Complete the mcq:
1. In a chi-square test, the sample data are called observed frequencies.
True
False
2. One advantage of the chi-square tests is that they can be used when the data are measured on a nominal scale.
True
False
3. A chi-square test for goodness of fit is used to evaluate a hypothesis about how a population is distributed across three categories. If the researcher uses a sample of n = 100 participants, then the chi-square test will have df = 99.
True
False
4. The chi-square test for independence requires that each individual be categorized on two separate variables.
True
False
5. For the chi-square test for goodness of fit, what is the value of df for a test with four categories and a sample of n = 100?
96
4
3
99
6. The chi-square distribution is
positively skewed, with no values less than zero.
negatively skewed, with no values greater than zero.
symmetrical, centered at a value determined by the degrees of freedom.
symmetrical, centered at a value of zero.
7. A researcher obtains a value of -8.50 for a chi-square statistic. What can you conclude because the value is negative?
the observed frequencies are consistently larger than the expected frequencies
The researcher made a mistake. The value of chi-square cannot be negative.
the expected frequencies are consistently larger than the observed frequencies
there are large differences between the observed and expected frequencies
8. A chi-square test for independence is used to evaluate the relationship between two variables. If one variable is classified into 4 categories and the other variable is classified into 2 categories, then the chi-square statistic will have
df = 6
cannot determine the value of df from the information provided
df = 3
df = 8
9. The sample data for a chi-square test are called ________.
observed proportions
observed frequencies
expected proportions
expected frequencies
10. In the chi-square test for independence, the null hypothesis states that
there is no relationship between the two variables being examined.
there is a relationship between the two variables being examined.
there is no difference between the two variables being examined.
there is a difference between the two variable