# DABench Task 652 - 1. Perform a distribution analysis on the X-coordinate column. Determine if the data follows a normal distribution and provide a justification. Use a significance level (alpha) of 0.05 for the normality test. If the p-value is less than 0.05, conclude that the data does not follow a normal distribution. If the p-value is greater than or equal to 0.05, conclude that the data does follow a normal distribution.

## Task Description

1. Perform a distribution analysis on the X-coordinate column. Determine if the data follows a normal distribution and provide a justification. Use a significance level (alpha) of 0.05 for the normality test. If the p-value is less than 0.05, conclude that the data does not follow a normal distribution. If the p-value is greater than or equal to 0.05, conclude that the data does follow a normal distribution.

## Concepts

Distribution Analysis

## Data Description

Dataset file: `DES=+2006261.csv`

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

## Constraints

Use Python's Scipy library's normaltest function for the normality test. Use a significance level (alpha) of 0.05 for the test.

## Files

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

## Submission Format

Submit a CSV with columns `id,answer`, containing one row. In the `answer` cell include both markers (space or newline separated) in this order (quote the cell as in the sample to preserve spaces/newlines):
@normal_distribution[boolean] @normality_test_p_value[p_value]

"p_value" is between 0 and 1, rounded to four decimal places. "boolean" is True if p-value >= 0.05, else False.

## 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

Medium
