STATS - CHI SQUARE
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20160601170949chi_square_stat_file.xlsChiSquare GOF Equal
| Chi-Square Goodness of Fit Test (Assuming Equal Expected) | ||||||
| Items | Observed | Expected | Chi Square | |||
| pool | 62 | 50.00 | 2.88 | |||
| no pool | 38 | 50.00 | 2.88 | |||
| - 0 | - 0 | |||||
| - 0 | - 0 | Data | ||||
| - 0 | - 0 | Level of Significance | 0.05 | |||
| - 0 | - 0 | Degrees of Freedom | 1 | |||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | Results | ||||
| - 0 | - 0 | Critical Value | 3.8415 | |||
| - 0 | - 0 | Chi-Square Test Statistic | 5.76 | |||
| - 0 | - 0 | p-Value | 0.0164 | |||
| - 0 | - 0 | Reject the null hypothesis | ||||
| - 0 | - 0 | |||||
| - 0 | - 0 | This tests the null hypothesis that the distribution is equal across all categories. | ||||
| - 0 | - 0 | It also tests if there is a difference in the frequencies of the categories / items. | ||||
| - 0 | - 0 | Rejecting the null implies a difference in the categories / items. | ||||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| ©2007 DrJimMirabella.com |
A p-value is the probability of making a type 1 error if you reject the null hypothesis. In other words, it is the probability you would be making a mistake to reject the null.
This is computed from the sample size minus one.
Also referred to as ALPHA. This is your tolerance for error; it is the probability of incorrectly rejecting the null hypothesis.
ChiSquare GOF Unequal
| Chi-Square Goodness of Fit Test (Assuming Unequal Expected) | |||||||
| Items | Observed | % Expected | Expected | Chi Square | |||
| Brick | 40 | 30.00% | 30.00 | 3.33 | |||
| Wood | 25 | 40.00% | 40.00 | 5.63 | |||
| Stucco | 35 | 30.00% | 30.00 | 0.83 | |||
| - 0 | - 0 | Data | |||||
| \ | - 0 | - 0 | Level of Significance | 0.05 | |||
| - 0 | - 0 | Degrees of Freedom | 2 | ||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | Results | |||||
| - 0 | - 0 | Critical Value | 5.9915 | ||||
| - 0 | - 0 | Chi-Square Test Statistic | 9.79 | ||||
| - 0 | - 0 | p-Value | 0.0075 | ||||
| - 0 | - 0 | Reject the null hypothesis | |||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | This tests the null hypothesis that the distribution is as expected. | |||||
| - 0 | - 0 | In other words, it tests if the results fit the expected distribution. | |||||
| - 0 | - 0 | Rejecting the null implies that the results do not fit the distribution. | |||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| - 0 | - 0 | ||||||
| 0 | |||||||
| ©2007 DrJimMirabella.com |
A p-value is the probability of making a type 1 error if you reject the null hypothesis. In other words, it is the probability you would be making a mistake to reject the null.
This is computed from the sample size minus one.
Also referred to as ALPHA. This is your tolerance for error; it is the probability of incorrectly rejecting the null hypothesis.
ChiSquare Table
| Chi-Square Test of Independence | |||||||||||||
| Observed Frequencies | |||||||||||||
| Column variable | Calculations | ||||||||||||
| Row variable | Lunch | Dinner | Total | fo-fe | |||||||||
| Ex | 34 | 42 | 76 | -4.56 | 4.56 | 0.00 | 0.00 | 0.00 | |||||
| VG | 24 | 32 | 56 | -4.41 | 4.41 | 0.00 | 0.00 | 0.00 | Use the YELLOW cells to set up the Chi Square table. | ||||
| G | 22 | 21 | 43 | 0.18 | -0.18 | 0.00 | 0.00 | 0.00 | The table can handle up to 5 rows and 5 columns of values. | ||||
| F | 14 | 3 | 17 | 5.37 | -5.37 | 0.00 | 0.00 | 0.00 | If fewer rows or columns are needed, leave the excess blank. | ||||
| P | 9 | 2 | 11 | 3.42 | -3.42 | 0.00 | 0.00 | 0.00 | The BLUE table computes the expected frequencies needed to compute the chi square | ||||
| Total | 103 | 100 | 0 | 0 | 0 | 203 | statistic. The only values that ultimately matter to you is in the RESULTS table. | ||||||
| Expected Frequencies | |||||||||||||
| Column variable | |||||||||||||
| Row variable | Lunch | Dinner | 0 | 0 | 0 | Total | (fo-fe)^2/fe | ||||||
| Ex | 38.56 | 37.44 | 0.00 | 0.00 | 0.00 | 76 | 0.54 | 0.56 | 0.00 | 0.00 | 0.00 | ||
| VG | 28.41 | 27.59 | 0.00 | 0.00 | 0.00 | 56 | 0.69 | 0.71 | 0.00 | 0.00 | 0.00 | ||
| G | 21.82 | 21.18 | 0.00 | 0.00 | 0.00 | 43 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | ||
| F | 8.63 | 8.37 | 0.00 | 0.00 | 0.00 | 17 | 3.35 | 3.45 | 0.00 | 0.00 | 0.00 | ||
| P | 5.58 | 5.42 | 0.00 | 0.00 | 0.00 | 11 | 2.09 | 2.16 | 0.00 | 0.00 | 0.00 | ||
| Total | 103 | 100 | 0 | 0 | 0 | 203 | |||||||
| Data | |||||||||||||
| Level of Significance | 0.05 | ||||||||||||
| Number of Rows | 5 | ||||||||||||
| Number of Columns | 2 | ||||||||||||
| Degrees of Freedom | 4 | ||||||||||||
| Results | |||||||||||||
| Critical Value | 9.4877290368 | ||||||||||||
| Chi-Square Test Statistic | 13.5390326677 | ||||||||||||
| p-Value | 0.0089 | ||||||||||||
| Reject the null hypothesis | |||||||||||||
| This tests the null hypothesis that the row variable and column variable are independent. | |||||||||||||
| Rejecting the null implies that the two variables are related (one is dependent on the other). | |||||||||||||
| ©2007 DrJimMirabella.com |
A p-value is the probability of making a type 1 error if you reject the null hypothesis. In other words, it is the probability you would be making a mistake to reject the null.
Also referred to as ALPHA. This is your tolerance for error; it is the probability of incorrectly rejecting the null hypothesis.
