Adapting to Different Audiences Chris Lowery and Bill Miller Georgia College & State University.

Slides:

Advertisements

Similar presentations

Using Technology to Engage Students and Enhance Learning Roxy Peck Cal Poly, San Luis Obispo

Advertisements

Inferences based on TWO samples

Implications of Big Data for Statistics Instruction Mark L. Berenson Montclair State University MSMESB Mini-Conference DSI - Baltimore November 17, 2013.

Spreadsheet Analytics

Islamic University in Gaza Faculty of commerce Business Administration Department (BUSE 4302) Operations Research Instructor: Hani Abuamer Office Hours:

Programme in Statistics (Courses and Contents). Elementary Probability and Statistics (I) 3(2+1)Stat. 101 College of Science, Computer Science, Education.

CSE 221: Probabilistic Analysis of Computer Systems Topics covered: Statistical inference (Sec. )

CSE 221: Probabilistic Analysis of Computer Systems Topics covered: Statistical inference.

Overview of STAT 270 Ch 1-9 of Devore + Various Applications.

Population Proportion The fraction of values in a population which have a specific attribute p = Population proportion X = Number of items having the attribute.

Statistics for the Social Sciences Psychology 340 Spring 2005 Course Review.

Teaching Statistics Methods for Biology 1. Outline About stat 503 Students Course set up – Lecture – Project Challenges Teaching approach – Project design.

Statistics 501 Methods of Applies Statistics Using MINITAB Fall 2012 TuTh 11:15AM-12:30PM Rm219 Professor H. K. Hsieh (“Shay”)

Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 12 Analyzing the Association Between Quantitative Variables: Regression Analysis Section.

Trying to Give Business Students What They Need for Their Future Bob Andrews Virginia Commonwealth University.

Business Analytics at LSSU C. Christopher Lee Associate Professor of Management Business Analytics at LSSU Presented by C. Christopher Lee Associate Professor.

Department of Business Information & Analytics MSMESB: Experience with Adding Analytics to the Academic Program Kellie Keeling University of Denver.

Using Lock5 Statistics: Unlocking the Power of Data

Introduction to Statistical Inference Probability & Statistics April 2014.

Math Stat Course: Making Incremental Changes Mary Parker University of Texas at Austin.

Statistics: Unlocking the Power of Data Lock 5 Afternoon Session Using Lock5 Statistics: Unlocking the Power of Data Patti Frazer Lock University of Kentucky.

Institute for Statistics and Econometrics Economics Department Humboldt University of Berlin Spandauer Straße Berlin Germany CONNECTED TEACHING.

Confidence Intervals for Means. point estimate – using a single value (or point) to approximate a population parameter. –the sample mean is the best point.

1 - 1 Module 1: Introduction This module describes the purpose of the course and the general approach followed for addressing this purpose. Reviewed 15.

Advanced Higher Statistics Data Analysis and Modelling Hypothesis Testing Statistical Inference AH.

Click to edit Master text styles Second level Third level Fourth level Fifth level Course Introduction.

Part 0 -- Introduction Statistical Inference and Regression Analysis: Stat-GB , C Professor William Greene Stern School of Business IOMS.

Quantitative Methods in Finance (FINA 514/614) Assoc.Prof.Dr. Salih KATIRCIOGLU (Ph.D in Economic Development and International Economics)

Highlighting Standards for Mathematical Practice in an Intro Stats Course by Fides Ushe Springfield College, MA.

Determination of Sample Size: A Review of Statistical Theory

Implementing a Randomization-Based Curriculum for Introductory Statistics Robin H. Lock, Burry Professor of Statistics St. Lawrence University Breakout.

1 BA 275 Quantitative Business Methods Quiz #2 Sampling Distribution of a Statistic Statistical Inference: Confidence Interval Estimation Introduction.

Course Outline Presentation Reference Course Outline for MTS-202 (Statistical Inference) Fall-2009 Dated: 27 th August 2009 Course Supervisor(s): Mr. Ahmed.

Chapter 10 Statistical Inference for Two Samples More than one but less than three! Chapter 10B < X

Recapitulation! Statistics 515. What Have We Covered? Elements Variables and Populations Parameters Samples Sample Statistics Population Distributions.

New Information Technologies in Learning Statistics M. Mihova, Ž. Popeska Institute of Informatics Faculty of Natural Sciences and Mathematics, Macedonia.

