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  • Open Learning Initiative
Anatomy & Physiology
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You probably have a general understanding of how your body works. But do you fully comprehend how all of the intricate functions and systems of the human body work together to keep you healthy? This course will provide that insight. By approaching the study of the body in an organized way, you will be able to connect what you learn about anatomy and physiology to what you already know about your own body.

By taking this course, you will begin to think and speak in the language of the domain while integrating the knowledge you gain about anatomy to support explanations of physiological phenomenon. The course focuses on a few themes that, when taken together, provide a full view of what the human body is capable of and of the exciting processes going on inside of it.

Topics covered include: Structure and Function, Homeostasis, Levels of Organization, and Integration of Systems.

Note: This free course requires registration

Subject:
Anatomy/Physiology
Life Science
Material Type:
Activity/Lab
Assessment
Diagram/Illustration
Interactive
Reading
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
04/27/2023
Behavior of Sample Mean (1 of 3)
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Apply the sampling distribution of the sample mean as summarized by the Central Limit Theorem (when appropriate). In particular, be able to identify unusual samples from a given population.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
04/27/2023
Estimation
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Learning Objectives: 1).Determine point estimates in simple cases, and make the connection between the sampling distribution of a statistic, and its properties as a point estimator.
2). Explain what a confidence interval represents and determine how changes in sample size and confidence level affect the precision of the confidence interval.
3). Find confidence intervals for the population mean and the population proportion (when certain conditions are met), and perform sample size calculations.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
04/27/2023
Examining Distributions
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1). Summarize and describe the distribution of a categorical variable in context.
2). Generate and interpret several different graphical displays of the distribution of a quantitative variable (histogram, stemplot, boxplot).
3). Summarize and describe the distribution of a quantitative variable in context: a) describe the overall pattern, b) describe striking deviations from the pattern.
4). Relate measures of center and spread to the shape of the distribution, and choose the appropriate measures in different contexts.
5). Compare and contrast distributions (of quantitative data) from two or more groups, and produce a brief summary, interpreting your findings in context.
5). Apply the standard deviation rule to the special case of distributions having the "normal" shape.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
04/27/2023
Parameters vs. Statistics
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LEARNING OBJECTIVE: Identify and distinguish between a parameter and a statistic.

LEARNING OBJECTIVE: Explain the concepts of sampling variability and sampling distribution.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
04/27/2023
Public Policy Analysis for Engineers
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Public policy issues are important to every field of engineering. Yet, most engineering students know little about the topic. For most students, however, an entire course focused on the topic is not necessary. For example, a class on engineering design could incorporate a case study on 3D printing policy.

This course will introduce students to the interrelationship of engineering and public policy, how to conduct neutral policy analysis, and then apply that knowledge in case studies to practice the skills they have learned. The modules takes a flipped classroom/active learning approach by using short videos to educate students, activities to practice the skills taught, and incorporates real-world examples such as hydraulic fracturing, drones, and 3D printing.

Subject:
Applied Science
Engineering
Material Type:
Full Course
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
01/01/2015
STEM Foundations
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This course is design to support the development of foundational skills in workplace communication and mathematics that are used in various STEM careers. The course offers practice using workplace communication and math skills that are encountered in the workforce. The activities are designed to strengthen skills in preparation for entering a college program in a STEM career.

Subject:
Mathematics
Material Type:
Full Course
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
01/01/2013
STEM Readiness
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The STEM Readiness course provides a refresher of core skills related to STEM careers. The core skills covered are Mathematics from arithmetic to beginning algebra, Workplace Communications and Professionalism. The topics of the course are presented through workplace scenarios to show learners how these skills apply to their potential careers. In reviewing these core skills students will be better prepared to be successful in post-secondary STEM related technical programs and ultimately in STEM related careers.

Subject:
Applied Science
Material Type:
Full Course
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
01/01/2013
Sampling
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1). Identify the sampling method used in a study and discuss its implications and potential limitations.
2). Critically evaluate the reliability and validity of results published in mainstream media.
3). Summarize and describe the distribution of a categorical variable in context.

Subject:
Mathematics
Statistics and Probability
Material Type:
Module
Provider:
Carnegie Mellon University
Provider Set:
Open Learning Initiative
Date Added:
04/27/2023