In this recipe, in the pulse dataset, we will look at the proportion of students who smoke regularly. We want to check if the proportion is different now from a historical figure of 25 percent of students who smoke regularly. Additionally, we will convert the numeric values in the Smokes column to text. This step is not necessary for the proportions test but can be useful to display the results.
Open the Pulse.mtw
dataset from the Minitab Sample Data
folder. The column Smokes has values of 1 and 2; 1 refers to those who smoke regularly and 2 refers to those who don't smoke regularly.
The following steps will recode the values in the smokes column to categories of Smokes and Does not Smoke before checking to see if the proportion of smokers is different from the historical proportion of 0.25:
0.25
.It is not essential to code the Smokes column from numeric values to text but this can be a useful step in the interpretation of the results. Steps 1 to 3 on coding data from numeric to text could be skipped if we want to go straight to the proportion test.
We have used the 1 Proportion test to count the frequency of observations in the Smokes column. It is also possible to use the 1 Proportion test with summarized results by entering the number of events and the number of trials.
The options for the 1 Proportion test can be used to change the confidence interval and choose between a one-sided or two-sided test.
The null hypothesis for this test is no different from the hypothesized proportion. The alternative hypothesis is that there is a difference. Here, we fail to reject the null hypothesis with a P-value of 0.278.
3.147.104.230