All language subtitles for 08 - Solution Summarize and analyze business data

(upbeat music)

- [Instructor] In the previous movie,

I described a set of challenges

working with the skills that you learned in Chapter 1.

Once again, we're working with 30 days of sales data,

and we can see that over here on the left

in columns A and B, I have the sales broken down by day

and you see that we do in fact

have 30 days of data.

In column D, I have a list of summaries

that I would like to perform and we can do that in column E.

So in cell E5, the first thing I want to do

is calculate the mean

or average of the values in column B.

So in E5, which I've already clicked,

I will type an equal sign.

And the average function is average.

And, again, that's also called the mean.

The range is B4 through B33,

and that won't be copying this formula

so I don't need to worry about absolute

or relative references.

Press Enter, and I see the average

is about $1,319.47 of sales per day.

If I were to sort those values into either ascending

or descending order, then I could calculate the median.

Because we have an even number of values, 30,

the median will be the average

of the two values in the middle, in positions 15 and 16.

So in E6, I'll type an equals sign.

And median is the function. B4 through B33.

Right parenthesis and enter.

And we see that the median is $1,285.50.

And that's very close to the mean

so that tells me that we don't have any outlying values.

There are no extremely large

or extremely small numbers in the data set.

If you want to find the maximum and minimum values,

then we can in cell E8 find the maximum.

So that's equal, max, left parenthesis

and then B4 to B33, Enter.

So the largest sales day had sales of 25.99.

And our minimum will be the smallest.

So equal min, which is the minimum function

and B4 through B33 and right parenthesis and Enter.

And the smallest was only 189.

So it's possible something untoward happened that day.

And it might be worth looking into

in terms of why sales were that low.

Next, we can calculate our quartiles.

The first quartile shows the cutoff

for where the lowest 25% of values will stop.

So in cell E10, I'll type an equals sign,

and then quartile.

And I will use exclusive, which does not include

the minimum and the maximum.

So I will make sure the quartile.exc is highlighted.

And then the array is B4 through B33, comma,

and then the first quartile.

So number one, right parenthesis and $1,072.25.

Now we can look at the third quartile

and that's where 25% of values are above it

and 75% below.

So I'll type an equals sign, quartile.exc,

same one we used before.

Then B4 through B33 and a comma.

And we'll look at the third quartile, 75%.

So type a three, right parenthesis and Enter.

And we get $1,569.75.

If we look at the median of 1,285.50

it fits nicely in the middle of the first quartile

and second quartile values.

Another way to analyze the spread of your data is

by calculating variance and standard deviation.

Variance, again, is the sum of the squared error

divided by the number of items in the list.

So I'll type equal and then var.

And I will use VAR.S, which is based on a sample.

And then the range, again, B4 through B33,

right parenthesis and Enter.

And we get 249,270.6.

The standard deviation is the square root of that value.

So I'll type an equals sign and STDEV.S.

Again, working with samples

which is a more conservative estimate.

And then B4 through B33, right parenthesis and enter.

And we get 499.27, which is the square root

of the variance that we had earlier.

And looking at our values, we're looking at the average

of 1,319.47, and with a standard deviation

of about 500, then one standard deviation above

would be about 1,800.

And one below would be about 800.

And given the range of values that we have,

with our maximum of almost 2,600 and our minimum of 189,

it looks like our standard deviation represents

the data in our collection pretty well.