BUG: Fix the `Float` type overflow issue for statistical functions.
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

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


### Reproducible Example

```python
>>> import pandas as pd
>>> df = pd.DataFrame([60000.0, 60000.0], dtype="float16")
```


```Python
/Users/username/opt/miniconda3/lib/python3.7/site-packages/numpy/core/_methods.py:47: RuntimeWarning: overflow encountered in reduce
  return umr_sum(a, axis, dtype, out, keepdims, initial, where)
0    inf
dtype: float16
```


### Issue Description

I have read the source code of pandas recently, it seems that when pandas implement DataFrame.mean() method, it calculate the tot = elements.sum() first, and then divide by the count_of_elements secondly to get the mean_value. This could cause a overflow error even if the result shouldn't be a number out of dtype range.

### Expected Behavior

1. The example should return 60000.0
2. For any Float dtype Series/DataFrame, the mean method should work and do not overflow.

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 73c68257545b5f8530b7044f56647bd2db92e2ba
python           : 3.7.6.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
Version          : Darwin Kernel Version 18.7.0: Tue Jun 22 19:37:08 PDT 2021; root:xnu-4903.278.70~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.UTF-8

pandas           : 1.3.3
numpy            : 1.19.2
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : 0.29.22
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.21.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : None
tables           : None
tabulate         : 0.8.9
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.53.1

</details>
