{"id":76802,"date":"2019-05-03T14:53:19","date_gmt":"2019-05-03T18:53:19","guid":{"rendered":"https:\/\/www.bu.edu\/academics\/?page_id=76802"},"modified":"2020-03-17T13:39:59","modified_gmt":"2020-03-17T17:39:59","slug":"quantitative-reasoning","status":"publish","type":"page","link":"https:\/\/www.bu.edu\/academics\/hub\/learning-outcomes\/quantitative-reasoning\/","title":{"rendered":"Quantitative Reasoning"},"content":{"rendered":"

The contemporary world demands competence in a broad array of quantitative skills, including the ability to interpret evidence, model complex systems, and draw valid inferences from data.<\/p>\n

On a daily basis, people evaluate quantitative evidence and arguments, for example, to assess risks, maximize returns, evaluate change, and interpret statistical models. While these quantitative skills are acquired primarily through the study of mathematical, statistical, and computational methods, quantitative reasoning is ubiquitous in all fields of study and all aspects of life. Beyond skills and methods for problem-solving, computational thinking has deep implications for understanding how the digital world works. Despite an ever-increasing potential for new insights and efficiency gains, algorithms\u2014processes or sets of rules to be followed in calculations or other problem-solving operations, especially by a computer\u2014can also amplify structural discrimination, produce errors that deny services to individuals, or mislead electorates. BU students should understand and use quantitative reasoning and interpret the role it plays in shaping their personal, professional, and civic lives. They must possess a fundamental understanding of the tools of quantitative reasoning and the ability to apply them to marshal, interpret, and analyze data to answer complex questions across a variety of settings. Developing a capacity for quantitative reasoning is crucial for personal self-sufficiency, professional advancement, and responsible citizenship.<\/p>\n

Quantitative Reasoning I<\/h3>
<\/p>\n

Learning experiences in this area enable students to acquire core concepts and tools for quantitative reasoning.<\/p>\n

Learning Outcomes<\/h3>\n
    \n
  1. Students will demonstrate their understanding of core conceptual and theoretical tools used in quantitative reasoning, such as statistics, computing, and mathematics.<\/li>\n
  2. Students will interpret quantitative models and understand a variety of methods of communicating them, such as graphs, tables, formulae, and schematics.<\/li>\n
  3. Students will communicate quantitative information symbolically, visually, numerically, or verbally.<\/li>\n
  4. Students will recognize and articulate the capacity and limitations of quantitative methods and the risks of using them improperly.<\/li>\n<\/ol>\n

    <\/div>\n<\/div>\n\n

    Quantitative Reasoning II<\/h3>
    <\/p>\n

    Courses in Quantitative Reasoning II build on previous college-level experience with quantitative reasoning. Learning experiences in this area enable students to frame and address complex problems using quantitative reasoning.<\/p>\n

    Learning Outcomes<\/h3>\n
      \n
    1. Students will frame and solve complex problems using quantitative tools, such as analytical, statistical, or computational methods.<\/li>\n
    2. Students will apply quantitative tools in diverse settings to answer discipline-specific questions or to engage societal questions and debates.<\/li>\n
    3. Students will formulate and test an argument by marshaling and analyzing quantitative evidence.<\/li>\n
    4. Students will communicate quantitative information symbolically, visually, numerically, or verbally.<\/li>\n
    5. Students will recognize and articulate the capacity and limitations of quantitative methods and the risks of using them improperly.<\/li>\n<\/ol>\n

      <\/div>\n<\/div>\n\n

      Note: For many students, taking a Quantitative Reasoning I course before a Quantitative Reasoning II course will be a logical sequence. However, depending on the course and on a student\u2019s background, this will not always be the case. Students are not required to take a Quantitative Reasoning I course prior to taking a Quantitative Reasoning II course. Additionally, a Quantitative Reasoning II course may be taken to fulfill the Quantitative Reasoning I requirement, allowing the student to use two Quantitative Reasoning II courses to fulfill this requirement.<\/p>\n","protected":false},"excerpt":{"rendered":"

      The contemporary world demands competence in a broad array of quantitative skills, including the ability to interpret evidence, model complex systems, and draw valid inferences from data. On a daily basis, people evaluate quantitative evidence and arguments, for example, to assess risks, maximize returns, evaluate change, and interpret statistical models. While these quantitative skills are […]<\/p>\n","protected":false},"author":1859,"featured_media":0,"parent":76786,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/76802"}],"collection":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/users\/1859"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/comments?post=76802"}],"version-history":[{"count":7,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/76802\/revisions"}],"predecessor-version":[{"id":79612,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/76802\/revisions\/79612"}],"up":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/pages\/76786"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/academics\/wp-json\/wp\/v2\/media?parent=76802"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}