A Statistics Project
Callini47
chi_square.xlsChiSquare GOF Equal
| Chi-Square Goodness of Fit Test (Assuming Equal Expected) | ||||||
| Items | Observed | Expected | Chi Square | |||
| Roll a 1 | 13 | 20.00 | 2.45 | |||
| Roll a 2 | 33 | 20.00 | 8.45 | |||
| Roll a 3 | 14 | 20.00 | 1.80 | |||
| Roll a 4 | 7 | 20.00 | 8.45 | Data | ||
| Roll a 5 | 36 | 20.00 | 12.80 | Level of Significance | 0.01 | |
| Roll a 6 | 17 | 20.00 | 0.45 | Degrees of Freedom | 5 | |
| - 0 | - 0 | |||||
| - 0 | - 0 | |||||
| - 0 | - 0 | Results | ||||
| - 0 | - 0 | Critical Value | 15.0863 | |||
| - 0 | - 0 | Chi-Square Test Statistic | 34.40 | |||
| - 0 | - 0 | p-Value | 0.0000 | |||
| - 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 | |||
| Sunday | 165 | 40.00% | 160.00 | 0.16 | |||
| Monday | 79 | 20.00% | 80.00 | 0.01 | |||
| Tuesday | 50 | 14.00% | 56.00 | 0.64 | |||
| Wednesday | 44 | 10.00% | 40.00 | 0.40 | Data | ||
| Thursday | 32 | 8.00% | 32.00 | - 0 | Level of Significance | 0.05 | |
| Friday | 20 | 6.00% | 24.00 | 0.67 | Degrees of Freedom | 6 | |
| Saturday | 10 | 2.00% | 8.00 | 0.50 | |||
| - 0 | - 0 | ||||||
| - 0 | - 0 | Results | |||||
| - 0 | - 0 | Critical Value | 12.5916 | ||||
| - 0 | - 0 | Chi-Square Test Statistic | 2.38 | ||||
| - 0 | - 0 | p-Value | 0.8818 | ||||
| - 0 | - 0 | Do not 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 | C1 | C2 | C3 | C4 | C5 | Total | fo-fe | ||||||
| R1 | 27 | 35 | 33 | 25 | 120 | 3.00 | 5.00 | -3.00 | -5.00 | 0.00 | |||
| R2 | 13 | 15 | 27 | 25 | 80 | -3.00 | -5.00 | 3.00 | 5.00 | 0.00 | Use the YELLOW cells to set up the Chi Square table. | ||
| R3 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | The table can handle up to 5 rows and 5 columns of values. | ||||||
| R4 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | If fewer rows or columns are needed, leave the excess blank. | ||||||
| R5 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | The BLUE table computes the expected frequencies needed to compute the chi square | ||||||
| Total | 40 | 50 | 60 | 50 | 0 | 200 | statistic. The only values that ultimately matter to you is in the RESULTS table. | ||||||
| Expected Frequencies | |||||||||||||
| Column variable | |||||||||||||
| Row variable | C1 | C2 | C3 | C4 | C5 | Total | (fo-fe)^2/fe | ||||||
| R1 | 24.00 | 30.00 | 36.00 | 30.00 | 0.00 | 120 | 0.38 | 0.83 | 0.25 | 0.83 | 0.00 | ||
| R2 | 16.00 | 20.00 | 24.00 | 20.00 | 0.00 | 80 | 0.56 | 1.25 | 0.38 | 1.25 | 0.00 | ||
| R3 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | ||
| R4 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | ||
| R5 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | ||
| Total | 40 | 50 | 60 | 50 | 0 | 200 | |||||||
| Data | |||||||||||||
| Level of Significance | 0.05 | ||||||||||||
| Number of Rows | 2 | ||||||||||||
| Number of Columns | 4 | ||||||||||||
| Degrees of Freedom | 3 | ||||||||||||
| Results | |||||||||||||
| Critical Value | 7.8147277639 | ||||||||||||
| Chi-Square Test Statistic | 5.7291666667 | ||||||||||||
| p-Value | 0.1256 | ||||||||||||
| Do not 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.
