DOC: Different behaviour with respect to `Series.all` docs when `NA` values are present
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
In[29]: s = pd.Series([None, None, None], dtype=pd.BooleanDtype())
In[30]: s
Out[30]: 
0    <NA>
1    <NA>
2    <NA>
dtype: boolean
In[31]: s.all(skipna=True)
Out[31]: True
In[32]: s.all(skipna=False)
Out[32]: <NA>
```

#### Problem description
The [documentation](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.all.html) says:
```
If skipna is False, then NA are treated as True, because these are not equal to zero.
```
But looks like a `pd.NA` value is being returned instead.


#### Expected Output

The expected behavior is the result of `all` should be `True` if we go by the docs or if this was a conscious design decision to return `NA` as scalar we should be updating the docs to reflect the same.
 
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 2a7d3326dee660824a8433ffd01065f8ac37f7d6
python           : 3.7.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-48-generic
Version          : #52-Ubuntu SMP Thu Sep 10 10:58:49 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8
pandas           : 1.1.2
numpy            : 1.19.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 49.6.0.post20200917
Cython           : 0.29.21
pytest           : 6.0.2
hypothesis       : 5.28.0
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.2
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.51.2

</details>
