Different Variables in Quantitative Research~GM Lectures
TLDRThis lecture delves into the concept of variables, crucial for understanding research studies. It explains that variables are entities that can change or affect study outcomes, and can be classified into numeric (continuous, interval, discrete) and categorical (ordinal, nominal, dichotomous, polycautimus). The talk further distinguishes between experimental variables (independent, dependent, control, moderating, extraneous) and non-experimental variables (predictor, criterion), emphasizing their roles in establishing causal relationships and controlling for confounding factors. The importance of recognizing and classifying variables is highlighted for meaningful study outcomes.
Takeaways
- 📚 Variables are essential in research studies to understand differences and can be anything that varies and affects the results.
- 🔢 Numeric variables describe measurable quantities and are divided into continuous/interval and discrete variables.
- ⏳ Continuous or interval variables can take any value within a range, such as time, age, weight, and height.
- 🔢 Discrete variables only take whole numbers, like class attendance or the number of children in a family.
- 🏷 Categorical variables describe qualities or characteristics and are qualitative, including ordinal, nominal, dichotomous, and polycautimus variables.
- 🔖 Ordinal variables can be logically ordered or ranked, such as clothing sizes, academic rankings, and satisfaction levels.
- 🔍 Nominal variables are for identification and cannot be logically ranked, like blood types, learning styles, and languages spoken.
- 👥 Dichotomous variables have only two categories, such as yes/no or true/false.
- 🏆 Polycautimus variables have many possible categories, like performance levels and educational attainment.
- 🔧 Experimental variables determine causal relationships and include independent, dependent, control, moderating, and extraneous variables.
- 🔄 Independent variables are manipulated to cause changes, while dependent variables change as a result.
- 🎚 Control variables are held constant to isolate the effects of the independent variable.
- 📊 Moderator variables affect how the relationship between independent and dependent variables changes under different conditions.
- 🚫 Extraneous variables are existing variables that could influence the results and should be controlled to avoid confounding the study.
- 📉 Non-experimental variables cannot be manipulated and include predictor variables that affect criterion variables in non-experimental studies.
Q & A
What factors might influence low academic performance according to the teacher's perspective in the script?
-The factors that might influence low academic performance include students not understanding instructions, sleeping instead of studying, running out of time to finish tests, and being unable to focus during review sessions.
What is the definition of a variable in the context of research studies?
-A variable is an entity that can take on different values, an aspect of a theory that can vary or change, or anything that can change or affect the results of a particular study.
How are variables classified in terms of their nature?
-Variables are classified as numeric, categorical, experimental, or non-experimental, which determines their roles in a particular study.
What are the two main types of numeric variables and how do they differ?
-Numeric variables are divided into continuous or interval variables and discrete variables. Continuous or interval variables can assume any value within a set of real numbers, while discrete variables can only assume whole numbers.
Can you provide examples of continuous or interval variables mentioned in the script?
-Examples of continuous or interval variables include time (hours, minutes, seconds), age (ten and a half, ten and three quarters), weight (grams, milligrams), and height (feet, centimeters, inches).
What are discrete variables and provide some examples?
-Discrete variables focus on whole numbers and do not recognize values in between. Examples include class attendance, number of establishments in an area, and number of children in a family.
How are categorical variables defined and what are their subtypes?
-Categorical variables describe a quality or characteristic of a data unit and are qualitative in nature. They are further divided into ordinal, nominal, dichotomous, and polycautimus variables.
What is the purpose of ordinal variables and provide an example?
-Ordinal variables serve the purpose of classification and ranking. An example would be academic ranking where a person who ranks first is different from someone who ranks second or third.
How do nominal variables differ from ordinal variables?
-Nominal variables are for classification and identification purposes only and cannot be arranged logically in terms of ranking, unlike ordinal variables which can be organized or ranked.
What is the role of experimental variables in determining causal relationships?
-Experimental variables help determine causal relationships by manipulating independent variables to observe changes in dependent variables, while controlling for control variables and considering moderator and extraneous variables.
Can you explain the difference between independent and dependent variables?
-Independent variables are presumed to cause changes in another variable and are usually manipulated in an experiment. Dependent variables change because of another variable and are usually affected by the manipulation of the independent variable.
What are control variables and moderator variables in the context of an experiment?
-Control variables are held constant to identify possible differences in outcomes, while moderator variables delineate how a relationship of interest changes under different conditions or circumstances.
What is the role of extraneous variables in a study and why are they important to control?
-Extraneous variables are existing variables during an experiment that could influence the results. They are important to control because they can offer alternative results and affect the validity of the study.
How are non-experimental variables different from experimental variables?
-Non-experimental variables cannot be manipulated by the researcher and are used in non-experimental studies. They are classified into predictor variables, which affect other variables, and criterion variables, which are influenced by predictor variables.
Why is it important for researchers to recognize and understand the classification and roles of variables in their study?
