Categorical Data Analysis by David Spade, PhD

The lecture Categorical Data Analysis by David Spade, PhD is from the course Statistics Part 2. It contains the following chapters:

What is not a condition under which the goodness-of-fit test is appropriate?

The goodness-of-fit test is appropriate for sample means.
The goodness-of-fit test is appropriate if data medians must count.
The goodness-of-fit test is appropriate if the data comes from a random sample.
The goodness-of-fit test is appropriate when we expect to see at least five individuals in each cell.
The goodness-of-fit test is appropriate when we want to evaluate the difference between observed and expected values.

What is the null hypothesis in the chi-square test for homogeneity?

The null hypothesis is that the population distribution of one categorical variable is the same for each level of the other categorical variable.
The null hypothesis is that the population proportions are the same for each cell.
The null hypothesis is that the population distribution of one categorical variable is different for each level of the other categorical variable.
The null hypothesis is that the population proportions are different in each cell.
The null hypothesis is that the population distribution is the same for at least one different level of the other categorical variables.

What is the null hypothesis for the chi-square test for independence?

The null hypothesis is that two categorical variables are independent.
The null hypothesis is that two categorical variables have a linear relationship.
The null hypothesis is that the distribution of one categorical variable is the same for each level of the other categorical variable
The null hypothesis is that the population proportions are the same in each cell.
The null hypothesis is that two categorical variables have a logarithmic relationship.

What is not a necessary condition for the test of independence to be appropriate?

The population distribution must be normal.
Patients are randomized if appropriate.
The individuals in the study are independent.
The sample size must be less than 10% of the population of interest for each categorical variable.
The patients are likely to be representative of the population.

What is not true of categorical data analysis?

A rejection of the hypothesis of independence between two categorical variables means that the change in one variable causes the change in the other.
The chi-squared methods can not be used for data that are not numbered.
Large samples are not necessarily good for categorical data analysis because the degrees of freedom do not increase with sample size.
The goodness-of-fit test, the test for homogeneity, and the test for independence are all based on the χ² distribution.
Goodness-of-fit test data should be spread out in a random manner.

If observed values are 90, 170, 218 and expected values are 100, 150, 200, what is the value of the chi-square statistic?

If the total in row 1 is 550, total in column 1 is 460, and total number observed is 2500, then what is the expected value for row 1 column 1?