Syllabi



Sample Topics #1
This is for a one semester Elementary Statistics course with no prerequisites. It is taken by almost all non-technical majors on campus.

Experimental Design
Random samples (random, stratified, systematic, cluster, multistage, convenience)
Observational studies vs. experiments
Surveys (good to cover if students will be doing a project using one)

Organizing Data and Graphing Data
Frequency tables
Pie charts
Bar graphs
Histograms
Ogives
    
Descriptive Statistics
Central tendency: mode, median, and mean
Variation: range, variance, standard deviation
Quartiles and box-and-whisker plots

Probability Theory
Multiplication rule, addition rule, mutually exclusive events, conditional probability, independence
Probability distributions (definition, mean, and variance of a general discrete distribution given by a table)
        
The Normal Distribution
Graphs of the normal distributions and the Empirical rule
z-scores, raw scores, and finding probabilities using the normal distribution
Inverse normal distribution

Sampling Distributions (one sample only)
Sampling distributions for means (Central Limit Theorem)
Sampling distributions for proportions

Confidence Intervals (Estimation)
Estimating μ when σ is known
Estimating μ when σ is unknown
    
Hypothesis Testing
Testing the mean μ when σ is known
Testing the mean μ when σ is unknown
Testing a proportion p
Tests involving paired differences (dependent samples)
Testing μ₁-μ₂ and p₁-p₂ (independent samples)

Correlation and Regression
Scatter diagrams and linear correlation
Linear regression and the coefficient of determination
Inferences for correlation and regression

Chi-Square Distribution
Tests of independence and homogeneity
Goodness of fit


Sample Topics #2 for a strong general education class.  When the class was weaker I stopped at Hypothesis Testing for proportions

Topic

 

Types of data

Analyzing basic single-variable plots

Measures of central tendency and position
Empirical Rule

 

Associations between two variables

Analyzing Data  Influential points, causal relationships, lurking variables, confounding variables

 

Observational studies and experiments

Random Selection

Blocking, clusters, stratification

 

Introduction to Probability

Bayes' Rule

Normal Distribution

Binomial Distribution
Normal approximation for binomial distribution

 

Sampling Distributions for means

Sampling Distributions for proportions

 

Point estimate, interval estimate

Confidence Intervals for proportions

Confidence i\Intervals for a mean

 

Introduction to significance tests

Writing Null and Alternate Hypotheses
Understanding a p-value

Significance testing for proportions

Significance testing for means

Hypothesis test errors

Comparing two proportions

Comparing two means

Matched pairs