Topic: Basic statistics, probability, and survey sampling
Format: Printed explanations (some graphics) and sample problems
Reviewer/email: Mike G – greers_pm@yahoo.com
This introduction to statistics and probability is clean and simple — nothing fancy. But as one who’s had my share of difficulty with statistics, I’d say it’s a solid introduction to a sometimes baffling topic. The website say it’s “designed to get you productive as quickly and painlessly as possible.” Short lessons, clear examples, sample problems… it’s all here.
(Continued in Comment.)
“This tutorial covers statistics, probability, and survey sampling. It is designed to get you productive as quickly and painlessly as possible… After completing the tutorial, you will be able to:
* Compute the probability that a particular event will occur.
* Use the right probability distribution (normal, t, binomial, etc.) for your analysis.
* Estimate population means and proportions, based on sample data.
*Determine margin of error and confidence levels.
*Test hypotheses about means and proportions.
*Choose the sample design that yields maximum precision for minimum cost.
* And much more . . .
Topics are introduced in short, easy-to-understand modules. Each lesson covers a single topic, and most lessons include one or more review questions to reinforce learning.”
NOTE: This website provides “The Advanced Placement (AP) Statistics Tutorial” to help prepare for the Advanced Placement (AP) Statistics Exam. However, the tutorial reviewed here (Introduction to Statistics and Probability) “includes all of the lessons from the AP Statistics Tutorial, and more!”
CAVEAT — The website makes this assumption: “Each tutorial assumes that you are comfortable with arithmetic (addition, substraction, multiplication, and division), as well as basic algebra.”
Here’s a complete outline (all topics covered) in the Statistics and Probability Tutorial:
Descriptive Statistics
* Quantitative measures (Variables, Measures of central tendency, Measures of variability, Measures of position)
* Charts and graphs (Patterns in data, Dotplots, Histograms, Stemplots, Boxplots, Cumulative frequency plots, Scatterplots, Comparing distributions)
* Tabular displays (One-way tables, Two-way tables)
Probability
* Probability basics (Sets and subsets, Statistical experiments, Counting data points)
* Probability laws (Introduction to probability, Working with probability, Laws of probability, Bayes’ rule)
* Random variables (Types of random variables, Probability distributions, Random variable attributes, Combining random variables, Transforming random variables)
* Sampling theory (Simple random sampling, Measures of interest, Measures of variability, Sampling distributions, Difference between proportions, Difference between means)
Distributions
* Distribution basics (Probability distributions, Discrete vs. continuous)
* Discrete (Binomial distribution, Negative binomial, Hypergeometric
Multinomial, Poisson)
* Continuous (Normal distribution, Standard normal, Student’s t distribution
Chi-square, F distribution)
Estimation
* Estimation theory (Estimation overview, Standard error, Margin of error
Confidence intervals)
* Proportions (Estimating a proportion, Proportions and small samples, Difference between proportions)
* Mean scores (Estimating a population mean, Difference between means, Difference between matched pairs)
Hypothesis Testing
* Foundations of testing (Tests of significance, How to test hypotheses)
* Mean scores (Hypothesis test of the mean, Difference between means, Difference between matched pairs)
* Proportions (Test for a proportion, Proportions and small samples, Difference between proportions)
* Power (Region of acceptance, Power of a test, How to compute power)
* Chi-square tests (Goodness of fit, Test for homogeneity, Test for independence)
Survey Sampling
* Sampling methods (Data collection methods, Survey sampling methods, Bias in survey sampling)
* SRS (Survey sampling, Analysis of simple random samples)
* Stratified sampling (Stratified random sampling, Analysis of stratified samples)
* Cluster sampling (Cluster sampling introduction, Analysis of cluster samples)
* Sample planning (Sample size: Simple random samples, Sample size: Stratified samples, How to compare sampling methods)
More Applied Statistics
* Linear regression (Linear correlation, Least squares linear regression, A regression example)
* Regression tests (Residual analysis, Transformations for linearity, Confidence interval for slope, Test of significance for slope)
* Experiments (Experiments, Experimental designs, Simulation experiments)
Appendices
* Notation
* Statistics Formulas
URL of Stat Trek tutorial — http://stattrek.com/Lesson1/Intro.aspx
======== RELATED REVIEWS FROM “The Best Free Training” =================
xyAlgebra and xySolver — http://www.bestfreetraining.net/?p=109
Math Tutorials for Chemistry, Economics, Political Science & Psychology Students — http://www.bestfreetraining.net/?p=221
ProProfs Online Free SAT Exam Study Center — http://www.bestfreetraining.net/?p=66
SAT Skills Insight: Get Ready for the SAT Exam — http://www.bestfreetraining.net/?p=214
Professor Martin Weissman
Essex County College
Newark, NJ 07102
weissman@essex.edu