Beginning Statistics Table of Contents HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008 by Hawkes Learning Systems/Quant Systems, Inc.

0-1 Intro Basic Statistics Stat 220 Autumn 2005 Prof. June Morita Dept. of Statistics Teaching Assistants Cathee Kneeling Maggie Niu Roopesh Ranjan.

Stats Term Test 4 Solutions. c) d) An alternative solution is to use the probability mass function and.

Statistics and Probability Theory Lecture 01 Fasih ur Rehman.

Green Belt – SIX SIGMA OPERATIONAL Central Limit Theorem.

Course Review. Distributions What are the important aspects needed to describe a distribution of one variable? List three types of graphs that could be.

ESTIMATION OF THE MEAN. 2 INTRO :: ESTIMATION Definition The assignment of plausible value(s) to a population parameter based on a value of a sample statistic.

WARM UP: Penny Sampling 1.) Take a look at the graphs that you made yesterday. What are some intuitive takeaways just from looking at the graphs?

Statistics and probability Dr. Khaled Ismael Almghari Phone No:

Stats 242.3(02) Statistical Theory and Methodology.

RES 342 GUIDES E XCELLENCE I N S TUDY RES 342 Entire Course FOR MORE CLASSES VISIT RES 342 Week 1 Individual Assignment Hypothesis.

Mail Call Us: , , Data Science Training In Ameerpet

schmidt-bremen.de -> QM (MGM)

Covariance/ Correlation

Chapter 1 A Review of Basic Concepts (Optional).

Statistical Quality Control, 7th Edition by Douglas C. Montgomery.

Chapter 4. Inference about Process Quality

R. E. Wyllys Copyright 2003 by R. E. Wyllys Last revised 2003 Jan 15

ISSCM 491 Managerial Statistics

Chapter Six Normal Curves and Sampling Probability Distributions

William J. Miller Christopher M. Lowery

Introductory Statistical Language

Part Three. Data Analysis

Econ Roadmap Focus Midterm 1 Focus Midterm 2 Focus Final Intro

Covariance/ Correlation

Covariance/ Correlation

What Statistical Knowledge Should Students Know to Prepare for Graduate Business Analytics? Jeffrey D. Camm Wake Forest University School of Business

Chapter 12 Inference on the Least-squares Regression Line; ANOVA

Session 2:50 PM - 4:20 PM; Saturday, Nov 18, 2017

STAT 5372: Experimental Statistics

Chapter 7: Introduction to Sampling Distributions

Covariance/ Correlation

Essentials of Statistics for Business and Economics (8e)

Mobile Teaching Statistics by Using

Presentation transcript:

Adapting to Different Audiences Chris Lowery and Bill Miller Georgia College & State University

Graduate Business Programs Part- time MBA Full-time MBA WebMBA Logistics Others

Part-time MBA One semester course Stats prerequisite

Part-time MBA Topics Centrality, Dispersion Normal Distribution Interval Estimation Hypothesis Testing Two population inferences ANOVA Regression Nonparametric procedures Text: Anderson, Sweeney, Williams, Camm, Cochran Statistics for Business and Economics (2014) Minitab

Full-time MBA Non-business undergraduates One semester course No stats prerequisite

Full-time MBA Topics Centrality, Dispersion Visual displays Probability Binomial Distribution Normal Distribution Interval Estimation Hypothesis Testing (1 and 2 Populations) ANOVA Regression Text: Anderson, Sweeney, Williams, Camm, Cochran Statistics for Business and Economics (2014) Software: Minitab

Web MBA Topics Columbus State University, Georgia College & State University, Georgia Southern University, Kennesaw State University, University of West Georgia, Valdosta State University Summer 2013Spring 2014 Intro to Data Analysis and Decision Making Describing Data: Graphs and Tables Describing Data: Summary Measures Getting the Right Data Regression Forecasting Linear Programming Models Probability and Probability Distributions Normal and Binomial Distributions Sampling and Sampling Distributions Confidence Interval Estimation Introduction to Quantitative Analysis Probability Concepts and Applications Decision Analysis Regression Models Forecasting Linear Programming Models Network Models Waiting Lines and Queuing Theory Simulation Modeling Text: Albright, Winston, & Zappe (2009) Analysis & Decision Making with MS Excel Text: Render, Stair & Hanna (2012) Quantitative Analysis for Management Software Tools StatTools for Excel Solver (LP) QM for Windows Excel QM Data Analysis (Excel-Undergrad)