MAS1401 Statistical Methods An Introduction to Statistical Methods used in the Agricultural and Biological Sciences Lecturer: Dr David Walshaw School of.

Slides:



Advertisements
Similar presentations
David S. Jones School of Pharmacy.  High Academic Background (circa 435 tariff points)  Requirements (AAB or ABB with an A in a fourth AS subject) 
Advertisements

13- 1 Chapter Thirteen McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
1 BA 275 Quantitative Business Methods Residual Analysis Multiple Linear Regression Adjusted R-squared Prediction Dummy Variables Agenda.
Statistics 350 Lecture 16. Today Last Day: Introduction to Multiple Linear Regression Model Today: More Chapter 6.
1 Welcome School of Computing and Mathematical Sciences (CMS)
Statistics for Business and Economics II Stat II Dr. Shuguang Liu.
Stat 217 – Week 10. Outline Exam 2 Lab 7 Questions on Chi-square, ANOVA, Regression  HW 7  Lab 8 Notes for Thursday’s lab Notes for final exam Notes.
1 Business 90: Business Statistics Professor David Mease Sec 03, T R 7:30-8:45AM BBC 204 Lecture 21 = Start Chapter “Confidence Interval Estimation” (CIE)
Quantitative Research Methods for Information Systems and Management (Info 271B) Introduction to Social Research.
732G21/732G28/732A35 Lecture 2. Inference concerning β 1  Confidence interval for β 1 : where  Test concerning β 1 : H 0 : β 1 = 0 H a : β 1 ≠ 0 Reject.
Quantitative Research Methods for Information Systems and Management (Info 271B) Course Introduction: Preface to Social Research and Quantitative Methods.
Educational Research by John W. Creswell. Copyright © 2002 by Pearson Education. All rights reserved. Slide 1 Chapter 8 Analyzing and Interpreting Quantitative.
Statistics 350 Lecture 17. Today Last Day: Introduction to Multiple Linear Regression Model Today: More Chapter 6.
Statistics for the Social Sciences Psychology 340 Spring 2005 Course Review.
University of Colorado - Dept of Aerospace Engineering Sciences - Introduction to FEM This is ASEN 5007: Introduction to Finite Element Methods.
Teaching Statistics Methods for Biology 1. Outline About stat 503 Students Course set up – Lecture – Project Challenges Teaching approach – Project design.
David S. Jones School of Pharmacy.  High Academic Background (circa 435 tariff points)  Requirements (AAB or ABB with an A in a fourth AS subject) 
ANALYSIS OF BIOLOGICAL DATA BIOL4062/5062 Hal Whitehead.
Course Introduction: Preface to Social Research and Quantitative Methods.
Overall agenda Part 1 and 2  Part 1: Basic statistical concepts and descriptive statistics summarizing and visualising data describing data -measures.
Math 125 Statistics. About me  Nedjla Ougouag, PhD  Office: Room 702H  Ph: (312)   Homepage:
N318b Winter 2002 Nursing Statistics Specific statistical tests: Correlation Lecture 10.
Correlation and Regression
FROM NOW TO THE FUTURE MATHEMATICS Return Home Return Home Mathematics: Where do I see my future? What am I good at? What do I enjoy?
Statistics 3 F71SC3. Contact Times (Summer Term 2008) Monday, , Lecture in LT1 Tuesday, , Maple Practical, in SR G12/13 Thursday,
Chap 12-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition Chapter 12 Introduction to Linear.
An Interdisciplinary Approach in Statistics Courses for Biology Students Ramon Gomez Senior Instructor Dept. of Math & Statistics Florida International.
Go to Table of Content Single Variable Regression Farrokh Alemi, Ph.D. Kashif Haqqi M.D.
Quantitative Methods in Geography Geography 391. Introductions and Questions What (and when) was the last math class you had? Have you had statistics.
Inference for Regression Chapter 14. Linear Regression We can use least squares regression to estimate the linear relationship between two quantitative.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
STAT 3130 Statistical Methods I Lecture 1 Introduction.
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
STA 286 week 131 Inference for the Regression Coefficient Recall, b 0 and b 1 are the estimates of the slope β 1 and intercept β 0 of population regression.
School of Mathematics & Statistics Stage 3 Induction 29 th September 2015 I am... Dr Peter Avery I am... Single Honours Degree Programme Director (Student.
2 sample interval proportions sample Shown with two examples.
Lecture 13: Chapter 11 David Wallace Croft Statistics for Psychology 2005 Jun 24 Fri Copyright 2005 David Wallace.
Course Outline Presentation Reference Course Outline for MTS-202 (Statistical Inference) Fall-2009 Dated: 27 th August 2009 Course Supervisor(s): Mr. Ahmed.
New Information Technologies in Learning Statistics M. Mihova, Ž. Popeska Institute of Informatics Faculty of Natural Sciences and Mathematics, Macedonia.
School of Mathematics & Statistics Stage 3 Induction 30 th September 2015 I am... Dr Peter Avery I am... Single Honours Degree Programme Director (Student.
Beginning Statistics Table of Contents HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008 by Hawkes Learning Systems/Quant Systems, Inc.
Statistics and Probability Theory Lecture 01 Fasih ur Rehman.
Power Point Slides by Ronald J. Shope in collaboration with John W. Creswell Chapter 7 Analyzing and Interpreting Quantitative Data.
Statistics and probability Dr. Khaled Ismael Almghari Phone No:
BUS 308 Complete Class BUS 308 Week 1 DQ 1 Data Scales BUS 308 Week 1 DQ 2 Probability BUS 308 Week 1 Quiz BUS 308 Week 1 Problem Set Week One BUS 308.
Statistical Data Analysis STAT221A
R. E. Wyllys Copyright 2003 by R. E. Wyllys Last revised 2003 Jan 15
Physics 210 General Physics I
ISSCM 491 Managerial Statistics
National University of Singapore
Chapter 13 Created by Bethany Stubbe and Stephan Kogitz.
MATH Instructor: Dr. Saralees Nadarajah
PSY 325 TUTOR Education for Service-- psy325tutor.com.
CHAPTER 29: Multiple Regression*
CHAPTER 26: Inference for Regression
Chapter 12 Inference on the Least-squares Regression Line; ANOVA
Lecture Slides Elementary Statistics Twelfth Edition
(or why should we learn this stuff?)
MA171 Introduction to Probability and Statistics
Correlation and Regression
12 Inferential Analysis.
Lecture Slides Elementary Statistics Twelfth Edition
Pima Medical Institute Online Education
Section 12.2 Comparing Two Proportions
ADVANCED DATA ANALYSIS IN SPSS AND AMOS
MA171 Introduction to Probability and Statistics
Announcements DS-203 Fall 2008.
Dr. David A. Gaitros Department of Computer Science
Announcements DS-203 Fall 2007.
STAT 515 Statistical Methods I Lecture 1 August 22, 2019 Originally prepared by Brian Habing Department of Statistics University of South Carolina.
Presentation transcript:

