No that's not what this formula is used for. This what we call a test statistic,Originally Posted byaskmemath

it's something we know (approximately) the distribution of. It is a function of

the data, and the data expected under the test hypothesis. The 's are the

observed frequencies in the analysis bins (in this case days), and the are the

frequencies we would have expected if our test hypos thesis were true.

Our test hypothesis is that there is no difference between the absentee rateBelow is the number of employees absent for a single day during a particular period of time

MOn(121absent), Tues (87absent) Weds (87 absent) Thur (91 absent) Fri (114 absent) TOTAL 500

Then I have to "test at the 5% level whether the differences in the observed and expected data are significant.

for differing days of the week. Under this hypothesis we expect the same

number of absentees on each day, with a total number of absentees.

So we have expected numbers of for ,

where denotes Monday, denotes Tuesday etc.

The observed frequencies are , so now we have

everything we need to plug into the formula for the test statistic.

so:

Now if I recall correctly the test statistic has a (Chi squared)

distribution, and degrees of freedom (number of bins minus one)

Now we look up the value of with degrees of freedom that 95%

of all observations should fall below, this is Thus we would expect

our test statistic to exceed this no more than 5% of the time. In this case

our test statistic does exceed this value so "at 5% level the differences in

the observed and expected data are significant".

RonL