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Learn Intervals to Compare | The First A/B Test
A/B Testing in Python

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Intervals to Compare

In the previous chapter, we created 2 plots. We can also create 2 confidence intervals for these groups.

A confidence interval is the mean of your estimate plus and minus the variation in that estimate. This is the range of values you expect your estimate to fall between if you redo your test, within a certain level of confidence. Confidence, in statistics, is another way to describe probability.

Tu build them use scipy.stats.t.interval(alpha, data, loc, scale). In our case we will use alpha equals 0.95(you may also choose 0,99, but you will need to compare the p-value with 0,01 thus), the data.shape[1] as a data, loc = data.clicks.mean() and scale = scipy.stats.sem(data.clicks).

If intervals cover each other a lot, 2 groups don't differ a lot => the new version of the site doesn't make any big changes.

Task

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  1. Build the confidence interval for the df_control using the information from the NOTE in the theory.
  2. Build the confidence interval for the df_test.

Solution

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SectionΒ 2. ChapterΒ 6

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book
Intervals to Compare

In the previous chapter, we created 2 plots. We can also create 2 confidence intervals for these groups.

A confidence interval is the mean of your estimate plus and minus the variation in that estimate. This is the range of values you expect your estimate to fall between if you redo your test, within a certain level of confidence. Confidence, in statistics, is another way to describe probability.

Tu build them use scipy.stats.t.interval(alpha, data, loc, scale). In our case we will use alpha equals 0.95(you may also choose 0,99, but you will need to compare the p-value with 0,01 thus), the data.shape[1] as a data, loc = data.clicks.mean() and scale = scipy.stats.sem(data.clicks).

If intervals cover each other a lot, 2 groups don't differ a lot => the new version of the site doesn't make any big changes.

Task

Swipe to start coding

  1. Build the confidence interval for the df_control using the information from the NOTE in the theory.
  2. Build the confidence interval for the df_test.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 2. ChapterΒ 6
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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