This activity is designed for a primary classroom (outdoors & indoors) investigation where students collect and investigate soil samples and describe the soils, looking for similarities and differences. Students develop a method of recording the data colleted and can present the information gathered.

This activity is a field investigation where students gather data on physical changes of the ecosystem surrounding their school habitat.

Introduces the concepts, techniques, and devices used to measure engineering properties of materials. Emphasis on measurement of load-deformation characteristics and failure modes of both natural and fabricated materials. Weekly experiments include data collection, data analysis, and interpretation and presentation of results.

In this product, students engage in processes/activities for collaboration and communication strategies. Students compare risks of courses of action confronting NASA's Deep Impact mission team. Students investigate information necessary to support arguments, quantitative risk analyses, debate, role play, persuasive writing/communication skills and group decision making procedures. This activity has been aligned to the national math and science standards as well as math and science standards for California, Texas and Maryland.

This course in crystal structure refinement examines the practical aspects of crystal structure determination from data collection strategies to data reduction and basic and advanced refinement problems of organic and inorganic molecules.

" This course in crystal structure refinement examines the practical aspects of crystal structure determination from data collection strategies to data reduction and basic and advanced refinement problems of organic and inorganic molecules."

This module describes how missing data can be managed while maintaining data quality. It explains how to plan for missing data; defines different types of Ňmissingness;Ó outlines the benefits of documenting missing data and illustrates how to document missing data; and describes procedures to minimize missing data. Upon completion of this module, students will be able to explain why data managers should strive to minimize missing data and develop a plan to record or code why data are missing.

Detailed specification for Data Quality: Missing Data module.

Defines what Out of Range Values are and how to account for them in data collection and statistical analysis.Competencies/Skills that HIBB Addresses: Understand how to minimize out of range values when creating new data sets.

In Data Analysis: As Real World As It Gets, we feature resources for teaching about data and statistics as supported by the NCTM Standards (NCTM, 2000). Data collection and analysis can be an avenue into the meaningful mathematics and problem-solving skills needed by students in the twenty-first century. And an answer to the student question, Why do we have to study math? can be found when teaching mathematics with a real-world statistics approach.

Students will design and create a LEGO structure that will house and protect a temperature sensor. They will leave the structure in a safe spot and check the temperature regularly and chart it.

Regression analysis is an enormously popular and powerful tool, used ubiquitously in the social and behavioral sciences. Most courses on the subject immediately dive into the mathematical aspects of the subject and illustrate the technique on problems that are already highly structured. As a result, most students come away with little idea of the wide range of problems to which regression analysis can be applied and how to represent those problems in a way that cleverly utilizes readily available data. Few understand, at a conceptual level, the limitations of regression analysis. The OLI Empirical Research Methods course bridges the gap between the mathematical foundations of regression and its practical application. We teach students how to move from an interesting question about the world to a regression model that, when estimated, meaningfully addresses the question asked. It emphasizes causal analysis as the main research goal and multivariate linear regression as the main statistical tool. We teach a process that involves: Formulating a research problem, Developing and formalizing hypotheses, Collecting data relevant to these hypotheses, Analyzing the data using an appropriate regression model, and Critically interpreting the results of these analyses.

This activity is a investigation where students observe soil and rocks, record their similarities and differences, interpret their findings, and are guided to develop a new investigable question.

This activity is designed for a primary classroom (large area) investigation where students investigate sports equipment and decide what force; push or pull (twist) is used to put the object in motion. Students develop a method of recording the data colleted and can present the information gathered.

This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course.

Students will develop a personal lifeline which will include events from the past and present. Students will also be asked to think or dream about events in the future. Advise students that for this activity they can plan to live to be one hundred years old. They must include a minimum of five events from their past and seven events they see in their future.
This curriculum contains suggested activities to gradually move students toward a more futuristic and empathetic mind set. Students may discover that in many ways, their concerns and needs are similar to those of the aged -- feeling cared for and respected; having a sense of belonging, yet being independent; being treated fairly. The curriculum encourages and is greatly enhanced by student involvement in cross-generational relationships. The format allows for infusing "aging" into the established curriculum. It is designed to be used as interdisciplinary units. It affords teachers the freedom to adapt and enhance lessons according to subject matter, specific learner needs, and the community dynamics acting upon the attendance area served by the school.

Help scientists recover worldwide weather observations made by Royal Navy ships around the time of World War I. These transcriptions will contribute to climate model projections and improve a database of weather extremes. Historians will use your work to track past ship movements and the stories of the people on board.

Course provides an overview of the purposes and uses of outcome-based evaluation approaches and methods, and provides an opportunity to conduct a focused outcome evaluation of a user-focused service in a library, a nonprofit organization, an archive, a museum or other service-focused organization.
Objectives are to:

* Learn about approaches to outcome-based evaluation
* Identify and use context-centered methods for evaluating public information services
* Examine the role of evaluation in developing more effective information services
* Gain skill in identifying appropriate data collection and analysis methods
* Gain an understanding of recent developments in measurement and evaluation
* Read assigned readings and appropriate focused readings
* Plan and carry out a focused outcome-based evaluation project

Defines what Out of Range Values are and how to account for them in data collection and statistical analysis.Competencies/Skills that HIBB Addresses: Understand how to minimize out of range values when creating new data sets.