Data Analysis - Chi-squared test for nominal (categorical) data
Watch the video on how to calculate a chi square p value Excel. P-values are used in hypothesis testing to help you figure out if your results. In this example, we wish to test the difference between X and Y a chi-square test of independence to test for a relationship. We use the chi-square test, and so need to calculate the expected values that H0: There is no difference between the two therapies' ability to cure cocaine.
Therapy 1 and 2, we will get erroneous results. We need to include Not Cured as well as Cured.
- Independence Testing
Real Statistics Excel Functions: The following supplemental functions are provided in the Real Statistics Resource Pack: Real Statistics Data Analysis Tool: A dialog box as in Figure 3 appears. Figure 3 — Dialog box for Chi-square Test Insert the observation data into the Input Range excluding the totals, but optionally including the row and column headings; i.
Goodness of Fit
D8click on the Excel format radio button and press the OK button. The output from the data analysis tool for the data in Example 1 in shown in Figure 4.
Figure 4 — Chi-Square data analysis tool output for Example 1 Observation: For large contingency tables, a small percentage of cells with expected frequency of less than 5 can be acceptable.
In any event, you should avoid using the chi-square test where there is an expected frequency of less than 1 in any cell. If the expected frequency for one or more cell is less than 5, it may be beneficial to combine one or more cells so that this condition can be met, although this must be done in such a way as to not bias the results.How To... Perform a Chi-Square Test for Independence in Excel
In addition to the usual Excel input data format, the Real Statistics Chi Square Test data analysis tool supports another input data format called standard format. This format is similar to that used by SPSS and other statistical analysis programs. A survey is conducted of 38 young adults whose parents are classified either as wealthy, middle class or poor to determine whether they will graduate from university or not. The results are summarized in the table on the left side of Figure 5 only the first 13 of 38 rows of data are shown.
When the dialog box shown in Figure 3 appears, insert A3: The data analysis tool first builds a contingency table range D5: F8 of Figure 5 and performs the same type of analysis as for Example 1 and 2. Example 3 uses the two column version of the standard format.
Chi-Square Independence Testing | Real Statistics Using Excel
There is also a three column version, which is a frequency table version of the other standard format. This is demonstrated in Figure 6 where A4: The output is identical to that shown in Figure 5. In general, the maximum likelihood test statistic is not used directly.
For large samples the results are similar, but for small samples the maximum likelihood statistic yields better results. Theorem 2 is used to perform what is called goodness of fit testing, where we check to see whether the observed data correspond sufficiently well to the expected values.
Data must come from a random sampling of a population.
The observations must be independent of each other. This means chi-square cannot be used to test correlated data e. These assumptions are similar to those for the normal approximation to the binomial distribution.
Since the data is usually organized in the form of a table, the last assumption means that there must be at least 5 cells in the table and the expected frequency for each cell should be at least 5. For large values of k, a small percentage of cells with expected frequency of less than 5 can be acceptable. Even for smaller values of k this may not cause big problems, but it is probably a better choice to use Fisher Exact Test in this case.
Using Excel for Data Analysis
In any event, you should avoid using the chi-square test where there is an expected frequency of less than 1 in any cell. If the expected frequency for one or more cells is less than 5, it may be beneficial to combine one or more cells so that this condition can be met although this must be done in such a way as to not bias the results. We have a die which we suspect is loaded to favor one or more numbers over the others.
To test this we throw the die 60 times and get the following count for each of the 6 possible throws as shown in the upper part of the worksheet in Figure 2: We calculate the chi-square test statistic to be G7 in cell H7 of Figure 2.
We can reach the same conclusion by looking at the critical value of the test statistic: Excel provides the following function which automates the above calculations: The ranges R1 and R2 must both have either one row or one column, they must contain the same number of elements and all the cells in R1 and R2 must contain only numeric values.
BSCI 1511L Statistics Manual: 2.4 Conducting a chi squared contingency test using Excel
A safari park in Africa is divided into 8 zones, each containing a known population of elephants. A sample is taken of the number of elephants found in each zone to determine whether the distribution of elephants is significantly different from what would be expected based on the known population in each zone.
The table on the left of Figure 3 columns A-C summarizes the data: Figure 3 — Data for Example 3 The sample consists of the 55 elephants actually recorded obsi by zone. For the analysis we use the following null hypothesis: Fitting data to a distribution Observation: The chi-square goodness of fit test as well as the maximum likeliness test can also be applied to determine whether observed data fit a certain distribution or curve.