes and Goals: Upon the completion of this course, students should be able to: 1. Perform basic statistical analyses of real-life data sets. They should be able to use standard statistical software on these data. 2. Transfer to four-year colleges and universities and pursue upper division courses and academic programs. 3. Review statistical analyses that involve the statistical procedures and methods presented in this course. 4. Communicate statistical ideas and analyses to audiences who may have little or no knowledge of statistics. Course Syllabus 1

2 Instructional Objectives: The instructor is expected to: 1. Explain the nature of statistics to the students, illustrate the key role statistics has in the technical aspect of life as well as its everyday applicability, and introduce the basic ideas and concerns about the processes used to obtain sample data. 2. Present how data sets can be organized or summarized through the use of tables, graphical displays, and descriptive measures. 3. Introduce the basic concepts of probability and the rules that apply to the probability of both simple and compound events. 4. Introduce the binomial, normal, and Student s t distributions and explain how they can be applied to estimate population parameters and conduct hypothesis tests. Instructor should clarify the assumptions and limitations of the statistical techniques that are based on these distributions. 5. Introduce the concepts of correlation and regression, explain how to use them to study bivariate data, and discuss how to use the regression equation to make predictions. 6. Explain how to use a statistical computer software package to organize, summarize, and analyze data sets in applied settings. 7. Guide students in reviewing statistical articles and in communicating statistical ideas and analyses. Performance Objectives: As a result of successful completion of this course, students should be able to: 1. Classify statistical studies as either descriptive or inferential. 2. Distinguish between populations and samples in an inferential study, compare different sampling methods, and describe possible sample biases. 3. Classify variables as either qualitative or quantitative, and discrete or continuous. 4. Create and interpret frequency distributions and graphs representing data sets. Course Syllabus 2

3 5. Obtain and interpret descriptive measures of univariate data sets for both samples and populations. Be able to distinguish between a parameter and a statistic. 6. Recognize and apply the basic definitions and rules of probability theory. 7. Examine binomial, normal, and Student s t random variables and their probability distributions. Be able to analyze a data set and determine which probability distribution is the best model to fit the data set. 8. Determine the sampling distribution of the mean for either a normally distributed variable or a variable that is not normally distributed, and state and apply the central limit theorem. 9. Use the normal or the Student s t-distribution to estimate population parameters and conduct hypothesis tests. 10. Utilize a statistical computer software package to organize and summarize information clearly and effectively, determine and compare descriptive measures of data sets, and use them to analyze data sets. 11. Utilize a statistical computer software package to simulate experiments in probability, simulate the sampling distribution of the mean, and illustrate the central limit theorem. 12. Use a statistical computer software package to obtain a one-sample t-confidence interval and perform a one-sample t-test for a population mean. 13. Use a statistical computer software package to obtain linear regression equation and compute linear correlation coefficient for bivariate data. 14. Read and interpret the results of linear correlation and regression presented in the output obtained from a statistical computer software package. Attendance/Lateness Policy Students are expected to attend all class meetings. Students are responsible for all information, material, and assignments covered in class regardless of class attendance. As per college policy, students who have more than 8 hours of unexcused absences don t meet the attendance requirement for passing the course. Students who miss more than 50% of the class period might Course Syllabus 3

4 be marked absent. Students who miss more than 15 minutes of the class period, might be marked late. Three lateness marks count as one unexcused absence. Students should consult the college catalog to find out the terms and conditions under which a WU, and incomplete, or an F grade may be given by an instructor. Course Materials: Textbook + Online Platform 1. Textbook (package available at the college bookstore ONLY) STATISTICS: INFORMED DECISIONS USING DATA PACKAGE FOR LAGUARDIA COMMUNITY COLLEGE Michael Sullivan, III; Pearson Learning Solutions (Copyright 2016) ISBN-10: ISBN-13: Online Course Platform (personal access code is included with a textbook package) MyStatLab on including Interactive Multimedia etext Online HW, Quizzes and Tests Study Plan/ Tutorial Integrated Algebra Skills Review SPSS technology tutorial videos Gradebook Technical Requirements: Access to a computer with text-editing, spreadsheet capabilities, and an internet connection. Access to a software package with Statistical functions and features, e.g., SPSS (available on Campus) or Excel. Access to a scientific calculator for in-class work, quizzes, exams, and homework. Optional Resources: SPSS 23 GradPak: (a 6-month rental for the SPSS program for your own computer, costing $41) downloadable from StudentDiscounts.com Course Syllabus 4

