README.md

# Data Files



This directory contains sample datasets for various statistical analyses.

## Available Datasets

### 1. sample_data.csv
**Purpose**: Linear regression analysis
**Columns**:
- `X1`, `X2`, `X3`: Independent variables
- `y`: Dependent variable

**Usage**:
```python
import pandas as pd
df = pd.read_csv('data/sample_data.csv')
X = df[['X1', 'X2', 'X3']].values
y = df['y'].values
```

### 2. time_series_data.csv
**Purpose**: Time series analysis and forecasting
**Columns**:
- `date`: Date index
- `value`: Time series values

**Usage**:
```python
import pandas as pd
df = pd.read_csv('data/time_series_data.csv', parse_dates=['date'], index_col='date')
ts_data = df['value']
```

### 3. panel_data.csv
**Purpose**: Panel data analysis (fixed/random effects)
**Columns**:
- `entity`: Entity identifier
- `time`: Time period
- `X1`, `X2`: Independent variables
- `y`: Dependent variable

**Usage**:
```python
import pandas as pd
from panel_data_analysis import PanelDataAnalysis

df = pd.read_csv('data/panel_data.csv')
panel = PanelDataAnalysis()
panel.prepare_panel_data(df, 'entity', 'time', ['X1', 'X2', 'y'])
```

### 4. hypothesis_test_data.csv
**Purpose**: Hypothesis testing (t-tests, ANOVA)
**Columns**:
- `group`: Group identifier (A, B, C, D)
- `value`: Measurement values

**Usage**:
```python
import pandas as pd
df = pd.read_csv('data/hypothesis_test_data.csv')
groups = df['group'].unique()
samples = {group: df[df['group'] == group]['value'].values for group in groups}
```

### 5. econometric_data.csv
**Purpose**: Econometric modeling (VAR, cointegration)
**Columns**:
- `date`: Date index
- `GDP`: Gross Domestic Product
- `Consumption`: Consumption
- `Investment`: Investment
- `Unemployment`: Unemployment rate

**Usage**:
```python
import pandas as pd
df = pd.read_csv('data/econometric_data.csv', parse_dates=['date'], index_col='date')
data = df[['GDP', 'Consumption', 'Investment']]
```

## Data Characteristics

| Dataset | Rows | Columns | Type |
|---------|------|---------|------|
| sample_data.csv | 30 | 4 | Cross-sectional |
| time_series_data.csv | 90 | 2 | Time series |
| panel_data.csv | 50 | 5 | Panel |
| hypothesis_test_data.csv | 40 | 2 | Cross-sectional |
| econometric_data.csv | 36 | 5 | Time series |

## Notes

- All datasets are synthetic and created for demonstration purposes
- Data files are compatible with pandas DataFrame operations
- Date columns are formatted for easy parsing
- All datasets include author information in comments

## Author

**RSK World**
- Website: https://rskworld.in
- Email: help@rskworld.in
- Phone: +91 93305 39277

hypothesis_testing.cpython-313.pyc

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data/panel_data.csv

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entity,time,X1,X2,y
0,0,1.2,2.3,5.8
0,1,1.5,2.1,6.2
0,2,1.8,2.5,6.5
0,3,1.3,2.2,6.1
0,4,1.6,2.4,6.4
0,5,1.4,2.6,6.3
0,6,1.7,2.3,6.6
0,7,1.9,2.5,6.8
0,8,1.5,2.4,6.4
0,9,1.6,2.7,6.7
1,0,2.1,3.2,7.5
1,1,2.3,3.4,7.8
1,2,2.5,3.1,7.6
1,3,2.2,3.3,7.4
1,4,2.4,3.5,7.9
1,5,2.6,3.2,7.7
1,6,2.3,3.4,7.5
1,7,2.5,3.6,8.0
1,8,2.7,3.3,7.8
1,9,2.4,3.5,7.6
2,0,0.8,1.5,4.2
2,1,0.9,1.6,4.4
2,2,1.0,1.4,4.1
2,3,0.7,1.5,3.9
2,4,0.8,1.7,4.3
2,5,1.1,1.5,4.2
2,6,0.9,1.6,4.0
2,7,1.0,1.8,4.4
2,8,1.2,1.6,4.3
2,9,0.9,1.7,4.1
3,0,3.2,4.1,9.2
3,1,3.4,4.3,9.5
3,2,3.6,4.0,9.3
3,3,3.3,4.2,9.1
3,4,3.5,4.4,9.6
3,5,3.7,4.1,9.4
3,6,3.4,4.3,9.2
3,7,3.6,4.5,9.7
3,8,3.8,4.2,9.5
3,9,3.5,4.4,9.3
4,0,1.8,2.8,6.9
4,1,2.0,2.9,7.1
4,2,2.2,2.7,6.8
4,3,1.9,2.8,6.6
4,4,2.1,3.0,7.0
4,5,2.3,2.8,6.9
4,6,2.0,2.9,6.7
4,7,2.2,3.1,7.1
4,8,2.4,2.9,7.0
4,9,2.1,3.0,6.8

53 lines•873 B

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README.md