12 courses with the subject QMBE, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
QMBE 1010Microsoft Excel Associate Certification1
Goals: To enable students to achieve certification in Microsoft Excel at the Associate level. Content: This online course is structured as a self-tutorial with instructor support. Offered only Pass/Fail with Pass achieved by passing the proficiency exam at a Certiport center. Credits obtained cannot be used toward the requirements for the Business Analytics concentration but are counted towards breadth of study. This course is open to all Hamline students, independent of major or minor area of study. Please
Goals: To enable students to achieve certification in Microsoft Excel at the Expert level. Content: This course is structured as a self-tutorial with instructor support. Offered only Pass/Fail with Pass achieved by passing the proficiency exam at a Certiport center. Credits obtained cannot be used toward the requirements for the Business Analytics concentration but are counted towards breadth of study. This course is open to all Hamline students, independent of major or minor area of study. Please
Crosslisted: Also listed as CDS 1100 Goals: To introduce R and RStudio, in preparation for courses in analytics and economics. By the end of this course, students will be able to import data, understand data types, manage data, and generate basic statistical output. Content: In this course you will learn how to program in R, in preparation for courses that use R for data analysis. You will learn how to install and configure software necessary for a statistical programming environment and learn the basics of importing and managing data.
Crosslisted: Also listed as CDS 1130 Goals: To introduce basic design principles for data visualization and interpretation. By the end of this course, students will be able to produce appropriate visualizations for a variety of types of data, including multivariate, temporal, text, and spatial data. Students will also learn to interpret data visualizations, use them in discussing the issues of the current world, and discuss the limitations of various visual representations of data. Content: Students will learn the fundamentals of data visualization, including figure design, figure making, and figure review. Students will apply these skills to a domain-specific and data-driven project to produce a poster, infographic, or webpage that conveys the primary conclusions inferred from the data.
CDS 1100/ QMBE 1100, grade of C- or higher, or concurrent enrollment Credits: 2
QMBE 1310Statistics4
Goals: To acquaint students with major parametric and nonparametric statistical techniques. Content: Data organization, simple probability, and sampling distributions; estimation and hypothesis testing; regression and correlation; time series; selected non parametric tests.
None, though a basic understanding of algebra is expected.
QMBE 1320Introduction to Business Analytics4
Goals: To introduce frequently used data analysis techniques, to develop the quantitative skills necessary to use them, and to apply the methods in business decision-making settings. Content: The course will cover decision-making frameworks as well as data capture, analysis and presentation techniques. Topics such as budgeting, forecasting and regression will be explored using Excel and other relevant software or analytical tools.
QMBE 1310 (or equivalent statistics course), grade of C- or higher Credits: 4
QMBE 3510Mapping, Spatial Analysis, and Social Issues4
Crosslisted: Also listed as ECON 3510 Goals: Students will learn to conceptualize social issues within a spatial framework by practicing a variety of analytical methods. They will gain experience with managing and manipulating spatial data to perform both descriptive analyses as well as hypothesis testing on an original research question. Content: This class will focus on introducing students to spatial analysis while also providing an entry point to using the industry-standard software package for GIS (ArcGIS). While learning the basics of data manipulation and management, students will be challenged to think about spatial or locational components to data generating processes. We will examine the best way to measure the clustering we observe in measurements of household income, educational attainment, air quality, or crime reports, for example. Students will learn to both take advantage of spatial aspects of data and recognize when conventional analysis might be misleading due to the presence of geographic correlation. We will also spend time on map design and effective presentation of analyses based on spatial data.
MATH 1200 or QMBE 1310, grade of C- or higher Credits: 4
QMBE 3720Decision Science4
Goals: To introduce students to decision-making analysis, stressing problem formulation, analytical methods for solution, and use of computer models. Content: Decision theory, linear programming, simulation, and implementation.
QMBE 1320 and MGMT 3100, grades of C- or higher Credits: 4
QMBE 3730Advanced Business Analytics4
Goals: To enable students to utilize advanced mathematical models and data analysis techniques. Content: This course picks up where QMBE 1320 leaves off, with more sophisticated models and new analytical techniques. Time permitting, topics covered will include a deeper look into optimization and spreadsheet models, multivariate regression, nonlinear regression, models of causation, and time series/forecasting. Taught: Yearly, spring semester
QMBE 1100 and QMBE 1320, grades of C- or higher Credits: 4
QMBE 3740Data Mining4
Goals: Introduce students to data mining techniques and best practices. Content: This course includes classification, prediction, data reduction, and data visualization. Advanced regression, network and cluster analysis. Taught: Alternate Years
QMBE 1100 or QMBE 1130; and QMBE 1320 or CDS 1010; and QMBE 1310 or MATH 1200, with grades of C- or higher Credits: 4
QMBE 3750Data Management and Communication4
Goals: To build a strong foundation in data organization, and management (i.e., “data wrangling”) as well as reporting, visualization, and communication to non-technical audiences. Content: Businesses today operate in a very complex environment, with more data available than ever before. Students will build skills in using data management and visualization tools (including SQL and Tableau), and consider approaches to professional data representation and communication.
QMBE 1310 (or equivalent statistics course) and QMBE 1320 or CDS 1010, with grades C- or higher Credits: 4
QMBE 3770Marketing Data Analysis4
Crosslisted: Also listed as MKTG 3770 Goals: To introduce students to data-centered analysis for critical aspects of marketing. Content: Topics covered include sales forecasting, profitability analysis, market segmentation, promotion budgeting, and database marketing. Students will cover essential decision models and metrics with data sources and techniques for effective marketing decisions.