5 Course Content Outline The timeline below is a suggestion and the course pacing may be adjusted by your instructor. Symbol refers to the SPSS technology tutorial videos linked to the Tools for Success tab of the toolbar menu on MyStatLab homepage. Additional technology resources will be posted on the MEC website and indicated by your instructor as needed. HOUR TOPIC SECTION PAGE MyStatLab Data Collection (Chapter 1) 1 2 Introduction to Practice of Statistics Section 1.1 HW Section 1.3 HW Population, Sample, Individual, Types of Variables, Parameter vs. Statistic 1.3, Section 1.4 HW Section 1.5 HW Sampling Methods Chapter 1 Review Quiz Sources of Bias Chapter 1 Review HW 3 Summarizing Data in Tables and Graphs (Chapter 2) Organizing Qualitative data Section 2.1 HW Frequency Distribution, Relative Frequency Distribution, Bar Graphs, Pareto Chart, Comparing Two Data Sets, Pie Charts LAB 1 Introduction to SPSS Opening /creating/editing SPSS data file Introduction to SPSS Data Manipulation: Sorting and Sampling (optional) Sampling (optional) 5 Organizing Quantitative Data Section 2.2 HW Frequency Distributions and Histogram for discrete and continuous data, Stem-and-leaf Plot, Dot Plot, Shape of a distribution Graphical Misrepresentation of Data Section 2.4 HW Chapter 2 Review Quiz Chapter 2 Review HW 6 Numerically Summarizing Data (Chapter 3) Measures of Central Tendency (raw data) Section 3.1 HW Mean, Median, Mode, using mean, median and mode to identify the shape of a distribution Course Syllabus 5

6 7 Measures of Dispersion (raw data) LAB 2 Basic Concepts, Range, Standard Deviation and Variance for sample and population, Comparing Variation, Interpreting Standard Deviation, Empirical Rule Using SPSS to organize and Summarize Data: Obtain frequency distributions, graphs and charts and descriptive statistics 9 Measures of Central Tendency and Dispersion (grouped data) Mean of a variable from grouped data, Weighted Mean Section 3.2 HW Descriptive Statistics, Histogram and Boxplot, Assessing Normality etc Section 3.3 HW 10 Measures of Position and Outliers Section 3.4 HW Z-score, Quartiles and Percentiles, Outliers 11 The Five-Number Summary and Boxplots Section 3.5 HW Chapter 3 Review Quiz Chapter 3 Review HW LAB 3 More SPSS Graphs and Charts: Stemand-Leaf Plot, Quartiles, Box-Plot, comparing data Descriptive Statistics, Histogram and Boxplot, Assessing Normality etc. 13 Review for Instructors Test #1 (Chapters 1, 2 and3) 14 Instructors Test #1 15 Describing the Relation between Two Variables (Chapter 4) Scatter Diagram and Correlation: Section 4.1 HW Scatter plot: draw and interpret, Pearson s Linear Correlation Coefficient: Meaning and Properties Regression Line /Equation: Section 4.2 HW Interpret Coefficients, Use for Prediction Contingency Tables and Association (optional) Section 4.4 HW Chapter 4 Review Quiz Chapter 4 Review HW Course Syllabus 6

