using this function (randBin(4,0.3,500) → L1 ) and counting the number of each outcome. (Can
you think of an efficient way to count each outcome?) She obtained
Do these data provide evidence that the randBin function on the calculator is correctly generating
values from this distribution?
Calculator Tip: It’s a bit of a digression, but if you actually wanted to do the experiment in question 1,
you would need to have an efficient way of counting the number of each outcome. You certainly don’t
want to simply scroll through all 500 entries and tally each one. Even sorting them first and then
counting would be tedious (more so if n were bigger than 4). One easy way is to draw a histogram of
the data and then TRACE to get the totals. Once you have your 500 values from randBin in L1 , go to
STAT PLOTS and set up a histogram for L1 . Choose a WINDOW something like [–0.5,4.5,1,–
1,300,1,1 ]. Be sure that Xscl is set to 1. You may need to adjust the Ymax from 300 to get a nice
picture on your screen. Then simply TRACE across the bars of the histogram and read the value of n for
each outcome off of the screen. The reason for having x go from –0.5 to 4.5 is so that the (integer)
outcomes will be in the middle of each bar of the histogram.
A chi-square test for the homogeneity of proportions is conducted on three populations and one
categorical variable that has four values. Computation of the chi-square statistic yields X 2 = 17.2. Is
this result significant at the 0.01 level of significance?
- Which of the following best describes the difference between a test for independence and a test for
homogeneity of proportions? Discuss the correctness of each answer.
a. There is no difference because they both produce the same value of the chi-square test statistic.
b. A test for independence has one population and two categorical variables, whereas a test for
homogeneity of proportions has more than one population and only one categorical variable.
c. A test for homogeneity of proportions has one population and two categorical variables, whereas
a test for independence has more than one population and only one categorical variable.
d. A test for independence uses count data when calculating chi-square and a test for homogeneity
uses percentages or proportions when calculating chi-square.