Optimizing NormalInferenceResults confidence interval method speed

[gdaiha]

Fixing issue #878, making an optimization to NormalInferenceResults.conf_int method speed, replacing a unnecessary loop by the main usage of scipy.stats.norm.ppf function. This allows big inputs to be calculated at least 50x faster (conservative estimation).

[kbattocchi]

Thanks for the contribution! If _safe_norm_ppf already correctly handles arrays as inputs, could you also change the other places that we're doing this unnecessary zipping as part of this PR? Specifically, PopulationSummaryResults.conf_int_mean in _inference.py, and _StatsModelsWrapper.coef__interval, _StatsModelsWrapper.intercept__interval, and _StatsModelsWrapper.predict_interval in linear_model.py.

[gdaiha]

Some tests are having unstable results.

[kbattocchi]

@gdaiha Recent changes to the GitHub macos-latest runner have broken our Mac tests; don't worry about addressing that yourself, but you'll have to merge in our fix once it hits main later today. Some of our other tests are occasionally flaky, but we can rerun them if we see a spurious failure.

[kbattocchi]

@gdaiha Recent changes to the GitHub macos-latest runner have broken our Mac tests; don't worry about addressing that yourself, but you'll have to merge in our fix once it hits main later today. Some of our other tests are occasionally flaky, but we can rerun them if we see a spurious failure.

We've run into some unanticipated making these fixes to the build system - I'll take care of merging them into this branch once they're ready. Thanks again for your contribution!