Data Science Connectors
Data science connector courses give students the opportunity to apply their data acumen within their chosen major. There are a number of courses available for the connector courses.
Data Science Connectors (choose one of the following)
An introduction to the history, methods, theories, and principles of archaeology. This course covers essential archaeological approaches, methods and practices to answer such questions as: What is the material evidence that archaeologists collect and how do they analyze it in order to understand humans of the past, their social organization, economy, subsistence, diet, technology, trade, exchange, and symbol systems? How do geological, palaeoenvironmental, paleontological, and genetic evidence contribute to archaeological understandings of human biological and social evolution? What was the effect of environmental and climate change on human evolution and global dispersal? How are knowledge of the past, public archaeology, culture heritage preservation, and archaeological ethics used in the modern world? Prerequisite: ANTH 150 or permission of instructor.
Students acquire practical experience with astronomical equipment and data reduction techniques used in research and educational contexts. ASTR 596, combined with an independent research experience, provides a pathway for students to demonstrate creativity and integration of background knowledge. Prerequisite: Corequisite: ASTR 591.
Statistical concepts related to biological problems. Topics include the scientific method, data representation, descriptive statistics, elementary probability distributions, estimation and hypothesis testing, emphasizing the analysis of variation. Prerequisite: College algebra and ten hours of natural science.
An introduction to the nature of theory and theory building in the study of human communication. Research methods include experimentation, survey, content analysis, and field description. An introduction to statistics and statistical tests is included as well. Prerequisite: MATH 101 and admission to the Communication Studies major or consent of instructor.
Decisions link our thoughts to our actions and as a result define who we are and who people think we are. This makes decision making a fundamental life skill. But, can we make better decisions? This course will introduce you to the science of decision making that has developed as scholars including biologists, economists, mathematicians, philosophers, psychologists, and others have sought to answer this very question. Over the course of the semester we will examine what we have learned so far such as how people predict and mispredict events, how people make decisions and how their decisions can be quite irrational from one perspective but simultaneously appear quite reasonable, how people bargain and why they sometimes choose to cooperate and other times not, and why negotiating can be so difficult. (Same as PSYC 513.) Prerequisite: PSYC 104 or ECON 142; MATH 101 or MATH 103 or MATH 104, or eligibility for MATH 115 or MATH 125 or MATH 126.
An analysis of econometric forecasting techniques, including time-series models, single-equation regression models, and multiple-equation regression models. The course will examine forecasts of (a) macroeconomic variables, such as interest rates, investment, GNP, and the rate of inflation; and (b) market variables, such as price and quantity. Prerequisite: ECON 526 or ECON 715 or permission of instructor.
This course addresses research possibilities and ongoing debates in the field of Digital Humanities. Students will examine how digital technologies and methodologies can enhance or suggest new modes of Humanities research. The course focuses on core topics in the field, including text analysis, data visualization, digital mapping, archiving and (digital) cultural studies. We will take a hands-on and critical approach to investigating the benefits and limitation of different digital methods. Course assignments will consist of blog posts and mini projects conducted throughout the semester. At the end of the semester, students will develop a proposal for a project that brings digital methodologies to bear on a research inquiry related to the student's discipline. No prior experience in digital work or technical skills required. Prerequisite: Instructor permission.
An introduction to research methods for environmental science. The course includes fieldwork in diverse ecosystems (lakes, streams, forests, prairies). It emphasizes the development of skills in data analysis and interpretation that are essential to a full understanding of environmental issues. Enrollment limited to environmental studies majors, or by instructor permission. Prerequisite: Junior or Senior standing, completion of the natural sciences requirement of the KU Core (GE3N), and either EVRN 320 or EVRN 332.
This course is an introduction to cartography and focuses on computer-based map making skills. It begins with the history of cartography, cognitive maps, and the use of maps in the past and modern times. Topics covered in this course emphasize spatial data handling, principles of cartography and symbolization, map elements and design, and mapping techniques such as choropleth, proportional symbol and dot maps. Students will learn to adopt appropriate spatial data and mapping techniques to create accurate and creative digital maps reflecting given phenomena.
