Research Methods in Crime and Justice Chapter 7 Variables and the Structure of Research

Variables and Hypotheses In social science, we use variables to describe the different characteristics of individuals, groups, organizations and social phenomena. The manner in which we describe things can sometimes help us understand a problem or phenomenon more precisely.

Variables and Hypotheses A variable is any characteristic of an individual, group, organization or social phenomenon that changes. A hypothesis is a statement that predicts how a change in one or more variables will cause a change in another variable. Making Research Real 7.1 – Aggravated Assaults in the Midwest (p. 137) The chief of a small town tries to understand why aggravated assaults are increasing among Hispanic residents After visiting with a community leader (local priest) he learns of a recent increase in Hispanics from Central and South America. Conflict between these groups might be the cause of the increase in aggravated assaults Because the chief was able to more narrowly define the issue (using a more precise variable for Hispanic) he was able to address the issue more intelligently.

Types of Variables Generally, there are three types of variables. Independent variables Dependent variables Intervening variables Each type of variable functions differently within a hypothesis.

Independent Variables An independent variable is; the causal variable, or the variable that a researcher predicts will be the cause of a change in another variable.

Dependent Variables A dependent variable is; the effect, or the variable that a researcher predicts will change as a result of a change in another variable or set of variables.

Independent vs. Dependent An easy way to distinguish between the independent and dependent variables is to ask which happens first. The independent variable always happens first. The first causal rule (temporal order) requires that the cause (independent variable) must happen prior to the effect (dependent variable).

Independent or Dependent? Children who experience domestic abuse are more likely as adults to abuse their domestic partners. Independent variable – Children who experience domestic abuse. Dependent variable – domestic abusive behavior as an adult.

Intervening Variables An intervening variable is any variable that occurs between the independent and dependent variables, and may change how, or even if, the independent variable affects a dependent variable. In other words, intervening variables intervene in the causal relationship.

Independent, Dependent or Intervening? Children who experience domestic abuse are more likely as adults to abuse their domestic partners, unless they develop strong attachments to non-abusive adults. Independent variable – Children who experience domestic abuse. Dependent variable – domestic abusive behavior as an adult. Intervening variable – strong attachments to non-abusive adults. Making Research Real 7.2 – An Intervention to Reduce Traffic Fatalities Caused by Intoxicated Drivers (p. 140) A community attempts to reduce traffic crash fatalities with ordinances regulating the number of hours alcohol can be served. They know that an increase in serving hours results in an increase of traffic crash fatalities. However, their ordinance does not have its intended effect. They learn that the availability of a taxi service intervenes in the relationship between serving hours and fatalities and, to the extent it is used, reduces fatalities.

Variable Attributes Attributes are the different characteristics or values that a variable can take on. A variable’s attributes must be both; Exhaustive Mutually exclusive

Exhaustiveness Exhaustiveness refers to the completeness of the list of attributes. All of the possible attributes for each variable must be included. In some cases it may be necessary to include an ‘other’ in the list of attributes.

Mutual Exclusivity Mutual exclusivity requires that the list of attributes must be we mean that each attribute must be distinctive, such that a respondent can pick one, and only one, option. Making Research Real 7.3 – Learning About Religious Preference, With a Little Help from Our Friends (p. 144) A researcher attempts to develop a set of attributes for the variable ‘religious preference’ The researcher learns that this is much more difficult than anticipated. Eventually, the researcher learns that knowledge of the variable (in this case the differences between religious preferences) is essential to developing an exhaustive and mutually exclusive set of attributes.

Elements of a Good Research Question A research question is an interrogative statement. An actual question Not a statement There are four criteria of a good research question. Measurable Unanswered Feasible Disinteresting

Elements of a Good Research Question Research questions should be measurable. The concepts in the question should be measurable, either quantitatively or qualitatively. Avoid the use of ambiguous terms and superlatives. Research questions should be unanswered. Most questions in the social sciences have been asked and answered by other researchers. This does not mean that we cannot ask them again or in different ways.

Elements of a Good Research Question Research questions should be feasible. Money and time are always finite resources. Researchers should consider whether a particular research project is practical or feasible. Research questions should be disinteresting. Researchers should be indifferent to the outcome of their research. Researchers never should try to prove anything, but be led by the evidence to the most logical conclusion. Making Research Real 7.4 – Measuring Jesus (p. 146) A student attempts to test a hypothesis that inmates who experience a religious conversion during incarceration are less likely to recidivate. The student confronts a problem when he attempts to measure the extent to which an inmate experiences a religious conversion. It is also clear that the student researcher is not disinterested in this question.  

Hypotheses in Social Research A hypothesis is a predictive statement that alleges a plausible connection between two or more variables. ‘Predictive’ means the hypothesis makes a specific prediction about how two or more variables are connected. ‘Plausible connection’ means that the hypothesis must describe the nature of the connection between the variables. All hypotheses contain two or more variables.

