MTH225 Spring 2013 Syllabus

Topic NumberMajor TopicText Chapter(s)Subtopics
1 Probability and Distributions 1Overview
N/AUsing Technology
1Measures of Location
1Measures of Variability
2 Probability 4.1-4.3Random Phenomena: Experiments, Sample Spaces and Events
N/ABernoulli Trials
4.2Axioms, Interpretations, and Properties
N/ACounting Techniques
4.5Conditional Probability
4.5Independence
3 Discrete Random Variables 3.1Random Variables
4.3Discrete Probability Distributions
4.4Expected Values
5.2The Binomial Distribution
N/AThe Geometric, Negative Binomial, and Hypergeometric Distributions
N/AThe Poisson Distribution
4 Continuous Random Variables 4.1-4.3Probability Density Functions
4.4Cumulative Distribution Functions and Expected Values
4.3The Normal Distribution
N/AOther Continuous Distributions
5 Multivariate Distributions 2.5Discrete Joint Distribution Functions
N/AContinuous Joint Distribution Functions
2.5 (discrete)Marginal Distributions
2.5 (discrete)Conditional Distributions
N/ASimulation: The Metropolis Algorithm
N/ASimulation: Gibbs Sampling
6 Sampling Distributions 5.1Distribution of the Sample Mean
5.1The Central Limit Theorem
5.2Counts and Proportions
7 Confidence Intervals 6.1Basic Properties of Confidence Intervals
6.1Large Sample and Normal Population Results
6.1Bootstrap Methods
N/ACredible Intervals and Bayesian Inference
8 Hypothesis Testing 7.1Testing Hypotheses on Means (Known Sigma)
7.1Small Sample Tests About a Population Mean (Unknown Sigma)
8.1Tests About a Population Proportion
7.1P-Values
9 Inference Based on Two Samples 7.2The Difference Between Two Population Means (Known Variance)
7.2The Difference Between Two Population Means (Unknown Variance)
N/AAnalysis of Paired Data
8.2Inference on Two Proportions
10 The Analysis of Variance N/ALinear Models Overview
12.1Single-Factor ANOVA
13.1Two-Factor ANOVA
10.1Simple Linear Regression
11.1Multiple Linear Regression
11 Additional Topics N/AMarkov Chain Montecarlo Methods and BUGS