20809294Introduction to Data Analytics
Course Information
Description
This course is an introduction to data analytics, designed for beginners. Topics include data collection and cleaning, handling missing data, exploratory data analysis, basic statistical methods, and techniques for visualization of data.  Useful data science tools will be introduced, including Excel and SQL.
Total Credits
3
Course Competencies
  1. Evaluate the role of data organization and management in the research process
    Assessment Strategies
    Quizzes, exams, and/or writing assignments
    Criteria
    Distinguish the tasks of data collection, data organization/management, and data analysis
    Differentiate unit of observation and unit of analysis
    Construct a variable
    Differentiate the levels of measurement

  2. Construct and modify a dataset
    Assessment Strategies
    Quizzes, exams, writing assignments, and/or projects
    Criteria
    Assemble a dataset by inputting data into a spreadsheet
    Import a dataset into a data management/analysis tool
    Use data management/analysis software to manipulate and create variables in a dataset
    Perform checks to make sure the modifications were successful

  3. Evaluate the implications of missing data in a dataset
    Assessment Strategies
    Quizzes, exams, writing assignments, and/or projects
    Criteria
    Investigate whether there are patterns of missing data
    Appraise the methods used to address missing data

  4. Compile survey data
    Assessment Strategies
    Quizzes, exams, writing assignments, and/or projects
    Criteria
    Distinguish primary and secondary data
    Create a codebook for a survey
    Use an internet-based data collection tool to build a survey with skip patterns
    Perform checks to make sure the internet survey is collecting data properly

  5. Merge two datasets
    Assessment Strategies
    Quizzes, exams, writing assignments, and/or projects
    Criteria
    Use data management/analysis software to integrate cases and variables into an existing dataset
    Perform checks to make sure the data merge was successful

  6. Organize and summarize the results of data analysis
    Assessment Strategies
    Quizzes, exams, writing assignments, and/or projects
    Criteria
    Use data management/analysis software to generate frequency distributions and descriptive statistics for variables in a dataset
    Create a spreadsheet that summarizes the results of data analysis and displays the results according to the categories of one or more variables

  7. Visualize the results of data analysis
    Assessment Strategies
    Quizzes, exams, writing assignments, and/or a projects
    Criteria
    Choose the appropriate figures to visualize the results of data analysis
    Create tables and figures displaying the results of univariate, bivariate, and multivariate analyses
    Create tables and figures displaying trends

  8. Communicate the results of data analysis
    Assessment Strategies
    Oral Presentation
    Criteria
    Create a PowerPoint presentation with tables and figures that display the results of data analysis
    Deliver a verbal presentation to an audience
    Use language appropriate to the audience’s level of knowledge and understanding
    Respond to audience questions
    Engage in eye contact with audience members