Pearson's chi-square used in nursing research or any other research identifies the significance of related variables. There are three types of variables in a hypothesis: Control, the part of the experiment that is being compared, the “norm”; Dependent, the factor that should be changed by the experiment or test; Independent, the aspect that is expected to change in the experiment. The focus of nursing research is providing superior nursing care. The test of chi-square is determining whether the null hypothesis is true, false or no change in variables.
Decide on a hypothesis that should be tested. Such as, a nurse wants to discover whether there is a correlation or relationship between fever and persons exposed to the cold. The expected outcome is that 90 patients out of 100 will develop a fever from being exposed to the cold.
Gather data. Out of 100 patients, 75 experience a fever when exposed to the cold, while 25 experience a fever without being exposed to the cold. These are the aspects of the experiment that have been observed.
Calculate: The number of patients observed with a fever from the cold, 75. Subtract the number of expected patients with fever, 90. 75-90=15, multiply by 2 or square, 30, ignore the negative.
Divide 30 against the expected number of cases, 90. 0.33.
Determine the degrees of freedom or df. Degrees of freedom are the calculated by dividing the number of cases compared with the number of cases compared. In this case the equation would be 100/100=1. This determines whether or not the probability is significant. In this case, p=0.05, p is found on the chi-square probability table.
Find .01 under p=0.05 on the chi-square distribution table. In this case, chi-square equals, 47.4. Meaning the null hypothesis is proven true or exposure to the cold causes a fever 47 percent of the time.
Chi-square must be computed carefully. It is easy to miss a step and receive a false negative or false positive.