The Alternative Hypotheses An alternative hypothesis (Ha) is a predictive statement alleging a plausible connection between two or more variables. This is the hypothesis the researcher wants to confirm as true at the end of the research. For each alternative hypothesis the researcher must develop a competing null hypothesis.

The Null Hypothesis A null hypothesis (Ho) is a predictive statement that alleges no plausible connection between two or more variables. The null hypothesis is the exact opposite of the alternative hypothesis.

Competing Hypotheses Alternative hypothesis (Ha): Poor academic performance in the early elementary school years is positively related to juvenile delinquency in the adolescent years. Null hypothesis (Ho): Poor academic performance in the early elementary school years is not related to juvenile delinquency in the adolescent years.

The Structure of Research In this research project the researcher wants to prove that the alternative hypothesis is a true statement. Before doing so, the researcher must first prove that the null hypothesis is a false statement.

The Structure of Research If, the data lead the researcher to the conclusion that; Poor academic performance in the early elementary school years is not related to juvenile delinquency in the adolescent years (i.e. the null hypothesis). Then the researcher will accept the null hypothesis and reject the alternative hypothesis.

The Structure of Research If on the other, hand the data lead the researcher to the conclusion that; Poor academic performance in the early elementary school years is not related to juvenile delinquency in the adolescent years (i.e. the null hypothesis). Is a false statement. Then, the researcher will reject the null hypothesis and accept the alternative hypothesis.

Why so Formal? Why not just ignore the null hypothesis and try to prove the alternative hypothesis? Just as the criminal justice system must presume innocence, so, too, must a researcher presume no relationship between the variables in a research project. The formal structure of research is intended to insure the quality of research findings. Making Research Real 7.5 – Can’t We Just Agree on the Question?(p. 149) A police chief and university professor are evaluating the effectiveness of a robbery suppression program. Conflict exists between them because of the way they present the research question. They are asking the same question, but the professor developed null and alternative hypotheses while the chief just asked whether the program worked or not. Both are correct in their approaches but the professor’s approach provides more detailed insight into the problem.   Making Research Real 7.6 – Sherlock the Researcher A woman reports a burglary. The police respond and a detective makes an arrest. The detective later learns that the person accused of burglarizing the residence had permission to use the ‘stolen’ property. This story illustrates the similarities between the structure of research (null and alternative hypotheses) and the criminal investigation process.

Other Types of Hypotheses Separate from the distinction between the null and alternative hypotheses, a hypothesis can also be categorized into one of two types. A hypothesis of association A hypothesis of difference This distinction is important because it determines how the researcher will analyze the data.

The Hypothesis of Association A hypothesis of association alleges that a change in the independent variable(s) is associated with a change in the dependent variable. In most cases the independent variable in a hypothesis of association will be measured at the ordinal, interval or ratio level of measurement. Hence, the data used to test a hypothesis of association can be illustrated in a linear graph.

The Hypothesis of Difference A hypotheses of difference alleges that the independent variable(s) makes groups different with respect to the dependent variable. In most cases the independent variable in a hypothesis of difference will be measured at the nominal level of measurement. Hence, the data used to test a hypothesis of difference can be illustrated in a bar graph.

Getting to the Point A variable is any characteristic of an individual, group, organization or social phenomenon that changes.

Getting to the Point An independent variable is the causal variable, or the variable that a researcher predicts will be the cause of a change in another variable. A dependent variable is the effect, or the variable that a researcher predicts will change as a result of a change in another variable or set of variables.

Getting to the Point An intervening variable is any variable that occurs between the independent and dependent variables, changing how, or even if, the independent variable affects a dependent variable.

Getting to the Point Attributes are the different characteristics or values that a variable can take on.   Exhaustiveness refers to the completeness of the list of a variable’s attributes. Mutual exclusivity refers to the capacity for a list of attributes to provide one, and only one, option for each respondent

Getting to the Point Good research questions should be; Measurable, Unanswered, Feasible, and Disinteresting.

Getting to the Point A hypothesis is a statement that predicts how a change in one or more variables will cause a change in another variable. An alternative hypothesis is a predictive statement that alleges a plausible connection between two or more variables. A null hypothesis is a statement that alleges no plausible connection between two or more variables.

Getting to the Point A hypothesis of association alleges that a change in the independent variable(s) is associated with a change in the dependent variable. If the independent variable is ordinal, interval or ratio, the hypothesis will be one of association. Hence, the data used to test a hypothesis of association can be illustrated in a linear graph.

Getting to the Point A hypothesis of difference alleges that the independent variable(s) makes groups different with respect to the dependent variable. If the independent variable is nominal, the hypothesis will be one of difference. Hence, the data used to test a hypothesis of difference can be illustrated in a bar graph.

Research Methods in Crime and Justice Chapter 7 Variables and the Structure of Research