Each person/thing we collect data on is called an **OBSERVATION** (in our work these are usually people/subjects. Currently, the term participant rather than subject is used when describing the people from whom we collect data).

OBSERVATIONS (participants) possess a variety of **CHARACTERISTICS**.

If a CHARACTERISTIC of an OBSERVATION (participant) is the same for every member of the group (doesn’t vary) it is called a **CONSTANT**.

If a CHARACTERISTIC of an OBSERVATION (participant) differs for group members it is called a **VARIABLE**. In research we don’t get excited about CONSTANTS (since everyone is the same on that characteristic); we’re more interested in VARIABLES. Variables can be classified as QUANTITATIVE or QUALITATIVE (also known as CATEGORICAL).

QUANTITATIVE variables are ones that exist along a continuum that runs from low to high. Ordinal, interval, and ratio variables are quantitative. QUANTITATIVE variables are sometimes called CONTINUOUS VARIABLES because they have a variety (continuum) of characteristics. Height in inches and scores on a test would be examples of quantitative variables.

QUALITATIVE variables do not express differences in amount, only differences. They are sometimes referred to as CATEGORICAL variables because they classify by categories. Nominal variables such as gender, religion, or eye color are CATEGORICAL variables. Generally speaking, categorical variables

Categorical variables are groups…such as gender or type of degree sought. Quantitative variables are numbers that have a range…like weight in pounds or baskets made during a ball game. When we analyze data we do turn the categorical variables into numbers but only for identification purposes…e.g. 1 = male and 2 = female. Just because 2 = female does not mean that females are better than males who are only 1. With quantitative data having a higher number means you have more of something. So higher values have meaning. |

A special case of a CATEGORICAL variable is a DICHOTOMOUS VARIABLE. DICHOTOMOUS variables have only two CHARACTERISTICS (male or female). When naming QUALITATIVE variables, it is important to name the category rather than the levels (i.e., gender is the variable name, not male and female).

*Variables have different purposes or roles…*

**Independent (Experimental, Manipulated, Treatment, Grouping) Variable-***That factor which is measured, manipulated, or selected by the experimenter to determine its relationship to an observed phenomenon.* “In a research study, independent variables are antecedent conditions that are presumed to affect a dependent variable. They are either manipulated by the researcher or are observed by the researcher so that their values can be related to that of the dependent variable. For example, in a research study on the relationship between mosquitoes and mosquito bites, the number of mosquitoes per acre of ground would be an independent variable” (Jaeger, 1990, p. 373)

While the independent variable is often manipulated by the researcher, it can also be a classification where subjects are assigned to groups. In a study where one variable causes the other, the independent variable is the cause. In a study where groups are being compared, the independent variable is the group classification.

**Dependent (Outcome) Variable-***That factor which is observed and measured to determine the effect of the independent variable, i.e., that factor that appears, disappears, or varies as the experimenter introduces, removes, or varies the independent variable. *“In a research study, the independent variable defines a principal focus of research interest. It is the consequent variable that is presumably affected by one or more independent variables that are either manipulated by the researcher or observed by the researcher and regarded as antecedent conditions that determine the value of the dependent variable. For example, in a study of the relationship between mosquitoes and mosquito bites, the number of mosquito bites per hour would be the dependent variable” (Jaeger, 1990, p. 370). The dependent variable is the participant’s response.

The dependent variable is the outcome. In an experiment, it may be what was caused or what changed as a result of the study. In a comparison of groups, it is what they differ on.

**Moderator Variable-** *That factor which is measured, manipulated, or selected by the experimenter to discover whether it modifies the relationship of the independent variable to an observed phenomenon. It is a special type of independent variable.*

The independent variable’s relationship with the dependent variable may change under different conditions. That condition is the moderator variable. In a study of two methods of teaching reading, one of the methods of teaching reading may work better with boys than girls. Method of teaching reading is the independent variable and reading achievement is the dependent variable. Gender is the moderator variable because it moderates or changes the relationship between the independent variable (teaching method) and the dependent variable (reading achievement).

Suppose we do a study of reading achievement where we compare whole language with phonics, and we also include students’ social economic status (SES) as a variable. The students are randomly assigned to either whole language instruction or phonics instruction. There are students of high and low SES in each group.

Let’s assume that we found that whole language instruction worked better than phonics instruction with the high SES students, but phonics instruction worked better than whole language instruction with the low SES students. Later you will learn in statistics that this is an interaction effect. In this study, language instruction was the independent variable (with two levels: phonics and whole language). SES was the moderator variable (with two levels: high and low). Reading achievement was the dependent variable (measured on a continuous scale so there aren’t levels).

With a moderator variable, we find the type of instruction did make a difference, but it worked differently for the two groups on the moderator variable. We select this moderator variable because we think it is a variable that will moderate the effect of the independent on the dependent. We make this decision before we start the study.

If the moderator had not been in the study above, we would have said that there was no difference in reading achievement between the two types of reading instruction. This would have happened because the average of the high and low scores of each SES group within a reading instruction group would cancel each other an produce what appears to be average reading achievement in each instruction group (i.e., Phonics: Low—6 and High—2; Whole Language: Low—2 and High—6; Phonics has an average of 4 and Whole Language has an average of 4. If we just look at the averages (without regard to the moderator), it appears that the instruction types produced similar results).

**Extraneous Variable-** *Those factors which cannot be controlled.*

Extraneous variables are independent variables that have not been controlled. They may or may not influence the results. One way to control an extraneous variable which might influence the results is to make it a constant (keep everyone in the study alike on that characteristic). If SES were thought to influence achievement, then restricting the study to one SES level would eliminate SES as an extraneous variable.

Here are some examples similar to your homework:

Null Hypothesis: Students who receive pizza coupons as a reward do not read more books than students who do not receive pizza coupon rewards.

Independent Variable: Reward Status

Dependent Variable: Number of Books Read

High achieving students do not perform better than low achieving student when writing stories regardless of whether they use paper and pencil or a word processor.

Independent Variable: Instrument Used for Writing

Moderator Variable: Ability Level of the Students

Dependent Variable: Quality of Stories Written

When we are comparing two groups, the groups are the independent variable. When we are testing whether something influences something else, the influence (cause) is the independent variable. The independent variable is also the one we manipulate. For example, consider the hypothesis “Teachers given higher pay will have more positive attitudes toward children than teachers given lower pay.”

One approach is to ask ourselves “Are there two or more groups being compared?” The answer is “Yes.” “What are the groups?” Teachers who are given higher pay and teachers who are given lower pay. Therefore, the independent variable is teacher pay (it has two levels– high pay and low pay). The dependent variable (what the groups differ on) is attitude towards school.

We could also approach this another way. “Is something causing something else?” The answer is “Yes.”

“What is causing what?” Teacher pay is causing attitude towards school. Therefore, teacher pay

is the independent variable (cause) and attitude towards school is the dependent variable (outcome).

Research Questions and Hypotheses

The research question drives the study. It should specifically state what is being investigated. Statisticians often convert their research questions to null and alternative hypotheses. The null hypothesis states that no relationship (correlation study) or difference (experimental study) exists. Converting research questions to hypotheses is a simple task. Take the questions and make it a positive statement that says a relationship exists (correlation studies) or a difference exists (experiment study) between the groups and we have the alternative hypothesis. Write a statement that a relationship does not exist or a difference does not exist and we have the null hypothesis.

*Format for sample research questions and accompanying hypotheses:*

**Research Question for Relationships:** Is there a relationship between height and weight?

**Null Hypothesis: ** There is no relationship between height and weight.

**Alternative Hypothesis:** There is a relationship between height and weight.

When a researcher states a nondirectional hypothesis in a study that compares the performance of two groups, she doesn’t state which group she believes will perform better. If the word “more” or “less” appears in the hypothesis, there is a good chance that we are reading a directional hypothesis. A directional hypothesis is one where the researcher states which group she believes will perform better. Most researchers use nondirectional hypotheses.

We usually write the alternative hypothesis (what we believe might happen) before we write the null hypothesis (saying it won’t happen).

*Directional*

**Research Question for Differences:** Do boys like reading more than girls?

**Null Hypothesis:** Boys do not like reading more than girls.

**Alternative Hypothesis:** Boys do like reading more than girls.

*Nondirectional*

**Research Question for Differences:** Is there a difference between boys’ and girls’ attitude towards reading? –or– Do boys’ and girls’ attitude towards reading differ?

**Null Hypothesis:** There is no difference between boys’ and girls’ attitude towards reading. –or– Boys’ and girls’ attitude towards reading do not differ.

**Alternative Hypothesis:** There is a difference between boys’ and girls’ attitude towards reading. –or– Boys’ and girls’ attitude towards reading differ.

Del Siegle, Ph.D.

Neag School of Education – University of Connecticut

del.siegle@uconn.edu

www.delsiegle.com