# DABench Task 39 - Explore the distribution of the "importance.score" column and determine if it follows a normal distribution by conducting a Shapiro-Wilk test. If the p-value is less than 0.05, apply a log transformation to make the distribution closer to normal. Calculate the mean and standard deviation of the transformed "importance.score" column.

## Task Description

Explore the distribution of the "importance.score" column and determine if it follows a normal distribution by conducting a Shapiro-Wilk test. If the p-value is less than 0.05, apply a log transformation to make the distribution closer to normal. Calculate the mean and standard deviation of the transformed "importance.score" column.

## Concepts

Distribution Analysis, Feature Engineering

## Data Description

Dataset file: `imp.score.ldlr.metabolome.csv`

The data is available in the `train.csv` file in the public directory.

## Constraints

1. Use the Shapiro-Wilk test to determine the normality of the data in the "importance.score" column. The null hypothesis for this test is that the data was drawn from a normal distribution.
2. Use a significance level of 0.05 for the Shapiro-Wilk test.
3. If the p-value from the Shapiro-Wilk test is less than 0.05, apply a natural log transformation to the "importance.score" column.

## Files

- `train.csv` - The training data
- `sample_submission.csv` - A sample submission file in the correct format

## Submission Format

Submit a single-row CSV with columns `id,answer`.

- `id`: always `39`
- `answer`: `@is_normal[<value>]`, a string/indicator of normality (per grader expectations).

## Evaluation

Submissions are evaluated on **exact match** with the ground truth answer (with tolerance of 0.01 for floating-point values).

## Goal

Provide the correct answer in the specified format.

## Difficulty Level

Hard
