Introduction to Data Analysis

$129.00

Professionals in all industries rely on data to make decisions. By including data in your decision-making process, you can remove some of the guesswork that comes from relying solely on instincts and experience. This course will introduce you to the world of data analysis by exploring the Davenport-Kim three-stage model for quantitative analysis. You will learn about different analytical methods, data quality and management, and visual representations of data. You will also explore research standards and best practices, as well as challenges that may arise as you analyze data. This course will provide you with information you can use to better understand data and its importance in the business world.

Professionals in all industries rely on data to make decisions. By including data in your decision-making process, you can remove some of the guesswork that comes from relying solely on instincts and experience. This course will introduce you to the world of data analysis by exploring the Davenport-Kim three-stage model for quantitative analysis. You will learn about different analytical methods, data quality and management, and visual representations of data. You will also explore research standards and best practices, as well as challenges that may arise as you analyze data. This course will provide you with information you can use to better understand data and its importance in the business world.

Credits

  • 0.5 IACET CEUs

  • 5 HRCI Credits

  • 5 SHRM PDCs

  • 5 PMI PDUs:

    • 2 Ways of Working PDUs

    • 2 Power Skills PDUs

    • 1 Business Acumen PDUs

Learning Outcomes

  • Explain the value of analytics for an organization and define key terms related to data analysis

  • Explain the stages of the Davenport-Kim three-stage model for analysis

  • Describe different data collection methods

  • Differentiate between qualitative and quantitative data

  • Explain standard analytical techniques

  • Describe the characteristics of high-quality data

  • Describe the elements of data management

  • Identify possible biases and errors within a data set

  • Describe different graphical displays for a data set

  • Describe common challenges associated with data analysis

Refund Policy

You may request a refund up to 7 days from the purchase date. The registration fee will only be refunded if less than 10% of the course has been completed. Completion percentage can be viewed on the Course Progress page from within the course.

Notes

Estimated time to complete: 5 hours

Access Time: 90 days

This course includes an “Ask the Expert” feature. You can use this feature to submit questions about course content. A subject matter expert will provide guidance or point you to additional resources for the topics you’re studying. Questions are answered as quickly as possible and usually within 24 hours.