CISC127 Quantitative Data Analysis
Department of Science, Technology, Engineering & Mathematics: Computer/Information Science
- I. Course Number and Title
- CISC127 Quantitative Data Analysis
- II. Number of Credits
- 3 credits
- III. Number of Instructional Minutes
- 2250
- IV. Prerequisites
- Math Placement Test score of 5 or higher or MATH095 (C or better)
- Corequisites
- None
- V. Other Pertinent Information
- This course meets the General Education requirement for Quantitative Literacy.
- VI. Catalog Course Description
- This course is an in-depth study of spreadsheets used to perform calculations and communicate quantitative information. Topics include: worksheets and templates, functions and formulas, charts and graphs, business intelligence and data analysis tools, validating and auditing workbooks, sorting and filtering data, automation with macros, and database functions.
- VII. Required Course Content and Direction
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Course Learning Goals
Students will:
- create complex spreadsheets to effectively communicate quantitative information [Quantitative Literacy];
- use financial, lookup, statistical, and logical functions, and construct complex formulas, using absolute, relative, and mixed cell referencing [Quantitative Literacy];
- analyze data with appropriate graphs and charts [Quantitative Literacy];
- validate data and audit a worksheet for errors;
- solve "what if," "goal-seek," and other problems, using built-in data analysis and business intelligence tools;
- write macros, which eliminate detailed repetitive routine; and
- create a database and perform data manipulation, including sorting and extraction of data.
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Planned Sequence of Topics and/or Learning Activities
- Creating and Formatting a Worksheet
- Absolute, Relative, and Mixed Cell Referencing
- Formulas and Functions
- Charts, Sparklines, and Graphs
- Data Validation and Auditing Worksheets
- Creating Tables
- Conditional Formatting
- Defined Names
- Sorting and Filtering
- Creating and Using Templates
- Business Intelligence (BI) and Data Analysis Tools
- PivotTables and PivotCharts
- Building Complex Functions
- Macros and Visual Basic for Applications
- Database Functions
- Collaborating with Others and Preparing a Workbook for Distribution
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Assessment Methods for Course Learning Goals
The assessment of Course Learning Goals is based on written tests, labs, and other assignments, as well as performance-based tasks as appropriate, and a departmental final exam. -
Reference, Resource, or Learning Materials to be used by Student:
Departmentally-selected textbook and other learning materials. Details provided by the instructor of each course section. See course syllabus.
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Review/Approval Date - 9/98; Revised 10/2010; New Core 8/2015; Name Change 11/21/2019