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Here, we've got the average
order value per user.

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00:00:04,590 --> 00:00:08,420
What if we wanted to display
more statistics for us, or for

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00:00:08,420 --> 00:00:10,550
someone else to analyze?

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00:00:10,550 --> 00:00:15,320
For example, you might want to find
a record with the largest value, like

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00:00:15,320 --> 00:00:20,860
the most expensive item in the store, or
the highest paid employee in the company.

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00:00:20,860 --> 00:00:27,550
Let's use another common set of functions
to get the maximum and minimum values.

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00:00:27,550 --> 00:00:33,590
We can use the max and the min functions
to find the maximum and minimum values.

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00:00:33,590 --> 00:00:35,270
It works just like average.

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00:00:36,550 --> 00:00:40,483
Let's add these two functions
to our select statement.

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00:00:40,483 --> 00:00:50,112
First, MAX(cost) AS Maximum,

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00:00:50,112 --> 00:00:59,353
then MIN(cost) AS Minimum.

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00:01:00,870 --> 00:01:08,220
Look at the column in the average,
maximum, and minimum functions.

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00:01:08,220 --> 00:01:12,470
Notice that how each of
the functions use the same column.

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00:01:12,470 --> 00:01:14,051
That's something you can do.

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00:01:14,051 --> 00:01:17,717
You can include as many functions
of printing on the same

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00:01:17,717 --> 00:01:21,440
column as many times as
you like on any query.

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00:01:21,440 --> 00:01:25,852
This enables you to generate more
compelling reports in a single query

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00:01:25,852 --> 00:01:30,201
without running multiple queries
to get each piece of information.

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00:01:35,662 --> 00:01:37,600
Also, don't forget your commas.

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00:01:40,280 --> 00:01:45,350
These numeric functions are powerful
tools, and simple to use.

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00:01:45,350 --> 00:01:46,000
You can use them,

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00:01:46,000 --> 00:01:50,460
not only for currency related queries,
but things such as user ratings.

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00:01:51,560 --> 00:01:55,860
You can get average reviews for
movies in a movie database.

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00:01:55,860 --> 00:02:00,570
You can count each of the reviews
by the value given like on Amazon.

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00:02:00,570 --> 00:02:03,270
Showing the customer's
distribution of ratings

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helps inform the customer on whether or
not they should make a purchase.