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.

Few people are aware of how crucial the sense of smell is to identifying foods, or the adaptive value of being able to identify a food as being familiar and therefore safe to eat. In this lesson and activity, students conduct an experiment to determine whether or not the sense of smell is important to being able to recognize foods by taste. The teacher leads a discussion that allows students to explore why it might be adaptive for humans and other animals to be able to identify nutritious versus noxious foods. This is followed by a demonstration in which a volunteer tastes and identifies a familiar food, and then attempts to taste and identify a different familiar food while holding his or her nose and closing his or her eyes. Then, the class develops a hypothesis and a means to obtain quantitative results for an experiment to determine whether students can identify foods when the sense of smell has been eliminated.

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 provides a solution sheet for the Hypothesis Testing: Two Means, Paired Data, Two Proportions chapter of the Collaborative Statistics textbook/collection.

In the first part of the activity, each student chews a piece of gum until it loses its flavor, and then leaves the gum to dry for several days before weighing it to determine the amount of mass lost. This mass corresponds to the amount of sugar in the gum, and can be compared to the amount stated on the package label. In the second part of the activity, students work in groups of four to design and conduct new experiments based on questions of their own choosing. These questions arise naturally from observations that occur during the first experiment, and from students' own experiences with and knowledge of the many varieties of chewing and bubble gums available.

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.

Gain practical insight and improved understanding of engineering experimentation through design and execution of "project" experiments. Building upon work in 16.621, students construct and test equipment, make systematic experimental measurements of phenomena, analyze data, and compare theoretical predictions with results. Written final report on entire project and formal oral presentation. Includes instructions on oral presentations. Provides valuable link between theory and practice.

Introduces laboratory experimental techniques. Principles of experimental design and reliable measurement. Laboratory safety. Instruction in effective report writing and oral presentation, including revision of written work. Selection and detailed planning of an individual research project, including design of components or equipment. Preparation of a detailed proposal for the selected project carried through to completion under 16.622.

To apply conceptual knowledge, to arrive at conclusions and to dare make predictions

In this lesson and its associated activity, students conduct a simple test to determine how many drops of each of three liquids can be placed on a penny before spilling over. The three liquids are water, rubbing alcohol, and vegetable oil; because of their different surface tensions, more water can be piled on top of a penny than either of the other two liquids. However, this is not the main point of the activity. Instead, students are asked to come up with an explanation for their observations about the different amounts of liquids a penny can hold. In other words, they are asked to make hypotheses that explain their observations, and because middle school students are not likely to have prior knowledge of the property of surface tension, their hypotheses are not likely to include this idea. Then they are asked to come up with ways to test their hypotheses, although they do not need to actually test their hypotheses. The important points for students to realize are that 1) the tests they devise must fit their hypotheses, and 2) the hypotheses they come up with must be testable in order to be useful.

Most of the flavoring in gum is due to the sugar or other sweetener it contains. As gum is chewed, the sugar dissolves and is swallowed. After a piece of gum loses its flavor, it can be left to dry at room temperature and then the difference between its initial (unchewed) mass and its chewed mass can be used to calculate the percentage of sugar in the gum. This demonstration experiment is used to generate new questions about gums and their ingredients, and students can then design and execute new experiments based on their own questions.

In this segment from Curious, learn how a robot is a machine that can connect with its surroundings and has some level of autonomy.

This activity will allow students to observe the orientation behavior of several organisms and practice formulating and testing hypotheses based on their observations.

Unfamiliar objects make us curious to know what they are. To make a proposed explanation --a hypothesis-- about something unfamiliar, archaeologists use the skills of observation and inference.

Short Description: This is an inquiry investigation, geared toward student use of outdoor schoolyard sites. Its focus is to have students applying what they've learned about the scientific method and experimental design, gathering quantitative evidence to support hypotheses.

Reaction time has many advantages for the introduction of the scientific method--the subject is familiar, many experiments are possible, and students enjoy competition. In our Introductory Biology courses, our students formulate and test a hypothesis about reaction time. We use Kosinski's Reaction Time software, that records reaction times and then analyzes them statistically using the chi-square median test. Students then write a paper that either rejects or fails to reject their null hypothesis. An online literature review on reaction time helps the students incorporate primary literature into their paper.