BUG: Cannot calculate quantiles from Int64Dtype Series when results are floats
- [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.

---

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

```python
import pandas as pd

pd.Series([1, 2, 3], dtype="Int64").quantile([0.75])
```
The result of the  above quantile call should be `2.5`, and the following error is thrown any time the result of the quantile call is a float: `TypeError: cannot safely cast non-equivalent object to int64`. Below, when we only calculate the `0.5` quantile (which is 2), no error is thrown:

```python
pd.Series([1, 2, 3], dtype="Int64").quantile([0.5])
```
#### Problem description

 In 1.2.5, this call works for Int64Dtype with the resulting dtype being `object`, and in 1.3.0, this call works for the non nullable `int64` with dtype `float64`. 

#### Expected Output
If we want to go with the 1.2.5 output, the expected output would be to not error and result in a Series with dtype `object`. It could also make sense for the resulting series to have `float64` dtype.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : f00ed8f47020034e752baf0250483053340971b0
python           : 3.8.2.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Thu Oct 29 22:56:45 PDT 2020; root:xnu-6153.141.2.2~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.0
numpy            : 1.21.0
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 41.2.0
Cython           : None
pytest           : 6.0.1
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.7
fastparquet      : 0.5.0
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 4.0.1
pyxlsb           : None
s3fs             : None
scipy            : 1.6.2
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.53.1


</details>
