BUG: is_[int|float]_dtypes functions not recognizing ArrowDtype
- [ ] closes #50667 (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

Went ahead and fixed the other numeric-like dtype checkers

LGTM

Nice. This helps avoid a number of conversions to object dtype, e.g.

```
import pandas as pd
import numpy as np

ser = pd.Series(np.arange(10**6), dtype="int64[pyarrow]")

%timeit ser.duplicated()

# 403 ms ± 7.19 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)      <- main
# 12.4 ms ± 71.9 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)  <- this PR
```
 thx @mroeschke 