Final answer:
To determine if a distribution is normal, you can visually assess graphs like histograms for skewness and kurtosis, and utilize statistical tests such as the chi-square goodness-of-fit test.
Step-by-step explanation:
You determine and assess if a distribution is normal by using graphical methods like histograms and assessing skewness and kurtosis visually. Moreover, you can use statistical tests such as the chi-square goodness-of-fit test, which determines if the data fit a particular distribution. When applying the test for homogeneity, you can assess whether two data sets come from the same distribution using the chi-square distribution. Additionally, the test of independence with the chi-square distribution can be used to assess whether factors are independent.
Descriptive statistics, which include constructing histograms and calculating measures of skewness and kurtosis, give a visual and numerical insight into the symmetry and shape of the distribution. This is useful before using more advanced inferential statistics, which allows us to make probabilistic statements and conclusions about whether the observed data could reasonably come from a normal distribution.
The answer to the original question would be option d: Using graphical methods like histograms and assessing skewness and kurtosis visually.