<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>gender</th>
      <th>race_ethnicity</th>
      <th>parental_level_of_education</th>
      <th>lunch</th>
      <th>test_preparation_course</th>
      <th>math_score</th>
      <th>reading_score</th>
      <th>writing_score</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>female</td>
      <td>group B</td>
      <td>bachelor's degree</td>
      <td>standard</td>
      <td>none</td>
      <td>72</td>
      <td>72</td>
      <td>74</td>
    </tr>
    <tr>
      <th>1</th>
      <td>female</td>
      <td>group C</td>
      <td>some college</td>
      <td>standard</td>
      <td>completed</td>
      <td>69</td>
      <td>90</td>
      <td>88</td>
    </tr>
    <tr>
      <th>2</th>
      <td>female</td>
      <td>group B</td>
      <td>master's degree</td>
      <td>standard</td>
      <td>none</td>
      <td>90</td>
      <td>95</td>
      <td>93</td>
    </tr>
    <tr>
      <th>3</th>
      <td>male</td>
      <td>group A</td>
      <td>associate's degree</td>
      <td>free/reduced</td>
      <td>none</td>
      <td>47</td>
      <td>57</td>
      <td>44</td>
    </tr>
    <tr>
      <th>4</th>
      <td>male</td>
      <td>group C</td>
      <td>some college</td>
      <td>standard</td>
      <td>none</td>
      <td>76</td>
      <td>78</td>
      <td>75</td>
    </tr>
  </tbody>
</table>
</div>

   gender race_ethnicity parental_level_of_education         lunch  \
0  female        group B           bachelor's degree      standard   
1  female        group C                some college      standard   
2  female        group B             master's degree      standard   
3    male        group A          associate's degree  free/reduced   
4    male        group C                some college      standard   

  test_preparation_course  math_score  reading_score  writing_score  
0                    none          72             72             74  
1               completed          69             90             88  
2                    none          90             95             93  
3                    none          47             57             44  
4                    none          76             78             75  

stdout

T-statistic: -4.169913529142
P-value: 3.311973638243664e-05
We reject the null hypothesis. There is a statistically significant difference in scores between male and female students.


<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>parental_level_of_education</th>
      <th>math_score</th>
      <th>reading_score</th>
      <th>writing_score</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>associate's degree</td>
      <td>67.882883</td>
      <td>70.927928</td>
      <td>69.896396</td>
    </tr>
    <tr>
      <th>1</th>
      <td>bachelor's degree</td>
      <td>69.389831</td>
      <td>73.000000</td>
      <td>73.381356</td>
    </tr>
    <tr>
      <th>2</th>
      <td>high school</td>
      <td>62.137755</td>
      <td>64.704082</td>
      <td>62.448980</td>
    </tr>
    <tr>
      <th>3</th>
      <td>master's degree</td>
      <td>69.745763</td>
      <td>75.372881</td>
      <td>75.677966</td>
    </tr>
    <tr>
      <th>4</th>
      <td>some college</td>
      <td>67.128319</td>
      <td>69.460177</td>
      <td>68.840708</td>
    </tr>
    <tr>
      <th>5</th>
      <td>some high school</td>
      <td>63.497207</td>
      <td>66.938547</td>
      <td>64.888268</td>
    </tr>
  </tbody>
</table>
</div>

  parental_level_of_education  math_score  reading_score  writing_score
0          associate's degree   67.882883      70.927928      69.896396
1           bachelor's degree   69.389831      73.000000      73.381356
2                 high school   62.137755      64.704082      62.448980
3             master's degree   69.745763      75.372881      75.677966
4                some college   67.128319      69.460177      68.840708
5            some high school   63.497207      66.938547      64.888268

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>test_preparation_course</th>
      <th>math_score</th>
      <th>reading_score</th>
      <th>writing_score</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>completed</td>
      <td>69.695531</td>
      <td>73.893855</td>
      <td>74.418994</td>
    </tr>
    <tr>
      <th>1</th>
      <td>none</td>
      <td>64.077882</td>
      <td>66.534268</td>
      <td>64.504673</td>
    </tr>
  </tbody>
</table>
</div>

  test_preparation_course  math_score  reading_score  writing_score
0               completed   69.695531      73.893855      74.418994
1                    none   64.077882      66.534268      64.504673

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>race_ethnicity</th>
      <th>math_score</th>
      <th>reading_score</th>
      <th>writing_score</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>group A</td>
      <td>61.629213</td>
      <td>64.674157</td>
      <td>62.674157</td>
    </tr>
    <tr>
      <th>1</th>
      <td>group B</td>
      <td>63.452632</td>
      <td>67.352632</td>
      <td>65.600000</td>
    </tr>
    <tr>
      <th>2</th>
      <td>group C</td>
      <td>64.463950</td>
      <td>69.103448</td>
      <td>67.827586</td>
    </tr>
    <tr>
      <th>3</th>
      <td>group D</td>
      <td>67.362595</td>
      <td>70.030534</td>
      <td>70.145038</td>
    </tr>
    <tr>
      <th>4</th>
      <td>group E</td>
      <td>73.821429</td>
      <td>73.028571</td>
      <td>71.407143</td>
    </tr>
  </tbody>
</table>
</div>

  race_ethnicity  math_score  reading_score  writing_score
0        group A   61.629213      64.674157      62.674157
1        group B   63.452632      67.352632      65.600000
2        group C   64.463950      69.103448      67.827586
3        group D   67.362595      70.030534      70.145038
4        group E   73.821429      73.028571      71.407143

Vizly: AI-powered data analysis

Statistical Analysis: Gender Differences in Student Scores

test the hypothesis which states that there will be no statistically significant difference in the scores of the male and female students.

Hypothesis Testing Summary

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Relationship Between Race/Ethnicity and Student Scores