Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Aprende Intervals to Compare | The First A/B Test
A/B Testing in Python

Desliza para mostrar el menú

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.

Tarea

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.

Solución

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 2. Capítulo 6

Pregunte a AI

expand
ChatGPT

Pregunte lo que quiera o pruebe una de las preguntas sugeridas para comenzar nuestra charla

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.

Tarea

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.

Solución

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 2. Capítulo 6
Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Lamentamos que algo salió mal. ¿Qué pasó?
some-alt