The day-to-day collaboration between the researchers in Public Health and Biostatistics at the School reveals unified topics that cut across many applications. This series of presentations introduces the topics that show empirically to be most important in these collaborations; and emphasizes concepts over details, through recent applications in Public Health.

The students will use ACC basketball statistics to practice the process of converting fractions to decimals then to percents and will learn how to create and edit a spreadsheet. They will then use this spreadsheet to analyze their data. This unit is done during the basketball season which takes approximately 15 weeks from the middle of November to the middle of March. Teachers must have Clarisworks to open the sample spreadsheet in the lesson, but may recreate it in another spreadsheet program.

" In analyzing fiscal issues, conventional public finance approaches focus mainly on taxation and public spending. Policymakers and practitioners rarely explore solutions by examining the fundamental problem: the failure of interested parties to act collectively to internalize the positive externalities generated by public goods. Public finance is merely one of many possible institutional arrangements for assigning the rights and responsibilities to public goods consumption. This system is currently under stress because of the financial crisis. The first part of the class will focus on collective action and its connection with local public finance. The second part will explore alternative institutional arrangements for mediating collective action problems associated with the provision of local public goods. The objective of the seminar is to broaden the discussion of local public finance by incorporating collective action problems into the discourse. This inclusion aims at exploring alternative institutional arrangements for financing local public services in the face of severe economic downturn. Applications of emerging ideas to the provision of public health, education, and natural resource conservation will be discussed."

Students should discover how their height is related to their arm span. They will learn how to do spatial and visual estimation, use measuring tools, recognize factional parts of an inch, gather data, and organize and create a graph based on their findings.

This lesson plan creates a classroom database collecting information on books that students have read over a period of time determined by the teacher and/or students. By sorting and filtering, students evaluate the data and can later create other products from their findings.

Students learn about the practical uses, structure, mathematics and terminology of the binary number system. They learn how to convert a given number from the binary to the decimal number system and vice versa, and perform binary addition and subtraction as part of a class game. They use this understanding to build their own simple, mechanical "hard drive" a box that uses binary numbers to represent words for later retrieval. The activity helps students build an appreciation for the way that computers and electronics store and retrieve information.

Using this lesson worksheet, computers and a simple programming interface, students step through and build a simple program to sequentially calculate all of the variables in the Hardy Weinberg equations. By building the program in sequence it is hoped that students will learn the sequence to solve a Hardy Weinberg problem and appreciate the value and power of computer number crunching capabilities as well as sequential programming considerations.

By building a program to determine the valence of ANY element on the first three rows of the Periodic table, students learn the steps to solve the problem while learning how to program logic and think about processing data in sequence. NOTE: The worksheet includes the option of letting students create a bug that they have to fix.

The student will learn the mechanics of editing and compiling a simple program written in C++ beginning with a discussion of the essential elements of C++ programming: variables, loops, expressions, functions, and string class. Next, the student will cover the basics of object-oriented programming: classes, inheritance, templates, exceptions, and file manipulation. The student will then review function and class templates and the classes that perform output and input of characters to/from files. This course will also cover the topics of namespaces, exception handling, and preprocessor directives. In the last part of the course, the student will learn some slightly more sophisticated programming techniques that deal with data structures such as linked lists and binary trees. Upon successful completion of this course, students will be able to: Compile and execute code written in C++ language; Work with the elementary data types and conditional and iteration structures; Define and use functions, pointers, arrays, struct, unions, and enumerations; Write C++ using principles of object-oriented programming; Write templates and manipulate the files; Code and use namespaces, exceptions, and preprocessor instructions; Write a code that represents linked lists and binary trees; Translate simple word problems into C++ language. (Computer Science 107)

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 module provides data sets for use with the Collaborative Statistics textbook/collection. Data sets include a series of recorded motorcycle race and practice lap times as well as IPO stock prices.

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: Two Means, Paired Data, Two Proportions chapter of the Collaborative Statistics textbook/collection.

This video segment adapted from Discovering Women demonstrates how scientists use sound waves to collect data about the structure of Earth's crust.

In this lesson students will learn to collect data and organize the data into a chart using computer technology.

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.

The six-channel board for the TI EVM320C54 offers two channels of input and six channels of output at a sample rate of 44.1 kHz. It can also communicate with the PC via a serial port connection. The file thru6.asm exercises these inputs and outputs.

The lessons posted on this site were designed to engage students with real-world data relevant to content taught in middle school and high school science courses, and to foster an understanding of ways in which they might gather organize, analyze and interpret the data in order to draw scientifically valid inferences, interpretations and conclusions. Most of the labs use computer-based technology of spreadsheet programs or the Python programming interface. The Python lessons guide students in computational thinking to create simple programs to manipulate data. The lessons also provide students (and teachers) with instructions and guidance in the use of these technologies. Teacher and Student worksheets, as well as any supporting files, are linked to from links at the top of each lesson webpage as well as from the downloads page ("downloads" link on the scrolling menu to the left).