Introduces the benefits and limitations of using quantitative methods to analyze geographical problems. Covers traditional descriptive (e.g., measures of central tendency) and inferential statistics (e.g., hypothesis testing) but also inherently geographical approaches such as shape and point pattern analysis, and spatial autocorrelation. Laboratory emphasizes using the computer to explore and analyze geographical problems.
This course will prepare students to draw conclusions from data and statistical evidence, in order to generate insights, support managerial decisions, and communicate compelling stories. Students learn and practice all components of the data workflow, including accessing and collecting data, assessing the credibility of data, using spreadsheets to organize and analyze data, drawing inferences from data, and communicating data with text and visualizations. Must be completed with a grade of C (2.0) or higher to advance in the JMC curriculum. Prerequisite: JMC 302 with a grade of 2.0 or better. Students must be admitted to the School of Journalism and Mass Communications, journalism minor or in an approved concentration to enroll.
An introduction to the theory and practice of elementary symbolic logic. Special emphasis will be placed upon the logical analysis of mathematical proof and upon a proof of the consistency of elementary logic.
Experiments in electricity and magnetism, waves and sound. Students will practice data reduction and error analysis in ways that are consistent with professional ethics. Prerequisite: Corequisite: PHSX 212.
An introduction to the social science methods of investigation and analysis that are used in political science as a discipline and, in many cases, in public and private sector analytical work as well. The nature of political science data sources and methods of data collection, the logic of social scientific inquiry, and key methods of data analysis are emphasized. Prerequisite: POLS 110 or POLS 150 or POLS 170 (or their Honors equivalents), or consent of instructor.
This course allows student to learn the major software programs associated with data analysis in politics, including R and STATA. Students also learn the major sources of political and policy data. Students will conduct data collection and analysis for specific political research activities like public opinion surveys, voting behavior, Congressional behavior, comparisons of political processes in different countries, and the evaluation of public policies. Prerequisite: POLS 306.
This course focuses on the role of polling in the political process and introduces the theory and methods used in survey research. Topics include the role of polling in campaigns and the policy process, how survey research firms produce polls, analysis of polling for campaigns and public opinion, the psychology of survey response, survey construction, and sampling. Other data collection techniques commonly used in politics and political science such as focus groups and experiments will be covered. Students will conduct original surveys. Prerequisite: Junior level or consent of instructor.
Decisions link our thoughts to our actions and as a result define who we are and who people think we are. This makes decision making a fundamental life skill. But, can we make better decisions? This course will introduce you to the science of decision making that has developed as scholars including biologists, economists, mathematicians, philosophers, psychologists, and others have sought to answer this very question. Over the course of the semester we will examine what we have learned so far such as how people predict and mispredict events, how people make decisions and how their decisions can be quite irrational from one perspective but simultaneously appear quite reasonable, how people bargain and why they sometimes choose to cooperate and other times not, and why negotiating can be so difficult. (Same as ECON 513.) Prerequisite: PSYC 104 or ECON 142; MATH 101 or MATH 103 or MATH 104, or eligibility for MATH 115 or MATH 125 or MATH 126.
Lectures and laboratory work on human sensory processes and how they result in perceptions of the environment. Experience is provided in designing and implementing research as well as in the skills necessary for statistical analysis, interpretation of data, and scientific writing. Prerequisite: PSYC 104 and PSYC 210 or PSYC 211 or consent of instructor.
Lectures and laboratory work on psychophysiology and neuropsychology research methods. Overview of psychophysiological tools to measure the central and peripheral nervous systems. Experience designing and implementing neuropsychology and psychophysiology research. Prerequisite: PSYC 104 and PSYC 210 or PSYC 211 or consent of instructor.
An introduction to the nature and methods of social research, including both qualitative and quantitative approaches. Topics may include: hypothesis formulation and testing; how to design a research project, collect and analyze data; elementary statistical procedures; and ethical issues. Prerequisite: Six hours of Sociology credit, including SOC 104/SOC 105/SOC 304. A minimum GPA of 2.3 in all Sociology courses is strongly recommended for students planning to enroll in this course.
An analysis of how economic organizations such as firms and markets are embedded within broader social structures with attention being given to such topics as: world economic crises and their social bases; capitalist and socialist economies; primitive and advanced economic systems; multinational corporations; the nature of housework; and the transformation of economic systems.
*Pending approval, please submit a substitution request.