Browse:
Keywords: Probability
(Complete Item Description)
- Abstract: Introduces statistical data analysis, concentrating on techniques used in management science and finance. Topics chosen from: statistical graphics, basics of sampling, estimation, hypothesis testing, linear and logistic regression, analysis of variance, contingency tables, forecasting, statistical quality control, principal components, and factor analysis. SAS or similar package used for data analysis. This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra. We would like to acknowledge the contributions that Prof. Roy Welsch (MIT), Prof. Gordon Kaufman (MIT), Prof. Jacqueline Telford (Johns Hopkins University), and Prof. Ramón León (University of Tennessee) have made to the course material.
- Subject:
Business, Mathematics and Statistics
- Grade Level:
Post-secondary
- Collection:
MIT OpenCourseWare
(Complete Item Description)
- Abstract: The purpose of this investigation is to have students analyze cloud cover and to compose written conclusions to a given related scenario.
- Subject:
Mathematics and Statistics, Science and Technology
- Grade Level:
Primary, Secondary
- Collection:
NASA
(Complete Item Description)
- Abstract: This course covers population and variables; Standard measures of location, spread and association; Normal approximation; Regression. Probability and sampling: Binomial distribution. Interval estimation; Some standard significance tests.
(Complete Item Description)
- Abstract: Finding the true probability of an event taking into account misses, false positives, and base rates. Also, using Bayes' Theorem.
- Subject:
Mathematics and Statistics
- Grade Level:
Post-secondary
- Collection:
Connexions
(Complete Item Description)
- Abstract: This module contains a review of the basic concepts of probability.
- Subject:
Mathematics and Statistics
- Grade Level:
Post-secondary
- Collection:
Connexions
(Complete Item Description)
- Abstract: Students play a game in which they place beans on numbers that represent the sum of two dice. Each time a number comes up in a dice roll, a corresponding bean may be removed. The first person who removes all his beans wins the game. Students mathematically analyze the game to develop strategies.
(Complete Item Description)
- Abstract: This course covers population and variables; Standard measures of location, spread and association; Normal approximation; Regression. Probability and sampling: Binomial distribution. Interval estimation; Some standard significance tests.
(Complete Item Description)
- Abstract: This activity will allow students to familiarize themselves with technology and its use in calculating marginal, conditional, and joint distributions, as well as making conclusions from these tabular and graphical displays.
- Subject:
Mathematics and Statistics
- Grade Level:
Post-secondary
- Collection:
Causeweb.org
(Complete Item Description)
- Abstract: The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform).
- Subject:
Mathematics and Statistics
- Grade Level:
Post-secondary
- Collection:
Causeweb.org
(Complete Item Description)
- Abstract: What many people refer to as 'good luck' can actually be explained by a little knowledge about probability and statistics. Our dice game allows you to see how increasing or decreasing the number of dice rolls affects an outcome. So give it a try, choose the number of rolls you would like to make...
(Complete Item Description)
- Abstract: What kind of coat will keep you the warmest, one made from cotton, steel wool or air? In this experiment, students test three materials to determine which one is the best insulator.
- Subject:
Science and Technology, Mathematics and Statistics
- Grade Level:
Primary
- Collection:
Jefferson Lab
(Complete Item Description)
- Abstract: Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. This textbook is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. The textbook is also available in printed form from Qoop.com.
- Subject:
Mathematics and Statistics
- Grade Level:
Post-secondary
- Collection:
Connexions
(Complete Item Description)
- Abstract: This is a custom collection (by R. Bloom) of homework and review problems to accompany Collaborative Statistics textbook custom collection by R. Bloom. Content is derived from Collaborative Statistics written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook by S. Dean and B. Illowsky was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. This textbook is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. This custom version of their collection has been modified by R. Bloom for her classes at De Anza College.
- Subject:
Mathematics and Statistics
- Grade Level:
Secondary, Post-secondary
- Collection:
Connexions
(Complete Item Description)
- Abstract: Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. This textbook is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. This custom textbook collection has been modified by R. Bloom for her classes at De Anza College; the homework content for the custom collection is now contained in a separate homework collection.
- Subject:
Mathematics and Statistics
- Grade Level:
Secondary, Post-secondary
- Collection:
Connexions
(Complete Item Description)
- Abstract: Introduces students to the basic tools in using data to make informed management decisions. Covers introductory probability, decision analysis, basic statistics, regression, simulation, and linear and nonlinear optimization. Computer spreadsheet exercises and examples drawn from marketing, finance, operations management, and other management functions. Restricted to Sloan Fellows.
(Complete Item Description)
- Abstract: Covers computational and data analysis techniques for environmental engineering applications. First third of subject introduces MATLAB and numerical modeling. Second third emphasizes probabilistic concepts used in data analysis. Final third provides experience with statistical methods for analyzing field and laboratory data. Numerical techniques such as Monte Carlo simulation are used to illustrate the effects of variability and sampling. Concepts are illustrated with environmental examples and data sets. This subject is a computer-oriented introduction to probability and data analysis. It is designed to give students the knowledge and practical experience they need to interpret lab and field data. Basic probability concepts are introduced at the outset because they provide a systematic way to describe uncertainty. They form the basis for the analysis of quantitative data in science and engineering. The MATLAB® programming language is used to perform virtual experiments and to analyze real-world data sets, many downloaded from the web. Programming applications include display and assessment of data sets, investigation of hypotheses, and identification of possible casual relationships between variables. This is the first semester that two courses, Computing and Data Analysis for Environmental Applications (1.017) and Uncertainty in Engineering (1.010), are being jointly offered and taught as a single course.
- Subject:
Science and Technology
- Grade Level:
Post-secondary
- Collection:
MIT OpenCourseWare
(Complete Item Description)
- Abstract: This course covers population and variables; Standard measures of location, spread and association; Normal approximation; Regression. Probability and sampling: Binomial distribution. Interval estimation; Some standard significance tests.
(Complete Item Description)
- Abstract: This course covers population and variables; Standard measures of location, spread and association; Normal approximation; Regression. Probability and sampling: Binomial distribution. Interval estimation; Some standard significance tests.
(Complete Item Description)
- Abstract: This publication offers online resources that connect mathematics to three subject areas: social studies, art, and science. Each section contains lesson plans, problems to solve, and examples of mathematics at work within contexts not usually associated with school mathematics.
- Subject:
Mathematics and Statistics, Social Sciences, Science and Technology
- Grade Level:
Primary, Secondary
- Collection:
Middle School Portal
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