Course ePortfolio

Online statistics open textbook and additional resources to assist students in understanding of statistics. Topics covered include Analysis of Variance, Boxplot, Confidence interval, Contrast among means, Correlated t-test, Correlation, Histogram, Independent groups t-test, Regression, Repeated measures ANOVA, and t-test.

This is a free online calculator for common statistics and data analysis for categorical data, continuous data, statistical distributions and interpreting P values, random numbers and chemical and radiochemical data.

A collection of applets designed to illustrate various topics in statistics and probability. Topics include Simulating Confidence Intervals for Population Parameter, Behavior of Regression Line, Reeses Pieces, Histogram Bin Width, Sampling Senators, Sampling Pennies, Dotplot Summaries, Guess the Correlation.

This tutorial will help you determine how accurate a sample mean is likely to be, and how this accuracy is related to the sample size. Brief reviews of the normal distribution and the Central Limit Theorem are included as supplemental materials.

"The Flash mathlets are divided into two sections.The For Students and Instructors section contains Flash applets which may be useful to instructors for classroom demonstrations, as well as to students for independent work and exploration. The For Developers section presents applets together with varied templates and the complete, object-oriented, easily-customizable source code that can be used by instructors for creating their own customized versions of the applets."

A searchable database of more than 1000 test questions for introductory statistics concepts. The user is prompted to select subject material and learning outcome expectations from a variety of question formats and then downloads the items and can edit the test with a word processor.

The site includes guided interdisciplinary labs for first and second courses in statistics. As stated on the homepage for this site, "This site presents workbook-style, project-based material that emphasizes real world applications and conceptual understanding. This material is designed to give students a sense of the importance and allure of statistics early in their college career. By incorporating many of the successful reforms of the introductory statistics course into a wide range of more advanced topics we hope that students in any discipline can realize the intellectual content and broad applicability of statistics."

This applet allows users to generate confidence intervals for either means or proportions. Users set the parameters including the number of samples and click "Sample." The applet graphs the intervals such that intervals containing the true mean or proportion are in green, while intervals not containing the true mean or proportion are in red. The true mean or proportion is shown by a blue line.

'Introductory Statistics follows the scope and sequence of a one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean, which has been widely adopted. Introductory Statistics includes innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful and memorable, so that students can draw a working knowledge from it that will enrich their future studies and help them make sense of the world around them. The text also includes Collaborative Exercises, integration with TI-83,83+,84+ Calculators, technology integration problems, and statistics labs.'

Demonstrates Correlation Coefficients in Statistics.

This site contains an extensive collection of java applets involving probability miscellany and puzzles. Written by Alexander Bogomolny, these applets are designed to engage the reader in interactive investigations. Background material is provided and the site serves as an excellent educational resource.

This is a collection of interactive scatterplots. The simulations display the regression line and allow the usere to change the location of data points, the slope of the regression line, the correlation coefficient, and sample size, as well as it provides rollover help.

This Java applet tutorial provides a series of word problems on determining confidence intervals. Each problem prompts the user to input the steps for determining a confidence interval for the mean. Hints are provided whenever the user enters an incorrect value. Once the steps are completed, a statement summarizing the interval obtained is displayed. The applet is supported by an explanation of the steps in creating confidence intervals..

This Java applet tutorial prompts the user to input the components of a hypothesis test for the mean. Hints are provided whenever the user enters an incorrect value. Once the steps are completed and the user has chosen the correct conclusion for accepting or rejecting the null hypothesis, a statement summarizing the conclusion is displayed. The applet is supported by an explanation of the steps in hypothesis testing and a description of one-tailed and two-tailed tests.

This Java applet tutorial provides a series of word problems on determining confidence intervals. Each problem prompts the user to input the steps for determining a confidence interval for the mean. Hints are provided whenever the user enters an incorrect value. Once the steps are completed, a statement summarizing the interval obtained is displayed. The applet is supported by an explanation of the steps in creating confidence intervals..

This Java applet tutorial prompts the user to input the components of a hypothesis test for a proportion. Hints are provided whenever the user enters an incorrect value. Once the steps are completed and the user has chosen the correct conclusion for accepting or rejecting the null hypothesis, a statement summarizing the conclusion is displayed. The applet is supported by an explanation of the steps in hypothesis testing and a description of one-tailed and two-tailed tests.

This is a virtual linear regression calculator. It allows students to enter data points, experiment with where the line of best fit might be, and then lets them see the correct line of best fit as well as the outliers. You can click through the introduction.

This site provides flash animation and directions for common uses of the TI-83+. The text files require Adobe Acrobat Reader. see more

This video was recorded at Stanford Engineering Everywhere EE364A - Convex Optimization I. So in pure statistics there's just parameterized probability distributions and we have a parameter X and your job, you get one or more samples from one of these distributions and you're charge is to say something intelligent about which distribution, which is to say which parameter value, generated the sample. So that's statistics. So a standard technique is maximum likelihood estimations. In maximum likelihood estimation you do the following. You have an observation Y and you look at the density of the – you look at the density at Y or probability distribution if it's a distribution on like – if its got different points on atomic points. ... See the whole transcript at Convex Optimization I - Lecture 11

This video was recorded at 6.00SC Introduction to Computer Science and Programming, Spring 2011 . Topics covered: Big O notation, algorithm complexity, algorithm comparison example, object-oriented programming, Person class example, defensive programming, private attributes, mutability, aliasing.

This video was recorded at 6.00SC Introduction to Computer Science and Programming, Spring 2011 . This lecture starts with some examples of how to use pylab's plotting mechanisms. It then returns to the topic of using probability and statistics to derive information from samples. Topics covered: Plotting, randomness, probability, Pascal's algorithm, Monte Carlo simulation, inferential statistics, gambler's fallacy, law of large numbers.

This video was recorded at 6.00SC Introduction to Computer Science and Programming, Spring 2011 . This lecture starts with some examples of how to use pylab's plotting mechanisms. It then returns to the topic of using probability and statistics to derive information from samples. Topics covered: Plotting, randomness, probability, Pascal's algorithm, Monte Carlo simulation, inferential statistics, gambler's fallacy, law of large numbers.

This video was recorded at 6.00SC Introduction to Computer Science and Programming, Spring 2011 . This lecture starts with some examples of how to use pylab's plotting mechanisms. It then returns to the topic of using probability and statistics to derive information from samples. Topics covered: Plotting, randomness, probability, Pascal's algorithm, Monte Carlo simulation, inferential statistics, gambler's fallacy, law of large numbers.

This video was recorded at 6.00SC Introduction to Computer Science and Programming, Spring 2011 . This lecture starts with some examples of how to use pylab's plotting mechanisms. It then returns to the topic of using probability and statistics to derive information from samples. Topics covered: Plotting, randomness, probability, Pascal's algorithm, Monte Carlo simulation, inferential statistics, gambler's fallacy, law of large numbers.

This tutorial is designed to give students practice in calculating basic probabilities using the binomial distribution. The applet gives students short problem descriptions that require a binomial probability to solve. The user is then prompted to follow a step by step process to find the probability. Users must answer a step correctly before the applet will allow them to move onto the next step. The page also gives further exercises that allow the user to think about binomial distributions more deeply and gives a link to more detailed information about the binomial distribution. This tutorial is one of a number of easy-to-use statistics tutorials developed by Larry Green

This applet demonstrates the theory behind linear regression.