A histogram divides sample values into many intervals and represents the frequency of data values in each interval with a bar.
The histogram visually shows the results of the hypothesis test. Minitab adjusts the data so that the center of the resamples is the same as the hypothesized proportion. For a onesided test, a reference line is drawn at the proportion of the original sample. For a twosided test, a reference line is drawn at the proportion of the original sample and at the same distance on the opposite side of the hypothesized proportion. The pvalue is the proportion of sample proportions that are more extreme than the values at the reference lines. In other words, the pvalue is the proportion of sample proportions that are as extreme as your original sample when you assume that the null hypothesis is true. These proportions are colored red on the histogram.
The bar chart shows the proportion of occurrences for each category.
Minitab displays a bar chart when you take only one resample. Minitab displays both the original data and the resample data.
The sample size (N) is the total number of observations in the original sample. Minitab takes resamples of this sample size to form the bootstrap samples.
The sample proportion equals the number of events divided by the sample size (N).
Minitab displays two different proportion values, the proportion of the observed sample and the proportion of the bootstrap distribution (Average). The proportion of the observed sample is an estimate of the population proportion. The proportion of the bootstrap distribution is usually close to the hypothesized proportion. The larger the difference between these two values, the more evidence you would expect against the null hypothesis.
In the output, the null and alternative hypotheses help you to verify that you entered the correct value for the hypothesized proportion.
 
 

In these results, the null hypothesis is that the population proportion is equal to 0.5. The alternative hypothesis is that the proportion is greater than 0.5.
The number of resamples is the number of times Minitab takes a random sample with replacement from your original data set. Usually, a large number of resamples works best.
Minitab adjusts the data so that the center of the resamples is the same as the hypothesized proportion. The sample size for each resample is equal to the sample size of the original data set. The number of resamples equals the number of observations on the histogram.
The average is the sum of the proportions in the bootstrapping sample divided by the number of resamples. Minitab adjusts the data so that the center of the resamples is the same as the hypothesized proportion.
Minitab displays two different proportion values, the proportion of the observed sample and the proportion of the bootstrap distribution (Average). The proportion of the observed sample is an estimate of the population proportion. The proportion of the bootstrap distribution is usually close to the hypothesized proportion. The larger the difference between these two values, the more evidence you would expect against the null hypothesis.
The pvalue is the proportion of sample proportions that are as extreme as your original sample when you assume that the null hypothesis is true. A smaller pvalue provides stronger evidence against the null hypothesis.
Use the pvalue to determine whether the population proportion is statistically different from the hypothesized proportion.