The impact of changing the standard deviation and mean is often lost. This demo visually shows the reason z-scores are necessary.

This lesson will be a review of skills for calculating mean, mode, median, and range of a set of numbers to be created by the students. It will result in a seasonal display for the classroom or school-wide bulletin board.

In this video segment from TV411, figure skaters compute their average daily practice time.

Students learn a simple technique for quantifying the amount of photosynthesis that occurs in a given period of time, using a common water plant (Elodea). They can use this technique to compare the amounts of photosynthesis that occur under conditions of low and high light levels. Before they begin the experiment, however, students must come up with a well-worded hypothesis to be tested. After running the experiment, students pool their data to get a large sample size, determine the measures of central tendency of the class data, and then graph and interpret the results.

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.

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.

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.

This module provides a solution sheet for the Hypothesis Testing: Single Mean and Single Proportion chapter of the Collaborative Statistics textbook/collection.

This module focuses on the solar wind information obtained by NASA-s Genesis spacecraft. Genesis collects pristine solar wind material -ionic particles from the Sun- that will provide clues about the elemental composition of the original solar nebula.

This module provides homework questions related to lessons on descriptive statistics. The original module by Dr. Barbara Illowsky and Susan Dean has been modified by Roberta Bloom. Some homework questions have been changed and/or added.

In this lesson, learners will practice graphing and statistically analyzing data. In the first part of the lesson, they will survey items in their homes that use energy; a worksheet is given to each learner that includes multiple choice questions related to energy consumption that will determine their energy audit scores. Depending on their grade level, learners will use all the audit scores from the group to find the mean, median, mode, range, upper quartile, or/and lower quartile. After the numbers have been analyzed, the group may review why it is important to reduce energy consumption and may think of ways to conserve energy. This lesson is standards-based and includes worksheets written in Chinese and resources for educators.

Students learn about the frequency range of human hearing by collecting data from a website simulation. They analyze the data to determine the typical range for students in their classroom. Students participate in a collaborative effort to gather scientific data on humans for use in designing an engineering product.

In this lesson, we're looking at the measures of central tendencies. The measures of central tendency provide us with statistical information about a set of data. The four primary measurements that we use are the mean, median, mode and range. Each one of these measurements can provide us with information about our data set. This information can then be used to define how the set of data points are connected.

Introduction to Statistics. Random Variable, Mean, Variance, Standard Deviation and Mathematical Expectation. Discrete Distributions: Bernoulli trials and Bernoulli distribution, geometric distribution, Poisson distribution. Continuous Distributions: random variables of the continuous type, uniform distribution, exponential distribution, gamma distribution, chi-square distribution, normal distribution, t-distributions. Estimation: biased and unbiased esimators, convidence intervals for means, convidence intervals for variances, sample size, maximum error of the point estimate, Likelihood function, Maximum Likelihood Estimation (MLE), Asymptotic Distributions of Maximum Likelihood Estimators, Chebyshev's Inequality. Hypothesis: tests of statistical hypotheses, Type I error, Type II error, tests about proportions, null hypothesis, alternative hypothesis, significance level of the test, probability value, tail-end probability, standard error of the mean, tests about one mean and one variance, test of the equality of two independent normal distributions, best critical region, Neyman-Pearson Lemma, most powerful test, uniformly most powerful critical region, Likelihood Ratio tests, critical region for the likelihood ratio test. Pseudo-Numbers: uniform pseudo-random variable generation, congruential generators, shift-register generators, Fibonacci generators, Combinations of Generators (Shuffling). The Inverse Probability Method for Generating Random Variables. The Logistic Distribution.

This lesson unit is intended to help you assess how well students are able to: Calculate the mean, median, mode, and range from a frequency chart; and to use a frequency chart to describe a possible data set, given information on the mean, median, mode, and range.

This item discusses the mean, variance and standard deviation

Highlight how changing a data set affects the mean, median, and mode with this tool (created by The Shodor Education Foundation and modified by The Concord Consortium) that allows you to add and delete data graphically.

This lesson shows how to determine the expected value of a random variable. [Probability playlist: Lesson 25 of 29]

This lesson involves students in collecting data, organizing data into a line plot, discussing statistics, calculating mean, median and mode and consumer awareness.