-Recognizing variables and understanding their classification and roles helps researchers have a more detailed idea of how the variables in their study interact and affect each other, contributing to a more meaningful discussion regarding the possible outcomes of a study.
Outlines
🔍 Variables Influencing Academic Performance
This paragraph introduces the concept of variables in the context of a teacher analyzing factors affecting students' low academic performance. It lists potential factors such as misunderstanding instructions, lack of study, time constraints, and lack of focus. The paragraph then defines a variable as an entity that can assume different values and change or vary within a study, emphasizing that any factor that can vary is considered a variable. It concludes by stating the importance of variables in understanding differences in research studies.
📊 Classification of Variables: Numeric and Categorical
The second paragraph delves into the classification of variables, focusing on numeric and categorical types. Numeric variables, which include measurable quantities, are further divided into continuous or interval variables and discrete variables. Continuous variables can take any value within a range, exemplified by time, age, weight, and height, while discrete variables are limited to whole numbers, such as class attendance and the number of children in a family. Categorical variables describe qualities or characteristics and are qualitative in nature, subdivided into ordinal, nominal, dichotomous, and polycautimus variables. Ordinal variables can be ranked, like clothing size and academic ranking, whereas nominal variables are for identification and classification, such as learning styles and blood types. Dichotomous variables have two categories, like gender, and polycautimus variables have multiple categories, like performance levels.
🧐 The Role of Variables in Experimental Design
This paragraph discusses the role of variables in experimental studies, distinguishing between experimental and non-experimental variables. Experimental variables determine causal relationships and include independent variables, which are manipulated to cause changes, and dependent variables, which change as a result. The paragraph provides examples to illustrate these concepts, such as studying affecting academic performance and diet and exercise affecting physical fitness. It also introduces control variables, which are held constant to identify differences in outcomes, and moderator variables, which influence how relationships change under different conditions. Extraneous variables, which can affect study results and should be controlled, are also mentioned, with an example of a study on the effect of music on academic performance, where genre of music could be a moderator variable and class duration a control variable.
🏛️ Non-Experimental Variables and Their Impact
The final paragraph addresses non-experimental variables, which cannot be manipulated by researchers and are used in non-experimental studies. It differentiates between predictor variables, which can affect other variables, and criterion variables, which are influenced by predictor variables. Examples given include management styles affecting employee satisfaction and guidance counseling programs influencing absenteeism and dropout rates among students. The paragraph emphasizes the importance of recognizing and understanding the roles of variables in a study to facilitate meaningful discussions about potential outcomes.
Mindmap
Keywords
💡Variable
💡Numeric Variable
💡Categorical Variable
💡Ordinal Variable
💡Nominal Variable
💡Discrete Variable
💡Continuous Variable
💡Experimental Variable
💡Independent Variable
💡Dependent Variable
💡Control Variable
💡Moderating Variable
💡Extraneous Variable
💡Non-Experimental Variable
Highlights
A teacher wants to identify factors influencing low academic performance.
Variables are factors that contribute to a study, such as understanding instructions, studying habits, time management, and focus.
A variable is an entity that can take on different values and affect the results of a study.
Variables can be anything that a researcher is interested in and can vary.
Variables are classified as numeric, categorical, experimental, or non-experimental based on their roles in a study.
Numeric variables describe measurable quantities and can be continuous, interval, or discrete.
Continuous or interval variables can take any value within a range, like time, age, and weight.
Discrete variables only take whole values, such as class attendance or the number of children in a family.
Categorical variables describe qualities or characteristics and are qualitative in nature.
Ordinal variables can be logically ordered or ranked, like clothing sizes or academic rankings.
Nominal variables are for identification and cannot be logically sequenced, like blood types or learning styles.
Dichotomous variables represent two categories, such as yes/no or true/false.
Polycautimus variables have many possible categories, like performance levels or educational attainment.
Experimental variables determine causal relationships and include independent, dependent, control, moderating, and extraneous variables.
Independent variables are presumed to cause changes in another variable and are manipulated in an experiment.
Dependent variables change because of another variable and are monitored in an experiment.
Control variables are held constant to identify differences in outcomes, while moderator variables change the relationship under different conditions.
Extraneous variables are existing variables that can influence study results and should be controlled.
Non-experimental variables cannot be manipulated and include predictor and criterion variables.
Recognizing variables and their classification helps researchers understand interactions and outcomes in a study.
Transcripts
Browse More Related Video
Types of Variables in Research and Their Uses (Practical Research 2)
Variables and Types of Variables | Statistics Tutorial | MarinStatsLectures
Research Variables 101: Dependent, Independent, Control Variables & More (With Examples)
Regression analysis
Classification of Variables and Types of Measurement Scales
Variables in Science: Independent, Dependent and Controlled!
5.0 / 5 (0 votes)
Thanks for rating: