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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.

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.

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.

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.

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.

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.

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