> For the complete documentation index, see [llms.txt](https://fxy.mindey.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://fxy.mindey.com/sequential/03-statistical-basics.md).

# 03 - Statistical Basics

## Computing the mean

While computation of the mean is a subject as broad as life, we'll start with a simple average.

#### Data <a href="#user-content-data" id="user-content-data"></a>

Let's say we have a `blood-data.csv` file:

```
uid,date,variable,unit,value
1,2022-04-04T11:00Z,blood:glucose,mmol/l,5.34
2,2022-05-20T12:00Z,blood:glucose,mmol/l,4.74
3,2022-04-04T11:00Z,urine:glucose,mmol/l,4.12
4,2022-05-20T12:00Z,urine:glucose,mmol/l,4.11
```

Save it to the file, and let's read this data to a dataframe:

#### Statistics <a href="#user-content-statistics" id="user-content-statistics"></a>

**Read data**

```
$ fx

In [1]: import pandas
In [2]: df = pandas.read_csv('blood-data.csv')
```

**Computing the mean**

```
In [3]: df.value.mean()
Out [3]: 4.5775
```

This is literally `(5.34 + 4.74 + 4.12 + 4.11) / 4 = 4.5775`.

OK. Enough with the simple. Let's do some required sample size computations for hypothesis testing.