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Impara Intervals to Compare | The First A/B Test
A/B Testing in Python
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Contenuti del Corso

A/B Testing in Python

A/B Testing in Python

1. What is A/B Test?
2. The First A/B Test
3. Performing One More AB Test

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.

Compito

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.

Soluzione

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Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 2. Capitolo 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.

Compito

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.

Soluzione

Switch to desktopCambia al desktop per esercitarti nel mondo realeContinua da dove ti trovi utilizzando una delle opzioni seguenti
Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 2. Capitolo 6
Switch to desktopCambia al desktop per esercitarti nel mondo realeContinua da dove ti trovi utilizzando una delle opzioni seguenti
Siamo spiacenti che qualcosa sia andato storto. Cosa è successo?
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