MAS1401 Statistical Methods An Introduction to Statistical Methods used in the Agricultural and Biological Sciences Lecturer: Dr David Walshaw School of Mathematics and Statistics, Merz Court

Course Arrangements :  Lectures: Just one each week, Monday 10am, Bedson LT1.  Computer Practical Classes: One two-hour session in each even week. GROUPS Tuesday9-11Stephenson Tree PC Wednesday9-11Merz Oracle PC Thursday9-11Daysh Brae PC Friday9-11Daysh Brae PC Check with your degree programme office for your group!

Assessment  There is *no* exam for this course!!!  Assessment: 100% based on assignments set in the practical classes.  There will be six assignments. Don’t fall behind!

Course Structure  The course is run in fortnightly blocks, each ending in a practical session with a set assignment.  The fortnightly blocks correspond to the six chapters in the course: Chapter 1.Descriptive statistics Chapter 2. Studying Normal populations Chapter 3. Confidence intervals and hypothesis tests Chapter 4. Analysis of variation (ANOVA) Chapter 4. Analysis of variation (ANOVA) Chapter 5.Studying non-Normal populations Chapter 6. Correlation and linear regression

Course Notes  PowerPoint presentations given in the lecture, then made available on the web.  Fortnightly handouts summarizing the material from each chapter. Given out in lectures.  Additional notes for you to take down in the lectures, and available only in the lectures.

Study Methods  We will analyse data using the computer package MINITAB.  The emphasis will be on understanding the analysis and interpreting the results.  Mathematics will be kept to a minimum!!

 I don’t use Blackboard.  Materials for this course will be on the web: