Behavioral Statistics 01 - A and B

Nominal Scales

When numbers are used as names that correspond to a specific category.

EX: Survey on Eye Color

Ordinal Scale

Numbers that correspond to categories that can be ranked on characteristics and traits (value).

EX: Class Rank

• Broad categories; the difference between participants is not known

Interval Scale

Equal distant measurements with no definite zero

EX: Temperature in Fahrenheit

• Distance between each unit is EQUAL

Ratio Scale

True zero measurements that indicate consistent differences between values

EX: Number of trips to the beach this year

• Can be weight, height, speed, time…

• Ratio comparison between two points can occur as well

Descriptive statistics

summarizing, describing, and understanding the data collected.

Inferential statistics

used to make predictions and draw conclusions about an entire population

Representative samples

accurately reflect the characteristics of their population.

Scientific method

Test a theory by making observations in a systematic and unbiased manner.

1. Develop a theory

2. Specify the hypothesis

3. Test the prediction with systematic observations.

Systematic

Methodical in procedure or plan.

Systematic Observations

following a specific procedure or plan for collecting the data.

• The same outcome should occur despite variability in participants or settings.

Representative Observations

representative sample of participants and a representative sample of their behaviors.

• must be systematic and numerous enough to capture the diversity

  and typical patterns of behavior.

Theory

One or more statements that help us to describe, predict, and control the world

around us.

Falsifiable

A statement that can be tested

• Can be shown to be false or true

Scientific Theory

Only theories that are falsifiable are considered scientific.

• A theory would not be considered a scientific theory if it could not be tested

Operational Definition

Specifies how something will be measured

• EX: height, happiness

Measurement Validity

The operational definition truly measures what it is intended to measure

Measurement Reliability

Multiple measurements all provide the same result

Hypothesis

A specific prediction

• The hypothesis is stated in future tense

• written using operational definitions.

Variable

Can have more than one value

• EX: Body temperature: Degrees Fahrenheit

Dependent Variable

What the researcher measures (Dependent on the x-axis variable)

—> Determined by the participant

• EX: Happiness: Score on the happiness scale

Independent Variable

What the researcher manipulates (Independent of the y-axis—can be manipulated)

—> Determined by the researcher

• EX: Exercise: 0 vs. 60 minutes

Subject Variable

A characteristic of the subjects used to divide the participants into groups

EX: Age: 20 years old vs. 50 years old (Cohorts)

Constant

A value that the researcher wishes to keep the same for everyone

Null Hypothesis

This is the hypothesis that the researcher wishes to reject

• The null hypothesis specifies that random chance is the explanation for any observations – either differences observed between groups or relationships measured between variables.

• Even if the null hypothesis is true, we do not expect all groups to be exactly equal, or the relationship between variables to be exactly zero.

Research Hypothesis

A prediction, written in future tense and using operational definitions.

• Specifies what we expect to observe if the theory is correct

EX: a real difference between groups or a relationship between variables

Mutually Exclusive

No overlap – only one outcome is possible

• EX: heads or tails on a coin flip

Systematic

Methodical in procedure or plan.

Survey

A list of questions that the participant answers

Correlational Research

The researcher states a prediction about the relationship between two variables before collecting any research data

• SAT score and college GPA

Experiment

An experiment is the only research method that enables a person to determine a

cause-and-effect relationship.

1. Start with at least two equivalent groups of participants

2. Manipulate at least one aspect between the two groups

3. Observe whether the manipulation had an effect.

Treatment Group

The treatment group receives the treatment, meaning that they attend the study workshop.

Control Group

The control group represents those participants not receiving the treatment.

Confound

An alternative explanation for the research results.

• occurs whenever something other than the independent variable can account for the

results of an experiment.