Students act as R&D entrepreneurs, learning ways to research variables affecting the market of their proposed (hypothetical) products. They learn how to obtain numeric data using a variety of Internet tools and resources, sort and analyze the data using Excel and other software, and discover patterns and relationships that influence and guide decisions related to launching their products. First, student pairs research and collect pertinent consumer data, importing the data into spreadsheets. Then they clean, organize, chart and analyze the data to inform their product production and marketing plans. They calculate related statistics and gain proficiency in obtaining and finding relationships between variables, which is important in the work of engineers as well as for general technical literacy and decision-making. They summarize their work by suggesting product launch strategies and reporting their findings and conclusions in class presentations. A finding data tips handout, project/presentation grading rubric and alternative self-guided activity worksheet are provided. This activity is ideal for a high school statistics class.

This lesson defines correlation as the relationship between variables presented on a scatter plot. This is part of a series of lessons about topics related to scatter plots. It is 2 of 9 in the series titled "Correlation.' [3:31]

This lesson defines correlation as the relationship between variables presented on a scatter plot. This is part of a series of lessons about topics related to scatter plots. It is 3 of 9 in the series titled "Correlation." [2:04]

This lesson will introduce correlation and correlation coefficient. It is 7 of 9 in the series titled "Correlation." [9:59]

This lesson will introduce correlation and correlation coefficient. It is 8 of 9 in the series titled "Correlation." [9:52]

This lesson will introduce correlation and correlation coefficient. It is 9 of 9 in the series titled "Correlation." [9:00]

This lesson will introduce the connection between correlation and causality. It is 1 of 4 in the series titled "Correlation and Causation." Includes short quiz. [5:19]

This lesson will introduce the connection between correlation and causality. It is 2 of 4 in the series titled "Correlation and Causation." Includes short quiz. [6:14]

This lesson will introduce the connection between correlation and causality. It is 4 of 4 in the series titled "Correlation and Causation." Includes short quiz. [3:02]

Understanding why correlation does not imply causality (even though many in the press and some researchers often imply otherwise).

Khan Academy learning modules include a Community space where users can ask questions and seek help from community members. Educators should consult with their Technology administrators to determine the use of Khan Academy learning modules in their classroom. Please review materials from external sites before sharing with students.

Demonstrates how to find the line of best fit for a scatter plot. [1:17]

Khan Academy learning modules include a Community space where users can ask questions and seek help from community members. Educators should consult with their Technology administrators to determine the use of Khan Academy learning modules in their classroom. Please review materials from external sites before sharing with students.

Students graph scatter plots and understand the concepts of correlation and least-squares regression. They also perform transformations to achieve linearity in the data plot.

In this activity, students test if a significant relationship exists between a bivariate data set, and then calculate the confidence and predictive intervals. They also improve the interval-prediction capabilities by automating the process.

Introduction to Sociology 2e adheres to the scope and sequence of a typical, one-semester introductory sociology course. It offers comprehensive coverage of core concepts, foundational scholars, and emerging theories, which are supported by a wealth of engaging learning materials. The textbook presents detailed section reviews with rich questions, discussions that help students apply their knowledge, and features that draw learners into the discipline in meaningful ways. The second edition retains the book’s conceptual organization, aligning to most courses, and has been significantly updated to reflect the latest research and provide examples most relevant to today’s students. In order to help instructors transition to the revised version, the 2e changes are described within the preface.

Differentiate between four kinds of research methods: surveys, field research, experiments, and secondary data analysis
Understand why different topics are better suited to different research approaches

This QuickTime movie provides an opportunity to create a data table by analyzing a scatter plot. As you watch and listen to the teacher and student interact it helps clarify the thinking behind applying this concept.

Excellent, comprehensive site on multiple regression. Key terms are defined and explained as needed. Links to relevant topics are provided.

Based off of the hit television show NUMB3RS, this lesson has students create box-and-whisker plots for given data, and then determine which (if any) data points are outliers. Students determine outliers through two methods in this lesson: recognizing points that are significantly "far" from the quartiles on the box-and-whisker, and also by observing differences in the correlation of a scatterplot when possible outliers have been removed from the data set. Students practice both of these methods in this calculator-intensive lesson.

Psychology is designed to meet scope and sequence requirements for the single-semester introduction to psychology course. The book offers a comprehensive treatment of core concepts, grounded in both classic studies and current and emerging research. The text also includes coverage of the DSM-5 in examinations of psychological disorders. Psychology incorporates discussions that reflect the diversity within the discipline, as well as the diversity of cultures and communities across the globe.Senior Contributing AuthorsRose M. Spielman, Formerly of Quinnipiac UniversityContributing AuthorsKathryn Dumper, Bainbridge State CollegeWilliam Jenkins, Mercer UniversityArlene Lacombe, Saint Joseph's UniversityMarilyn Lovett, Livingstone CollegeMarion Perlmutter, University of Michigan