7 LAB 4 Use SPSS to make a Scatter-plot with a Regression Line, produce and understand Linear Correlation and Regression Output 17 Probability and Probability Distributions: (Chapter 5) Probability Rules Empirical and Classical methods The Addition Rule & Complements Independence and the Multiplication Rule Conditional Probability and the General Multiplication Rule LAB 5 Use SPSS to Simulate Randomness Simulating Data based on Probabilities 21 Discrete Probability Distributions (Chapter 6) Discrete Random Variables A Discrete Probability Distribution Table, Probability Histogram Compute mean of Discrete Random Variable Interpret the mean as Expected Value Scatter-plot Regression and Residual Plots Correlation Section 5.1 HW Section 5.2 HW Section 5.3 HW Section 5.4 HW Chapter 5 Review Quiz Chapter 5 Review HW. Sampling (if not covered in Lab 1) Generating Random Numbers Section 6.1 HW Binomial Probability Distributions Criteria for a binomial probability experiment, Computing Binomial Probability: Table and Formula LAB 6 Simulate Binomial Random Variable, obtain Table of Binomial Probabilities, compute descriptive measures from a Probability Distributions Section 6.2 HW Course Syllabus 7

8 25 Binomial Probability Distributions Mean, Variance, and Standard Deviation of a Binomial Random Variable, Histogram, Check for Unusual Results 26 The Normal Probability Distributions (Chapter 7) Properties of the Normal Distribution Graph and Properties of the Normal Curve Area as Probability 27 Applications of the Normal LAB 7 Distributions The Standard Normal Distribution Using z-table: Finding Probabilities Given z Scores, Finding z Scores for given Areas Generate and study shape of Binomial Distribution bar graph, as the value of p changes 29 Applications of the Normal Distributions Finding Probabilities for given Values, Finding Values corresponding to Probabilities 30 Review for Test #2 31 Test #2 LAB 8 Simulating normal random variable, finding Probabilities for given scores, finding scores for given probabilities, Determining Normality (Q-Q Plot) 33 Sampling Distributions (Chapter 8) Distribution of the Sample Mean Sampling distribution, Mean and Standard Deviation of the Sampling Distribution, The Central Limit Theorem , Chapter 6 Review Quiz Chapter 6 Review HW Section 7.1 HW Section 7.2 HW Section 7.2 HW 393 Chapter 7 Review Quiz Chapter 7 Review HW Finding Inverse Normality (Finding z-scores Given an Area) and the Area under the Normal Curve Section 8.1 HW Chapter 8 Review Quiz Chapter 8 Review HW Course Syllabus 8

9 34 Estimating the Value of a Parameter (Chapter 9) Estimating a Population Mean Point Estimates, Confidence Intervals and their Interpretations, Meaning of Margin of Error, Constructing CI with σ known, Determining Sample Size Required 35 Estimating a Population Mean Properties of Student s t-distribution Finding t-values LAB 9 Use SPSS to explore Sampling Distribution of the mean for cases where population is Normal, and cases where population is not Normal. Access normality using Q-Q plots. 37 Estimating a Population Mean (σ Unknown) Construct and Interpret a Confidence Interval using Student s t-distribution Hypothesis Test Regarding a Parameter (Chapter 10) The Language of Hypothesis Testing Null and Alternate Hypothesis, Type I and Type II errors, Conclusions to Hypothesis Tests LAB 10 Estimating a Population Mean with SPSS using Confidence Intervals Hypothesis Testing about Population Mean, Hypothesis Tests for a Population Mean Traditional & P-value Methods ( σ unknown) σ -known case is optional Significance: statistical vs. practical LAB 11 Review for Test #3 45 Test # Final Examination Review Section 9.2 HW Descriptive Statistics,,Assessing Normality and Generating Confidence Intervals Section 9.2 HW Chapter 9 Review Quiz Chapter 9 Review HW Section 10.1 HW Hypothesis test for One Sample Mean and Associated Confidence Intervals Section 10.3 HW Chapter 10 Review Quiz Chapter 10 ReviewHW Course Syllabus 9

