1. The χ² goodness of fit can be used for both qualitative and quantitative data

2. The actually measured counts in the cells of a contingency table are referred to as the expected cell frequencies.

3. The chi-square distribution is a continuous probability distribution that is skewed to the left.

4. In a contingency table, when all the expected frequencies equal the observed frequencies the calculated c² statistic equals zero.

5. In a contingency table, if all of the expected frequencies equal the observed frequencies, then we can conclude that there is a perfect dependence between rows and columns.

6. A fastener manufacturing company uses a chi-square goodness of fit test to determine if a population of all lengths of ¼ inch bolts it manufactures is distributed according to a normal distribution. If we reject the null hypothesis, it is reasonable to assume that the population distribution is at least approximately normally distributed.

7. In performing a chi-square test of independence, as the difference between the respective observed and expected frequencies decrease, the probability of concluding that the row variable is independent of the column variable increases.

8. The chi-square goodness of fit test can only be used to test whether a population has specified multinomial probabilities or to test if a sample has been selected from a normally distributed population. It cannot be applied to test if a sample data comes from other distribution forms such as Poisson.

9. When we carry out a chi-square test of independence, the expected frequencies are based on the null hypothesis.

10. When we carry out a goodness of fit chi-square test, the expected frequencies are based on the alternative hypothesis.