Every day, millions of users across the world download all sorts of apps to their phones.

For this exercise, well consider a user active on an app if they used it at all during that period of timeeven if using it just once or for the first time, and no matter how briefly.

Following this approach, given a date and time T, we can define an apps:

• Daily Active Users (DAUs) at T as the number of unique users that have been active during the 24 hours ending at T
• Monthly Active Users (MAUs) at T as the number of unique users that have been active during the 30 days ending at T
• Yearly Active Users (YAUs) at T as the number of unique users that have been active during the 365 days ending at T

For example, if 100 different people used app A on November 19, 2019, then app A had 100 DAUs at midnight of that day. When we write about an apps DAUs at a certain, imprecisely defined time (e.g., at the beginning of 2018) or during a period of time (e.g., in February 2019), we generally mean the average DAUs around that time or during that period. This can be quite convenient and accurate enough in most practical cases.

Going from DAUs to MAUs and YAUs isnt obvious, as the calculation depends on the users activity patterns. For instance, lets say that during month X, the very same people active on a particular day Y of that month are active every day of the monthand no one else is active. It follows that the MAUs at the end of month X will be equal to the DAUs at the end of day Y. But things arent as straightforward if different people are active on the various days of month Xwhich is what tends to happen in practice.

Question 1: Which of the following statements are true? Select all that apply.

Given a date and time T, an app can never have fewer YAUs than MAUs at T

Given a date and time T, an app can have more than 30 times as many MAUs than DAUs at T

The DAUs for an app at two different dates and times T1 and T2 will always be the same

For an app whose active user base is growing (i.e., the apps DAUs increase with every passing day), the ratio MAUs/DAUs at a date and time T during that period of growth will generally be higher than the same ratio for an app whose user base is flat