Chi-Square Distribution Table for Statistical Analysis
This dataset offers a comprehensive Chi-Square Distribution Table, detailing critical χ² values for 37 degrees of freedom and various p-levels. It's an indispensable resource for statistical hypothesis testing.
Bezpłatne pobieranie
Kluczowe wnioski
- Access critical χ² values for 37 degrees of freedom.
- Explore Chi-Square values across a range of p-levels (0.005 to 0.995).
- Download a ready-to-use table for statistical hypothesis testing.
- Leverage accurate data for research, education, and data analysis.
Wyświetlanie 37 z 37
| Degrees of Freedom (df) | χ² (p=0.995) | χ² (p=0.990) | χ² (p=0.975) | χ² (p=0.950) | χ² (p=0.050) | χ² (p=0.025) | χ² (p=0.010) | χ² (p=0.005) |
|---|---|---|---|---|---|---|---|---|
| 1 | 0 | 0 | 0.001 | 0.004 | 3.841 | 5.024 | 6.635 | 7.879 |
| 2 | 0.01 | 0.02 | 0.051 | 0.103 | 5.991 | 7.378 | 9.21 | 10.597 |
| 3 | 0.072 | 0.115 | 0.216 | 0.352 | 7.815 | 9.348 | 11.345 | 12.838 |
| 4 | 0.207 | 0.297 | 0.484 | 0.711 | 9.488 | 11.143 | 13.277 | 14.86 |
| 5 | 0.412 | 0.554 | 0.831 | 1.145 | 11.07 | 12.833 | 15.086 | 16.75 |
| 6 | 0.676 | 0.872 | 1.237 | 1.635 | 12.592 | 14.449 | 16.812 | 18.548 |
| 7 | 0.989 | 1.239 | 1.69 | 2.167 | 14.067 | 16.013 | 18.475 | 20.278 |
| 8 | 1.344 | 1.646 | 2.18 | 2.733 | 15.507 | 17.535 | 20.09 | 21.955 |
| 9 | 1.735 | 2.088 | 2.7 | 3.325 | 16.919 | 19.023 | 21.666 | 23.589 |
| 10 | 2.156 | 2.558 | 3.247 | 3.94 | 18.307 | 20.483 | 23.209 | 25.188 |
| 11 | 2.603 | 3.053 | 3.816 | 4.575 | 19.675 | 21.92 | 24.725 | 26.757 |
| 12 | 3.074 | 3.571 | 4.404 | 5.226 | 21.026 | 23.337 | 26.217 | 28.3 |
| 13 | 3.565 | 4.107 | 5.009 | 5.892 | 22.362 | 24.736 | 27.688 | 29.819 |
| 14 | 4.075 | 4.66 | 5.629 | 6.571 | 23.685 | 26.119 | 29.141 | 31.319 |
| 15 | 4.601 | 5.229 | 6.262 | 7.261 | 24.996 | 27.488 | 30.578 | 32.801 |
| 16 | 5.142 | 5.812 | 6.908 | 7.962 | 26.296 | 28.845 | 32 | 34.267 |
| 17 | 5.697 | 6.408 | 7.564 | 8.672 | 27.587 | 30.191 | 33.409 | 35.718 |
| 18 | 6.265 | 7.015 | 8.231 | 9.39 | 28.869 | 31.526 | 34.805 | 37.156 |
| 19 | 6.844 | 7.633 | 8.907 | 10.117 | 30.144 | 32.852 | 36.191 | 38.582 |
| 20 | 7.434 | 8.26 | 9.591 | 10.851 | 31.41 | 34.17 | 37.566 | 39.997 |
| 21 | 8.034 | 8.897 | 10.283 | 11.591 | 32.671 | 35.479 | 38.932 | 41.401 |
| 22 | 8.643 | 9.542 | 10.982 | 12.338 | 33.924 | 36.781 | 40.289 | 42.796 |
| 23 | 9.26 | 10.196 | 11.689 | 13.091 | 35.172 | 38.076 | 41.638 | 44.181 |
| 24 | 9.886 | 10.856 | 12.401 | 13.848 | 36.415 | 39.364 | 42.98 | 45.559 |
| 25 | 10.52 | 11.524 | 13.12 | 14.611 | 37.652 | 40.646 | 44.314 | 46.928 |
| 26 | 11.16 | 12.198 | 13.844 | 15.379 | 38.885 | 41.923 | 45.642 | 48.29 |
| 27 | 11.808 | 12.879 | 14.573 | 16.151 | 40.113 | 43.195 | 46.963 | 49.645 |
| 28 | 12.461 | 13.565 | 15.308 | 16.928 | 41.337 | 44.461 | 48.278 | 50.993 |
| 29 | 13.121 | 14.256 | 16.047 | 17.708 | 42.557 | 45.722 | 49.588 | 52.336 |
| 30 | 13.787 | 14.953 | 16.791 | 18.493 | 43.773 | 46.979 | 50.892 | 53.672 |
| 40 | 20.707 | 22.164 | 24.433 | 26.509 | 55.758 | 59.342 | 63.691 | 66.766 |
| 50 | 27.991 | 29.707 | 32.357 | 34.764 | 67.505 | 71.42 | 76.154 | 79.49 |
| 60 | 35.534 | 37.485 | 40.482 | 43.188 | 79.082 | 83.298 | 88.379 | 91.952 |
| 70 | 43.275 | 45.442 | 48.758 | 51.739 | 90.531 | 95.023 | 100.425 | 104.215 |
| 80 | 51.172 | 53.54 | 57.153 | 60.391 | 101.879 | 106.629 | 112.329 | 116.321 |
| 90 | 59.196 | 61.754 | 65.647 | 69.126 | 113.145 | 118.136 | 124.116 | 128.299 |
| 100 | 67.328 | 70.065 | 74.222 | 77.929 | 124.342 | 129.561 | 135.807 | 140.169 |
Przypadki użycia
- Import the CSV file into your Python scripts or R environment to perform automated chi-square tests and integrate results into larger statistical models.
- Use the Excel file to quickly look up critical χ² values, create custom tables, and support manual hypothesis testing for academic or professional reports.
- Print the PDF version for a handy reference during exams, classroom lectures, or offline statistical problem-solving without needing a computer.
- Leverage this dataset to validate statistical inferences, educate students on probability distributions, and support data-driven decision-making in various fields.