[Calculus Concepts And Contexts 4th Edition Pdf Download
Ainoha Sistek
In work on student understanding of concepts in advanced thermal physics, we are exploring student understanding of the mathematics required for productive reasoning about the physics. By analysis of student use of mathematics in responses to conceptual physics questions, as well as analogous math questions stripped of physical meaning, we find evidence that students often enter upper-level physics courses lacking the assumed prerequisite mathematics knowledge and/or the ability to apply it productively in a physics context. Our focus is in two main areas: interpretation of P-V diagrams, requiring an understanding of integration, and material properties and the Maxwell relations, involving partial differentiation. We have also assessed these mathematical concepts among students in multivariable calculus. Calculus results support the findings among physics students: some observed difficulties are not just with transfer of math knowledge to physics contexts, but seem to have origins in the understanding of the math concepts themselves.
To receive a bachelor's degree at Northern Arizona University, you must complete at least 120 units of credit that minimally includes a major, the liberal studies requirements, and university requirements as listed below.
Purpose Statement
Because the amount of global information collected is increasing rapidly due to technological advances, businesses and organizations that can utilize that information stand to benefit. Those organizations need people with the unique skillsets to store, access, and manipulate large sets of data; visualize and model relationships present; and draw actionable inference to make data-informed decisions.
Our students learn the fundamentals of computer science to facilitate the automation of tedious tasks, data storage, and algorithmic problem solving. They also learn statistical science foundations to inform data collection methods, model linear and non-linear relationships, and create predictive models. Students will be exposed to real data drawn from many different fields and have hands-on experience in how data insights are made.
Students with a Bachelor of Science degree in data science could pursue jobs as a business analyst, actuary, and data scientist for both public and private organizations in a diverse set of fields such as research, engineering, finance, marketing and public health.
Student Learning Outcomes
- Technical Skills: Graduates will demonstrate breadth and depth of knowledge of statistics and computer science necessary to continue onto graduate training or technical careers.
- Students will demonstrate mathematics competency by:
- Applying calculus concepts regarding rates of change.
- Applying matrices, matrix manipulations and related concepts (e.g. eigenvalues) to a statistical model.
- Selecting appropriate probability distributions to model a process and apply rules of probability to derive basic quantities.
- Students will demonstrate practical coding competency.
- Creating code scripts that solve a given problem and serve as documentation of how the solution was calculated.
- Applying common coding techniques (loops, user defined functions) to create complex software programs.
- Having proficiency with modern software development tools (e.g. debuggers, version control, profilers, IDEs).
- Students will demonstrate competency in data wrangling techniques by:
- Accessing data presented in a variety of formats (e.g CSV, Excel, SQL, JSON, HTML).
- Performing complex transformations and summarizations.
- Reshaping data into equivalent formats for use in subsequent analysis procedures.
Students will fit statistical and machine learning models to data by: - Use software to perform common statistical and machine learning analysis procedures (e.g. linear models, CART).
- Obtain appropriate diagnostic information to be able to asses model appropriateness.
- Make model predictions and uncertainty calculations for a variety of model quantities.
Students will summarize data and analysis results via numerical and graphics methods by: - Students will demonstrate mathematics competency by:
- Creating graphics of data that indicate analysis possibilities and relationships present.
- Create technical graphical summaries suitable for assessing model fit and appropriateness.
- Creating graphics that combine data and model results that are suitable for disseminating analysis results to domain area experts as well as the general public.
- Reasoning Skills: Graduates will demonstrate statistical and computational reasoning skills.
- Students will understand principles of data organization and storage and select appropriate schemes for data of varying size and organization.
- Students will evaluate the applicability of available data to address a desired research question.
- Students will choose among analysis methods based on the constraints of a study design and the scientific questions of interest.
- Students will be able to assess model fit to the data and propose model modifications to address observed deficiencies.
- Students will assess statistical significance of aspects of a proposed model and interpret the results in the situational context.
- Evaluate the trade-offs of various computation and inferential issues.
- Communication Skills: Graduates will collaborate with peers and communicate results and issues effectively in preparation for careers in industry, with government agencies, or in education.
- Explain computational issues, statistical methodology, and results by both written and oral means to both technical and non-technical audiences.
- Select and use of numerical, graphical, and narrative methods for conveying information to both technical and non-technical audiences.
- Effectively work in small technical groups.
The required coursework is in statistics and computer science with the upper-division statistics courses utilizing the program competency acquired. Students are encouraged to pursue a minor in another field of interest in order to gain deep understanding of the challenges and needs that can be addressed by data science.
You may take these remaining courses from any of the academic areas, using these courses to pursue your specific interests and goals. You may also use prerequisites or transfer credits as electives if they weren't used to meet major, minor, or liberal studies requirements.
We encourage you to consult with your advisor to select the courses that will be most advantageous to you.
This page summarizes the accessibility issues demonstrated in the Word, PDF, and PowerPoint sample files that accompany the Accessible University demo site. With each issue, a solution is suggested as demonstrated in the accessible files.
A workshop and facilitation guide to support B.C. post-secondary institutions to prevent and respond to sexual violence and misconduct. Accountability and Repairing Relationships is a series of four 90-minute workshops for individuals who have been informed that they have caused harm in the context of sexual violence. Designed for one-on-one or small group facilitation, learners are guided through information and reflection activities that help them recognize the harm they have caused, learn how to be accountable, and develop the skills needed to build better relationships and support a safe and healthy campus. (The slide deck that accompanies this resource can be downloaded from the Introduction).
Accounting Principles: A Business Perspective uses annual reports of real companies to illustrate many of the accounting concepts in use in business today. Gaining an understanding of accounting terminology and concepts, however, is not enough to ensure your success. You also need to be able to find information on the Internet, analyze various business situations, work effectively as a member of a team, and communicate your ideas clearly. This text was developed to help you develop these skills.
This course covers techniques for and critical thinking about the evaluation of changes in educational practices and policies in schools, organizations, and informal contexts. Topics include quantitative and qualitative methods for design and analysis, participatory design of practices and policies, institutional learning, the wider reception or discounting of evaluations, and selected case studies, including those arising from semester-long student projects.
Activity Sheet: This document provides an overview of how online education helps remove common barriers to accessing education, such as geographical restrictions, disabilities, scheduling conflicts, social stigma, and financial constraints. It uses simple icons and explanations to illustrate how the flexibility and accessibility of online learning platforms can expand educational opportunities to a broader range of students. This would be a useful resource for those exploring online education options, comparing modalities, or looking to increase enrollment through distance learning programs.
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