To be able to have meaningful results from a chi square goodness of fit test I should have, among other assumptions, expected frequencies for each category at least 1.

If I have expected frequencies <1, does it make sense to excude those categories from the test? Example:

**Population frequencies:**

2

100

150

80

(total = 332)

**Sample frequencies:**

1

15

20

10

(total = 46)

Therefore I get:

**Expected ferquencies:**

0.28 (=2*46/332)

13.86 (=100*46/332)

20.78 (=150*46/332)

11.08 (=80*46/332)

(total = 46)

Since 0.28<1, does it make sense to do the test on:

**Population frequencies:**

100

150

80

(total = 330)

**Sample frequencies:**

15

20

10

(total = 45)

**Expected ferquencies:**

13.64 (=100*45/330)

20.45 (=150*45/330)

10.91 (=80*45/330)

(total = 45)

? Is there a standard way to deal with low expected frequencies? Maybe a different test?

Thanks,

Diodoo