Exam 9: A Synopsis of Selected Statistical Tests for Examining Nominal Data

An evaluative researcher measured a group of teenage parents on sleep deprivation before and after the birth of their children and categorized each teenage parent as high or low on sleep deprivation according to some threshold of sleep deprivation and decides to use the McNemar test because:

Explain the process of using the Binomial test to compare the categories of a dichotomous variable.

You cannot report the difference in proportions as your phi coefficient because it is only a quick-and-dirty estimate to be used before you actually calculate the real value.

Although you can make up your own mind about how noteworthy a given coefficient is by just examining the relationship as displayed in the output table in SPSS, it is a common practice to assume that a phi coefficient of .70 reveals:

The contingency coefficient is used when one or more of your two nominal variables have more than two categories.

The chi square statistic and the binomial test are tools for determining statistical significance when the data are measured at the:

The McNemar test for the significance of changes examines:

The chi square statistic examines:

The phi coefficient does not calculate numerical order of the variables. Please explain.

When a researcher wants to compare the proportion of perpetrators of domestic violence who completed their anger management exercises during the pretest period with the number of perpetrators who completed the anger management exercises during the posttest period, you would use:

In order to determine whether the frequencies in a dichotomous variable are significantly different from a 0-50 split, with 50% of cases in each of the two categories of the variable, you would engage in:

When you compare two independent groups such as males and females on the basis of a dichotomous dependent variable such as "improvement on the social skills" or "doesn't show improvement on social skills" measured at the nominal level, you can use:

Sample size is not one of the likely determinants of statistical significance.

When you compute chi square, the importance of expected frequencies and the logic behind it is evident in the method of calculating the expected frequencies for the cells. Please explain this process.