1. Learn
    2. /
  2. Projects
    3. /
  3. Analyzing Marketing Campaigns with pandas
  • 1

    Pandas

    Free

    In this chapter, you will review pandas basics including importing datasets, exploratory analysis, and basic plotting.

  • 2

    Exploratory Analysis & Summary Statistics

    In this chapter, you will learn about common marketing metrics and how to calculate them using pandas. You will also visualize your results and practice user segmentation.

  • 3

    Conversion Attribution

    In this chapter, you will build functions to automate common marketing analysis and determine why certain marketing channels saw lower than usual conversion rates during late January.

  • 4

    Personalization A/B Test

    In this chapter, you will analyze an A/B test and learn about the importance of segmentation when interpreting the results of a test.

Initializing

Exercise

Evaluating statistical significance

Now that you know the personalization variant outperformed the control, it's time for you to determine whether the result is statistically significant. Remember, statistical significance is vital to understanding whether a test showed a positive result by chance or if it is reflective of a true difference between the variants. This will enable your marketing team to make an informed choice about whether to roll out the feature or not.

Test out the stats.ttest_ind() using control and personalization as the inputs.

Is the difference between the control and personalization statistically significant?

Instructions

50 XP

Possible answers