10 Data Analysis Projects and Activities Instructors will assign and evaluate at least 3 mini-projects or one course-long master project. Students should prepare a project report for each project assigned. The report must include the method(s) used for the data analysis and the interpretations of the numerical results. Some suggested projects from the course package are listed below. Use of SPSS or other professional software package is recommended for data analysis projects. Topic Chapter Page Exercise # Understanding Data Collection 1 62 Making an Informed Decision: What college should I attend (1-3) Organizing Qualitative Data Organizing Quantitative Data Consumer Reports: Consumer Reports Rates Treadmills Chap. 2: Case study (The Day the Sky Roared) Measure of Central Tendency Measure of Dispersion Five number Summary and Box-plot Consumer Reports: Basement Waterproofing Making an Informed Decision: What car should I buy Scatter Diagram and Correlation Least Square Regression Consumer Reports: Fit to Drink (a d) Making an Informed Decision:relationship between variables on the World scale Probability Chap. 5: Case study (The Case of the Body in the Bag) The Binomial Probability Distribution Making an Informed Decision: Should we convict? Applications of Normal Distribution Consumer Reports: Sunscreens Chap. 7: Case study (The Tale of Blood Chemistry and Health) Estimating The Value of a Parameter Consumer Reports: Consumer Reports Tests Tires Hypothesis Testing Chap. 10: Case study (How old is Stonehenge) A sample course-long master project (Data Analyses Project: Historical temperature Trends) is available on MEC website at bb Course Grading: HW Assignments, Quizzes 10% Data Analyses Projects and Activities 15% 3 Instructor Exams 45% Departmental Final Examination 30% Course Syllabus 10

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

COURSE OUTLINE. Course Number Course Title Credits MAT201 Probability and Statistics for Science and Engineering 4. Co- or Pre-requisite

COURSE OUTLINE. Course Number Course Title Credits MAT201 Probability and Statistics for Science and Engineering 4. Co- or Pre-requisite COURSE OUTLINE Course Number Course Title Credits MAT201 Probability and Statistics for Science and Engineering 4 Hours: Lecture/Lab/Other 4 Lecture Co- or Pre-requisite MAT151 or MAT149 with a minimum

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

AP Statistics: Syllabus 3

AP Statistics: Syllabus 3 AP Statistics: Syllabus 3 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

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

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

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

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

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

Minitab Guide. This packet contains: A Friendly Guide to Minitab. Minitab Step-By-Step

Minitab Guide. This packet contains: A Friendly Guide to Minitab. Minitab Step-By-Step Minitab Guide This packet contains: A Friendly Guide to Minitab An introduction to Minitab; including basic Minitab functions, how to create sets of data, and how to create and edit graphs of different

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

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

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

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

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

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

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

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

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

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

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

STATS APPLIED STATISTICS Spring 2016

STATS APPLIED STATISTICS Spring 2016 STATS 250 - APPLIED STATISTICS Spring 2016 Instructor Information: Instructor: Professor Alfonso Taboada Email: alfonso@suffolk.es Phone: 91-533-5935 Ext.136 Office: Top floor, Math & Business Office Office

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

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

Math 1342 STATISTICS Course Syllabus

Math 1342 STATISTICS Course Syllabus Math 1342 STATISTICS Course Syllabus Instructor: Mahmoud Basharat; E-mail: Please use email within Eagle-Online Alternating email: basharatah@hotmail.com or mahmoud.basharat@hccs.edu. (Please use only

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

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

Lean Six Sigma Training/Certification Book: Volume 1

Lean Six Sigma Training/Certification Book: Volume 1 Lean Six Sigma Training/Certification Book: Volume 1 Six Sigma Quality: Concepts & Cases Volume I (Statistical Tools in Six Sigma DMAIC process with MINITAB Applications Chapter 1 Introduction to Six Sigma,

More information

UNIVERSITY of MASSACHUSETTS DARTMOUTH Charlton College of Business Decision and Information Sciences Fall 2010

UNIVERSITY of MASSACHUSETTS DARTMOUTH Charlton College of Business Decision and Information Sciences Fall 2010 UNIVERSITY of MASSACHUSETTS DARTMOUTH Charlton College of Business Decision and Information Sciences Fall 2010 COURSE: POM 500 Statistical Analysis, ONLINE EDITION, Fall 2010 Prerequisite: Finite Math

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

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

Chapter 2: Exploring Data with Graphs and Numerical Summaries. Graphical Measures- Graphs are used to describe the shape of a data set.

