Deck 8: Elaboration of Tabular Data and the Nature of Causation

Question 1

What are the requirements to establish causality? Indicate the meaning of the terms. Also provide an example in which the requirement is absent.
a. __________________________________
b. __________________________________
c. __________________________________

Answer 1

a. Association. There must be at least some relationship between the variables, meaning that one variable must impact the other variable at least occasionally. There is no relationship between age and gender, between race and weight, or between education and the life expectancy of your dog.
b. Temporal order. If we want to establish causality, variable A must occur prior to variable B. For example, if we theorize that more police (A) will result in less crime, the increased presence of the police must occur prior to a decrease in criminal activity (B).
c. Nonspuriousness. The outcome (DV) is not (better) explained by another variable. Nonspuriousness is absent if we rest the relationship between ice cream and crime, between daylight and the tides, and between IQ and death.

Question 2

Indicate whether in the following examples the IV is necessary, sufficient, both, or neither.
a. The willingness to change is a _____________ cause of desistance.
b. Driving under the influence of alcohol is a ______________ cause for arrest.
c. Being born in the United States is a ________________ cause for U.S. citizenship.
d. Being convicted for an offense is a ___________________ cause for a criminal record.

Answer 2

a. Necessary.
b. Sufficient.
c. Sufficient.
d. Necessary and sufficient.

Question 3

To determine whether one variable (IV) is predicting another variable (DV) to a certain degree, statisticians make use of multivariate analyses and thus are introducing other variables (IVs) as so-called ________________ variables.

Answer 3

Control variables.

Question 4

Assume you are interested to find what variables influence the decision-making process of a police officer to arrest an individual after being stopped because of a traffic violation (0 = no arrest; 1 = arrest). First, you question whether race (0 = nonminority; 1 = minority) could have some influence on an officer's decision to make an arrest. Then, you ask whether seriousness of the traffic offense influences the outcome of arrest (0 = minor; 1= severe). The hypothetical data (n = 35) are presented in the table below. You set your alpha level at 0.05.

a. Organize your data in a table and then identify the IV and DV.
b. State your null and alternative hypotheses.
c. Compute the degrees of freedom.
d. State your decision rule using the chi square table.
e. Compute chi square (χ²).
f. Make your decision and interpret your findings.

Question 5

You are wondering whether the relationship between being a minority and arrest remains statistically significant when taking the seriousness of the traffic violation into consideration. Compute chi square and phi. Compute chi square (minority, arrest) holding severity of traffic violation constant.
a. Organize your data in tables and then identify the IVs and DVs.
b. State your null and alternative hypotheses.
c. Compute the degrees of freedom for each test.
d. State your decision rule using the chi square table.
e. Compute chi square (χ²).
f. Make your decision and interpret your findings for each test.