Sampling

This module explores a variety of sampling schemes. Students create a factory, ship lots, and determine if their sample is representative of the whole. They see the cost of mistakes and dip into the world of statistical process control. Lesson 1 Census versus Survey Students define a census and a survey. They compare and contrast different types of data gathering. Lesson 2 Sample Error Students explore the types of errors present in samples and use a "Margin of Error" table to discuss reliability of a survey. Actual cases studies are used to illustrate sampling error. Lesson 3 Summarizing Our Product's Characteristics Students begin creating a "factory" to produce a product that they will analyze using samples in later lessons. The product is a "package" of M&M's with appropriate color proportions. Lesson 4 The Normal Approximation of a Binomial Distribution Students investigate the behavior of events where the only two choices are either the absence or presence of a desired characteristic. When probability of choosing the desired characteristic is known, students discover that the behavior of the distributions are Normal or "Bell" shaped with a predictable mu and sigma. Lesson 5 Characteristics of Samples Students "operate" their M&M "factories" and produce packages of M&M's. They sample their product and summarize characteristics of these samples to discover the behavior of samples taken from a Normal population. Lesson 6 Control Charts Students investigate Statistical Process Control (SPC) which is a quality control technique used in the manufacturing industry. They chart their sample means from their M&M "factory" on a Control Chart and monitor the operation of a good & bad factory process using the Control Chart. Lesson 7 SPC in a Semiconductor Factory Students were introduced to SPC using the M&M "factory" that they ran themselves. In this lesson they walk through a more real-life application of SPC in the saw room of a semiconductor manufacturing company. Lesson 8 How Defects Affect Profitability Students investigate the relationship between defect levels and profit. They determine a linear model for profit as a function of defects for a scenario involving M&M's products. Lesson 9 Deming's All or Nothing Acceptance Sampling Scheme Students are introduced to some fundamental quality control concepts developed by a well known contributor in this field, Edward Deming. Students explore scenarios where it is either better to test every product so that only good products are shipped to customers or ship all products to the customer and let the customer return the defective ones for repair. Compare this module to traditional course topics in the Matrix of Course Competencies. If one of the lessons has a link, you can preview that lesson. Other modules: Beat Ratios Functions Exp. Growth Data & Graphs Representing Data Finance Geometry Sampling Non-linear Behavior Linear Behavior Sets and Logic Patterns Probability Systems Right Tri. Trig.