Chapter 2: Exploring Data with Graphs and Numerical Summaries. Graphical Measures- Graphs are used to describe the shape of a data set. Page 1 of 16 Chapter 2: Exploring Data with Graphs and Numerical Summaries Graphical Measures- Graphs are used to describe the shape of a data set. Section 1: Types of Variables In general, variable can

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

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

Descriptive Statistics. Frequency Distributions and Their Graphs 2.1. Frequency Distributions. Chapter 2

Descriptive Statistics. Frequency Distributions and Their Graphs 2.1. Frequency Distributions. Chapter 2 Chapter Descriptive Statistics.1 Frequency Distributions and Their Graphs Frequency Distributions A frequency distribution is a table that shows classes or intervals of data with a count of the number

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

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

F. Farrokhyar, MPhil, PhD, PDoc

F. Farrokhyar, MPhil, PhD, PDoc Learning objectives Descriptive Statistics F. Farrokhyar, MPhil, PhD, PDoc To recognize different types of variables To learn how to appropriately explore your data How to display data using graphs How

More information

STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance

STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance Principles of Statistics STA-201-TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis

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

Simple Linear Regression in SPSS STAT 314

Simple Linear Regression in SPSS STAT 314 Simple Linear Regression in SPSS STAT 314 1. Ten Corvettes between 1 and 6 years old were randomly selected from last year s sales records in Virginia Beach, Virginia. The following data were obtained,

More information

THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS. Fall 2013

THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS. Fall 2013 THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING 1 COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS Fall 2013 & Danice B. Greer, Ph.D., RN, BC dgreer@uttyler.edu Office BRB 1115 (903) 565-5766

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

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

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

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

International College of Economics and Finance Syllabus Probability Theory and Introductory Statistics International College of Economics and Finance Syllabus Probability Theory and Introductory Statistics Lecturer: Mikhail Zhitlukhin. 1. Course description Probability Theory and Introductory Statistics

More information

MAT 282 STATISTICS 3 cr. (3-0) (online sections)

MAT 282 STATISTICS 3 cr. (3-0) (online sections) JOHN A. LOGAN COLLEGE J. Dethrow SM 11 MAT 282 STATISTICS 3 cr. (3-0) (online sections) COURSE DESCRIPTION: MAT 282 is designed to meet the needs of students requiring a statistics course with a college

More information

Chapter 15 Multiple Choice Questions (The answers are provided after the last question.)

Chapter 15 Multiple Choice Questions (The answers are provided after the last question.) Chapter 15 Multiple Choice Questions (The answers are provided after the last question.) 1. What is the median of the following set of scores? 18, 6, 12, 10, 14? a. 10 b. 14 c. 18 d. 12 2. Approximately

More information

Foundation of Quantitative Data Analysis

Foundation of Quantitative Data Analysis Foundation of Quantitative Data Analysis Part 1: Data manipulation and descriptive statistics with SPSS/Excel HSRS #10 - October 17, 2013 Reference : A. Aczel, Complete Business Statistics. Chapters 1

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

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

Using SPSS, Chapter 2: Descriptive Statistics

Using SPSS, Chapter 2: Descriptive Statistics 1 Using SPSS, Chapter 2: Descriptive Statistics Chapters 2.1 & 2.2 Descriptive Statistics 2 Mean, Standard Deviation, Variance, Range, Minimum, Maximum 2 Mean, Median, Mode, Standard Deviation, Variance,

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

Chapter 3: Data Description Numerical Methods

Chapter 3: Data Description Numerical Methods Chapter 3: Data Description Numerical Methods Learning Objectives Upon successful completion of Chapter 3, you will be able to: Summarize data using measures of central tendency, such as the mean, median,

