Lesson 10   Qualitative and quantitative data

Lesson 10 Qualitative and quantitative data

Understanding Decision Making Through Data

The Importance of Data in Decision Making

  • Data is crucial for effective decision-making, as it helps answer various types of questions.
  • Two primary types of data discussed are quantitative and qualitative, each serving different purposes.

Quantitative vs. Qualitative Data

  • Quantitative Data: Focuses on numerical facts, answering "what," "how many," and "how often" questions (e.g., number of commuters using the train).
  • Qualitative Data: Describes subjective qualities that cannot be measured numerically, helping to answer "why" questions (e.g., preferences for a celebrity or snack).

Visualizing and Contextualizing Data

  • Quantitative data can be represented visually through charts or graphs, providing clear insights into trends.
  • Qualitative data adds context to these numbers, enhancing understanding of underlying reasons behind the data.

Application in Business Decisions

  • Customer reviews serve as an example where both quantitative and qualitative data are utilized to inform business decisions.
  • A local ice cream shop uses online reviews to gauge customer satisfaction and identify areas for improvement.

Analyzing Customer Feedback

  • The ice cream shop owner starts with measurable questions about negative reviews to gather quantitative data (e.g., average rating).
  • Identifying patterns in negative feedback reveals common frustrations among customers, leading to qualitative inquiries about their experiences.

Implementing Changes Based on Insights

  • By recognizing that customers are frustrated due to popular flavors running out, the shop can adjust its inventory accordingly.
  • Combining both quantitative and qualitative insights allows the owner to make informed changes that enhance customer satisfaction.

Conclusion: The Role of a Data Detective

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Google Data Analytics - Course 2 - Ask Questions to Make Data-driven Decisions Lesson 10 Qualitative and quantitative data