Here's how you would do it:
a) Compare the standard deviations of the two processes:
The standard deviation quantifies the amount of variation or dispersion of a set of values. To compare the standard deviations of the two processes, firstly calculate the standard deviation for each process. Subtract standard deviation of process 2 from that of process 1. The result gives the difference in standard deviations. If the result is positive, it means that process 1 has greater variation than process 2. If the result is negative, process 2 has more variation. If zero, both processes have equal variation.
b) Perform a t-test to compare the means:
A t-test is used to determine if the means of two sets of data are significantly different from each other. You'll calculate the mean for each process, then use these values to perform the t-test. You will compare the test statistic with the t-table value for the appropriate degrees of freedom. If the t-value is greater than the table value, this suggests a significant difference between the means of the processes.
c) Calculate the product of the means:
To determine the product of the means of the two processes, simply multiply the mean of process 1 by the mean of process 2. This value doesn't hold a direct response to your question, but could be valuable to further statistical analysis or comparisons.
d) Conduct an ANOVA test:
ANOVA (Analysis of Variance) is used to determine significant differences between means of three or more groups. You're working with just two processes here, so it's not entirely necessary. But, if you wish to do it, the null hypothesis is that the means are equal. By performing the test, if the F-statistic is greater than 1 and the p-value is less than the alpha level (often set at 0.05), then you would reject the null hypothesis and conclude that there is a significant difference in the mean units produced between the two processes.