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

Statistics revision. Dr. Inna Namestnikova. Statistics revision p. 1/8

Statistics revision. Dr. Inna Namestnikova. Statistics revision p. 1/8 Statistics revision Dr. Inna Namestnikova inna.namestnikova@brunel.ac.uk Statistics revision p. 1/8 Introduction Statistics is the science of collecting, analyzing and drawing conclusions from data. Statistics

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

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

Chapter 13 Introduction to Linear Regression and Correlation Analysis

Chapter 13 Introduction to Linear Regression and Correlation Analysis Chapter 3 Student Lecture Notes 3- Chapter 3 Introduction to Linear Regression and Correlation Analsis Fall 2006 Fundamentals of Business Statistics Chapter Goals To understand the methods for displaing

More information

Desciptive Statistics Qualitative data Quantitative data Graphical methods Numerical methods

Desciptive Statistics Qualitative data Quantitative data Graphical methods Numerical methods Desciptive Statistics Qualitative data Quantitative data Graphical methods Numerical methods Qualitative data Data are classified in categories Non numerical (although may be numerically codified) Elements

More information

Objective of the course The main objective is to teach students how to conduct quantitative data analysis in SPSS for research purposes.

Objective of the course The main objective is to teach students how to conduct quantitative data analysis in SPSS for research purposes. COURSE DESCRIPTION The course Data Analysis with SPSS was especially designed for students of Master s Programme System and Software Engineering. The content and teaching methods of the course correspond

More information

INTERNATIONAL BACCALAUREATE (IB) MATH STANDARD LEVEL, YEARS 1 AND 2 Grades 11, 12

INTERNATIONAL BACCALAUREATE (IB) MATH STANDARD LEVEL, YEARS 1 AND 2 Grades 11, 12 INTERNATIONAL BACCALAUREATE (IB) MATH STANDARD LEVEL, YEARS 1 AND 2 Grades 11, 12 Unit of Credit: 1 Year for Year 1 and 1 Year for Year 2 Pre-requisite: Algebra 2 for Year 1 IB Math Standard Level Year

More information

Statistics with Aviation Applications Math 211 Mode of Delivery Lecture Blended Course Syllabus

Statistics with Aviation Applications Math 211 Mode of Delivery Lecture Blended Course Syllabus Statistics with Aviation Applications Math 211 Mode of Delivery Lecture Blended Course Syllabus Credit Hours: 3 Credits Academic Term: Term 4: 23 March 2015 24 May 2015 Meetings: Thurs 18:00-22:00 26 Mar;

More information

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE STATISTICS The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE VS. INFERENTIAL STATISTICS Descriptive To organize,

More information

Math Chapter 2 review

Math Chapter 2 review Math 116 - Chapter 2 review Name Provide an appropriate response. 1) Suppose that a data set has a minimum value of 28 and a max of 73 and that you want 5 classes. Explain how to find the class width for

More information

Study Guide for the Final Exam

Study Guide for the Final Exam Study Guide for the Final Exam When studying, remember that the computational portion of the exam will only involve new material (covered after the second midterm), that material from Exam 1 will make

More information

Inferential Statistics

Inferential Statistics Inferential Statistics Sampling and the normal distribution Z-scores Confidence levels and intervals Hypothesis testing Commonly used statistical methods Inferential Statistics Descriptive statistics are

More information

MAT 120 Probability & Statistics Mathematics

MAT 120 Probability & Statistics Mathematics MAT 120 Probability & Statistics Mathematics Catalog Course Description: This course includes the following topics: introductory probability and statistics, including organization of data, sample space

More information

An introduction to using Microsoft Excel for quantitative data analysis

An introduction to using Microsoft Excel for quantitative data analysis Contents An introduction to using Microsoft Excel for quantitative data analysis 1 Introduction... 1 2 Why use Excel?... 2 3 Quantitative data analysis tools in Excel... 3 4 Entering your data... 6 5 Preparing

More information

096 Professional Readiness Examination (Mathematics)

096 Professional Readiness Examination (Mathematics) 096 Professional Readiness Examination (Mathematics) Effective after October 1, 2013 MI-SG-FLD096M-02 TABLE OF CONTENTS PART 1: General Information About the MTTC Program and Test Preparation OVERVIEW

