BISHOP’S UNIVERSITY

LENNOXVILLE, QUEBEC

FALL 2005

PHYSICS 101: STATISTICAL METHODS IN EXPERIMENTAL SCIENCE

 

INSTRUCTOR:         Professor K. Jaffer

SCHEDULE:  Mon, Wed, Fri 12:30 - 1:30; Bishops Williams Hall, J200

TEXT: Introduction to Probability and Statistics, 12th ed. by Mendenhall, Beaver, and Beaver

SYNOPSIS:    This course is specifically designed to meet the needs of students of physics, chemistry, biology, mathematics and computer science. Topics include: errors of observation, graphical visualization of data; descriptive analysis; elementary probability, permutations and combinations; the binomial, normal and Poisson distributions; random sampling; testing hypotheses, significance levels, confidence limits, large and small sampling methods; regression and correlation; chi-square test; analysis of variance.

Note: In order for students to obtain credit for both Physics 101 and Mathematics 213, Physics 101 must be taken first or concurrently.

REFERENCES:         Several texts are on reserve at the library.  In addition, the companion site for the text book is a valuable resource.

ASSIGNMENTS:      Assignments must be submitted by the due date.  Late assignments will not be accepted unless special permission has been granted in advance.

MARKING SCHEME:         Assignments:       10%

                                                                Class Tests (2):     30%
                                                                Final Exam:            60%

CONTACT INFO:     Professor K. Jaffer

Johnson 1, x2482 

                                    kjaffer@ubishops.ca

COURSE INFO:        Office hours, assignment questions, respective due dates, news and course updates are all available on the website: http://physics.ubishops.ca/kjaffer

TOPICS TO BE COVERED (as time permits):

  1. Descriptive Statistics, Ch. 1-3

                                             i.      Visualizing Data; Frequency Distributions; Stem and Leaf Plots

                                            ii.      Analyzing Data; Measures of Central Tendency; Measures of Variation

                                          iii.      The Standard Deviation; z-scores

                                          iv.      Linear Correlation & Regression; Correlation Coefficient; Non-Linear Regression

  1. Probability and Distributions, Ch 4-6

                                             i.      Permutations and Combinations

                                            ii.      Addition and Multiplication Rules; Conditional Probability

                                          iii.      Discrete Probability Distributions; Binomial Distribution; Poisson Distribution

                                          iv.      Normal Distribution, Applications; Approximation to the Binomial Distribution

  1. Inferential Statistics, Ch 7-10, 14, 11-13

                                             i.      Stratified Sampling; Sample Means

                                            ii.      Central Limit Theorem

                                          iii.      Estimations; Significance; Confidence Intervals

                                          iv.      Hypothesis Testing; Types of Errors; p-values; Applications

                                           v.      Chi-Squared Distribution; Goodness of Fit; Contingency Tables

                                          vi.      Analysis of Variance; One-way and Two-way ANOVA Tables

                                        vii.      Linear Regression Revisited; Correlation Confidence

                                       viii.      Multiple Regression, Applications