A+ Click is an interactive collection of more than 3700 math problems and answers for K-1 K-12 school program. It defines the personal level of math knowledge. You move up into the next level if you give 5 correct answers in a row. Practice makes perfect.
This textbook is part of the OpenIntro Statistics series and offers complete coverage of the high school AP Statistics curriculum. Real data and plenty of inline examples and exercises make this an engaging and readable book. Links to lecture slides, video overviews, calculator tutorials, and video solutions to selected end of chapter exercises make this an ideal choice for any high school or Community College teacher. In fact, Portland Community College recently adopted this textbook for its Introductory Statistics course, and it estimates that this will save their students $250,000 per year. Find out more at: openintro.org/ahss
View our video tutorials here:
Students build a formal understanding of probability, considering complex events such as unions, intersections, and complements as well as the concept of independence and conditional probability. The idea of using a smooth curve to model a data distribution is introduced along with using tables and techonolgy to find areas under a normal curve. Students make inferences and justify conclusions from sample surveys, experiments, and observational studies. Data is used from random samples to estimate a population mean or proportion. Students calculate margin of error and interpret it in context. Given data from a statistical experiment, students use simulation to create a randomization distribution and use it to determine if there is a significant difference between two treatments.
Applied Finite Mathematics covers topics including linear equations, matrices, linear programming, the mathematics of finance, sets and counting, probability, Markov chains, and game theory. Endorsed by CollegeOpenTextbooks.org.
This is a "first course" in the sense that it presumes no previous course in probability. The units are modules taken from the unpublished text: Paul E. Pfeiffer, ELEMENTS OF APPLIED PROBABILITY, USING MATLAB. The units are numbered as they appear in the text, although of course they may be used in any desired order. For those who wish to use the order of the text, an outline is provided, with indication of which modules contain the material.
This resource consists of a Java applet and expository text. The applet is a simulation of the ballot experiment: The votes in an election are randomly counted. The event of interest is that the winning candidate is always ahead in the vote count.
This resource consists of a Java applet and expository text. The applet is a simulation of Bertrand's experiment: a random chord on a circle The event of interest is whether the length of the chord is larger than the length of the inscribed equilateral triangle. Three models for generating the random chord can be used.
This resource consists of a Java applet and expository text. The applet illustrates Bayesian estimation of the probability of heads for a coin. The prior beta distribution, true probability of heads, and the sample size can be specified. The applet shows the posterior beta distribution.
This resource consists of a Java applet and expository text. The applet simulates a random sample from a beta distribution, and computes standard point estimates of the left and right parameters. The bias and mean square error are also computed.
This resource consist of a Java applet and expository text. The applet simulates Bernoulli trials in terms of coin tosses. The random variables of interest are the number of heads and the proportion of heads. The number of coins and the probability of heads can be varied. The applet illustrates the law of large numbers and the central limit theorem.
This resource consists of a Java applet and expository text. The applet simulates Bernoulli trials in terms of random points on a timeline. The random variables of interest are the number of successes and the proportion of successes. The number of trials and the probability of success can be varied. This applet illustrates the law of large numbers, the central limit theorem, and the binomial distribution.
Biology is designed for multi-semester biology courses for science majors. It is grounded on an evolutionary basis and includes exciting features that highlight careers in the biological sciences and everyday applications of the concepts at hand. To meet the needs of today’s instructors and students, some content has been strategically condensed while maintaining the overall scope and coverage of traditional texts for this course. Instructors can customize the book, adapting it to the approach that works best in their classroom. Biology also includes an innovative art program that incorporates critical thinking and clicker questions to help students understand—and apply—key concepts.
By the end of this section, you will be able to:Describe the scientific reasons for the success of Mendel’s experimental workDescribe the expected outcomes of monohybrid crosses involving dominant and recessive allelesApply the sum and product rules to calculate probabilities
This resource consists of a Java applet and expository text. The applet is a simulation of the birthday experiment: a sample of size n is chose at random and with replacement from the first m positive integers. The random variable of interest is the number of distinct sample values. The event of interest is that all sample values are distinct.
Try this fun problem! In any group of six people, what is the probability that everyone was born in different months?
This resource consists of a Java applet and expository text. The applet simulates the bivariate normal distribution. The means are set at 0, but the standard deviations and the correlation can be varied. Simulated points from the distribution are shown as dots in a scatterplot.
This resource consists of a Java applet and expository text. The Java applet illustrates the bivariate uniform distribution on three types of regions: a square, a circle, and a triangle. Simulated points from the distribution are shown as dots in a scatterplot.