More information

Find the median temperature. A) 33 F B) 59 F C) 51 F D) 67 F Answer: B

Find the median temperature. A) 33 F B) 59 F C) 51 F D) 67 F Answer: B Review for TEST 2 STA 2023 FALL 2013 Name Find the mean of the data summarized in the given frequency distribution. 1) A company had 80 employees whose salaries are summarized in the frequency distribution

More information

Stats Review Chapters 3-4

Stats Review Chapters 3-4 Stats Review Chapters 3-4 Created by Teri Johnson Math Coordinator, Mary Stangler Center for Academic Success Examples are taken from Statistics 4 E by Michael Sullivan, III And the corresponding Test

More information

Unit 21 Student s t Distribution in Hypotheses Testing

Unit 21 Student s t Distribution in Hypotheses Testing Unit 21 Student s t Distribution in Hypotheses Testing Objectives: To understand the difference between the standard normal distribution and the Student's t distributions To understand the difference between

More information

Good luck! BUSINESS STATISTICS FINAL EXAM INSTRUCTIONS. Name:

Good luck! BUSINESS STATISTICS FINAL EXAM INSTRUCTIONS. Name: Glo bal Leadership M BA BUSINESS STATISTICS FINAL EXAM Name: INSTRUCTIONS 1. Do not open this exam until instructed to do so. 2. Be sure to fill in your name before starting the exam. 3. You have two hours

More information

MATE 601 Physics, Chemistry & Statistics of Heat for Middle School Teachers

MATE 601 Physics, Chemistry & Statistics of Heat for Middle School Teachers MATE 601 Physics, Chemistry & Statistics of Heat for Middle School Teachers Instructors Carla Comeau, Pittsfield Public Schools, STEM Coordinator Alexis Dekel, Head of Math department, BART Dr. Adrienne

More information

Business Statistics MATH 222. Eagle Vision Home. Course Syllabus

Business Statistics MATH 222. Eagle Vision Home. Course Syllabus Business Statistics MATH 222 EagleVision Home Course Syllabus Credit Hours: 3 Credits Academic Term: March 2012 [March 19, 2012 May 20, 2012] Meetings: Location: Instructor: Office Hours: Monday/Wednesday,

More information

Lecture 1: Review and Exploratory Data Analysis (EDA)

Lecture 1: Review and Exploratory Data Analysis (EDA) Lecture 1: Review and Exploratory Data Analysis (EDA) Sandy Eckel seckel@jhsph.edu Department of Biostatistics, The Johns Hopkins University, Baltimore USA 21 April 2008 1 / 40 Course Information I Course

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

03 The full syllabus. 03 The full syllabus continued. For more information visit www.cimaglobal.com PAPER C03 FUNDAMENTALS OF BUSINESS MATHEMATICS

03 The full syllabus. 03 The full syllabus continued. For more information visit www.cimaglobal.com PAPER C03 FUNDAMENTALS OF BUSINESS MATHEMATICS 0 The full syllabus 0 The full syllabus continued PAPER C0 FUNDAMENTALS OF BUSINESS MATHEMATICS Syllabus overview This paper primarily deals with the tools and techniques to understand the mathematics

More information

SPSS for Exploratory Data Analysis Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav)

SPSS for Exploratory Data Analysis Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav) Data used in this guide: studentp.sav (http://people.ysu.edu/~gchang/stat/studentp.sav) Organize and Display One Quantitative Variable (Descriptive Statistics, Boxplot & Histogram) 1. Move the mouse pointer

More information

, then the form of the model is given by: which comprises a deterministic component involving the three regression coefficients (

, then the form of the model is given by: which comprises a deterministic component involving the three regression coefficients ( Multiple regression Introduction Multiple regression is a logical extension of the principles of simple linear regression to situations in which there are several predictor variables. For instance if we

