Variables Flashcards
Measurable elements that can change or vary. They can refer to characteristics such as age, gender, intelligence, and others that are central to research studies.
Variables
The two (2) Types of Variables are:
- Quantitative
- Qualitative
There are 3 Kinds of Quantitative Variables. These include:
- Discrete
- Continuous
- Ratio
Can be counted, only whole numbers (e.g., group sizes, frequency of behavior)
Discrete Variables
Measured in ranges, can include fractions or decimals (e.g., temperature)
Continuous Variables
Special type of continuous variable that cannot have negative values (e.g., age, height, test scores)
Ratio Variables
There are three (3) Kinds of Qualitative Variables. These include:
- Dichotomous
- Nominal
- Ordinal
Two distinct categories (e.g., yes/no answers)
Dichotomous Variables
More than two categories (e.g., blood type, marital status)
Nominal Variables
Have ranked or ordered values (e.g., frequency of actions, grades A+, A, B)
Ordinal Variables
There are three (3) Types of Variable Relationships. These include:
- Independent Variables
- Dependent Variables
- Extraneous Variables (+ Confounding Variables)
Cause changes in the dependent variable, manipulated by the researcher (e.g., in an experiment).
Independent Variables
Are affected by the independent variable; the presumed effect.
Dependent Variables
Any variable that is not independent or dependent but could affect the results of a study.
Extraneous Variables
When an extraneous variable influences the dependent variable and not the independent variable.
Confounding Variables
Other Variable Types include:
- Attribute Variables
- Covariate Variables
- Latent Variables
- Manifest Variables
Characteristics of participants (e.g., intelligence, creativity).
Attribute Variables
Interact with independent and dependent variables.
Covariate Variables
Not directly observable (e.g., personality traits).
Latent Variables
Observable and measurable variables that indicate the presence of latent variables.
Manifest Variables
Example: The number of cars in a parking lot; the number of students in a class
Discrete Variables
Example: The height of students in a classroom; temperature in a room
Continuous Variables
Example: A person’s age measured in years; weight of a product
Ratio Variables
Example: Whether a student passed or failed an exam (pass/fail); sex (male/female)
Dichotomous
Example: Level of satisfaction with a product; educational attainment
Ordinal Variables
Example: In an experiment studying the effect of sleep on test performance, the amount of
sleep is the [][].
Independent Variables
Example: In a weight loss program study, the [][] would be the amount of weight lost by participants after following a specific diet or exercise plan.
Dependent Variable
Example: In a study on the effect of exercise on weight loss, diet could be a(n) [][] if not controlled because participants who exercise and eat healthily might lose more weight.
extraneous variable
Example: In a study on the impact of diet on heart disease, age could be a [][] as older participants are more likely to have heart disease regardless of their diet.
confounding variable
Example: Intelligence or creativity level, which might be measured using IQ tests or creativity assessments.
Attribute Variable
Example: In a study on physical activity and heart health, body mass index (BMI) might be a [][] since it can influence both activity levels and heart health.
covariate variable
Example: Personality traits like extroversion or introversion
Latent Variable
Example: Scores on a questionnaire assessing extroversion
Manifest Variables
(provided measurable indications of the latent personality trait)