More information

2. Describing Data. We consider 1. Graphical methods 2. Numerical methods 1 / 56

2. Describing Data. We consider 1. Graphical methods 2. Numerical methods 1 / 56 2. Describing Data We consider 1. Graphical methods 2. Numerical methods 1 / 56 General Use of Graphical and Numerical Methods Graphical methods can be used to visually and qualitatively present data and

More information

Versions 1a Page 1 of 17

Versions 1a Page 1 of 17 Note to Students: This practice exam is intended to give you an idea of the type of questions the instructor asks and the approximate length of the exam. It does NOT indicate the exact questions or the

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

AP Statistics 2001 Solutions and Scoring Guidelines

AP Statistics 2001 Solutions and Scoring Guidelines AP Statistics 2001 Solutions and Scoring Guidelines The materials included in these files are intended for non-commercial use by AP teachers for course and exam preparation; permission for any other use

More information

STA2023 Introduction to Statistics Spring 2013. Class Website: http://www.hccfl.edu/faculty-info/jdenson3/sta2023-introduction-to-statistics.

STA2023 Introduction to Statistics Spring 2013. Class Website: http://www.hccfl.edu/faculty-info/jdenson3/sta2023-introduction-to-statistics. Instructor: Jennifer Denson STA2023 Introduction to Statistics Spring 2013 Class Website: http://www.hccfl.edu/faculty-info/jdenson3/sta2023-introduction-to-statistics.aspx Contact Information: Email:

More information

Biostatistics Lab Notes

Biostatistics Lab Notes Biostatistics Lab Notes Page 1 Lab 1: Measurement and Sampling Biostatistics Lab Notes Because we used a chance mechanism to select our sample, each sample will differ. My data set (GerstmanB.sav), looks

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

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Final Exam Review MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) A researcher for an airline interviews all of the passengers on five randomly

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

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

Diagrams and Graphs of Statistical Data

Diagrams and Graphs of Statistical Data Diagrams and Graphs of Statistical Data One of the most effective and interesting alternative way in which a statistical data may be presented is through diagrams and graphs. There are several ways in

More information

STAT 200: Course Aims and Objectives

STAT 200: Course Aims and Objectives STAT 200: Course Aims and Objectives Attitudinal aims In addition to specific learning outcomes, the course aims to shape the attitudes of learners regarding the field of Statistics. Specifically, the

More information

The University of Texas at Austin School of Social Work SOCIAL WORK STATISTICS

The University of Texas at Austin School of Social Work SOCIAL WORK STATISTICS 1 The University of Texas at Austin School of Social Work SOCIAL WORK STATISTICS Course Number: SW 318 Instructor: Michael Bergman, Ph.D. Unique Number: 65190 Office Number: SSW 1.214 (IT Classroom) Semester:

More information

Data Analysis: Describing Data - Descriptive Statistics

Data Analysis: Describing Data - Descriptive Statistics WHAT IT IS Return to Table of ontents Descriptive statistics include the numbers, tables, charts, and graphs used to describe, organize, summarize, and present raw data. Descriptive statistics are most

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

BIOSTATISTICS QUIZ ANSWERS

BIOSTATISTICS QUIZ ANSWERS BIOSTATISTICS QUIZ ANSWERS 1. When you read scientific literature, do you know whether the statistical tests that were used were appropriate and why they were used? a. Always b. Mostly c. Rarely d. Never

More information

90872 - Using R for Policy Data Analysis (6 units)

90872 - Using R for Policy Data Analysis (6 units) Page 1 of 7 90872 - Using R for Policy Data Analysis (6 units) Adjunct Professor: M William Sermons, PhD msermons@andrew.cmu.edu Work: (202) 349-1851 Mobile: (301) 499-5018 Carnegie Mellon University Heinz

More information

A Guide for a Selection of SPSS Functions

A Guide for a Selection of SPSS Functions A Guide for a Selection of SPSS Functions IBM SPSS Statistics 19 Compiled by Beth Gaedy, Math Specialist, Viterbo University - 2012 Using documents prepared by Drs. Sheldon Lee, Marcus Saegrove, Jennifer

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