Types of Variance

Discuss the following in relation to research design

Systematic Variance: This is associated with the main variable of the hypothesis and is maximized by ensuring that the methods, treatments, independent variables etc are not alike.

Extraneous variance: These are external factors to the study, which can influence the dependent variable. You can take care of this by randomising your subjects (sample), using statistical control, matching the subjects, including the factors as moderator or attribute variable etc.

Error Variance: This comes mainly from measurement and individual difference (fatigue, guessing, lapses in memory, inconsistency of responses etc). This is often

control with controlled experiments. Again, the use of valid and reliable instruments is of utmost importance.


  1. Systematic Variance: This pertains to the variability in your data that is directly related to the main variable of interest in your hypothesis. To maximize systematic variance, it’s important to ensure that your research methods, treatments, and independent variables are distinct and not similar. By carefully designing your experimental conditions and manipulating your independent variables effectively, you can enhance the systematic variance in your study.
  2. Extraneous Variance: Extraneous variance refers to the influence of external factors on the dependent variable that are not part of the primary research focus. These factors can introduce noise and potentially obscure the effects you’re trying to measure. To address extraneous variance, researchers employ strategies such as randomizing the sample to distribute these external factors evenly, using statistical control techniques to account for their effects, matching subjects in experimental and control groups, or even including these factors as moderator or attribute variables to understand their impact better.
  3. Error Variance: Error variance emerges due to factors like measurement inaccuracies and individual differences among participants (e.g., fatigue, guessing, memory lapses, response inconsistencies). This type of variance can obscure the true effects of your independent variables on the dependent variable. Controlled experiments are often used to manage error variance by minimizing external influences and ensuring that changes in the dependent variable are primarily attributed to changes in the independent variable. It’s vital to use valid and reliable measurement instruments to minimize measurement-related error and enhance the accuracy of your findings.

By understanding and effectively addressing these different types of variance, researchers can enhance the validity and reliability of their research designs and draw more accurate conclusions from their studies.


Systematic Variance:

  1. Study on Study Habits and Exam Performance: To maximize systematic variance, researchers could vary the type of study material (textbooks, online resources, videos) provided to different groups of students while keeping other factors constant.
  2. Effect of Different Exercise Intensities on Weight Loss: Researchers might manipulate exercise intensity levels (low, moderate, high) to examine how systematic variance changes the outcomes in terms of weight loss among participants.
  3. Impact of Advertisements on Brand Preference: By exposing participants to distinct types of advertisements (humorous, emotional, informative), researchers can generate systematic variance in brand preference responses.
  4. Influence of Teaching Methods on Language Learning: Researchers could employ different teaching methods (immersive, traditional, technology-based) to create systematic variance in language learning outcomes among students.
  5. Effect of Lighting on Mood: To maximize systematic variance, researchers might expose participants to different lighting conditions (natural light, fluorescent light, dim lighting) to gauge the impact on mood ratings.

Extraneous Variance:

  1. Examining the Effect of a New Drug: Researchers randomize participants to control for extraneous factors like age, gender, and pre-existing health conditions that could influence the drug’s effectiveness.
  2. Studying the Impact of Nutrition Programs: To minimize extraneous variance, researchers match participants based on factors like socioeconomic status and dietary habits before assigning them to different nutrition programs.
  3. Investigating the Effect of Noise Levels on Concentration: Researchers control for extraneous variables by assigning participants to different noise conditions (silent, moderate, noisy) while ensuring that other factors like sleep quality and caffeine intake are evenly distributed.
  4. Research on Leadership Styles and Employee Performance: Researchers might use statistical control to account for extraneous factors like work experience and job role when analyzing the relationship between leadership styles and performance outcomes.
  5. Exploring the Influence of Social Media Usage on Self-Esteem: By including extraneous factors like age, gender, and baseline self-esteem levels as attribute variables, researchers can better understand the nuanced effects of social media on self-esteem.

Error Variance:

  1. Measuring Reaction Times: Individual differences in attention and motor skills might introduce error variance when measuring reaction times, so researchers use multiple trials and advanced measurement techniques to minimize this variability.
  2. Assessing Memory Recall: Error variance can arise due to lapses in memory, so researchers use techniques like recall practice and spaced repetition to control for this and improve the reliability of memory assessments.
  3. Surveying Attitudes Towards Political Issues: Error variance from response inconsistency can be mitigated by using clear and unbiased questions in surveys, along with analyzing response patterns to identify potential outliers.
  4. Evaluating Pain Perception: In pain studies, error variance due to participants’ subjective interpretations can be reduced by using standardized pain scales and controlling for factors like mood changes during the experiment.
  5. Testing Visual Acuity: Error variance in visual acuity measurements can be minimized by using calibrated equipment and ensuring participants are well-rested to reduce factors like eye strain and fatigue.

Remember, these examples illustrate how systematic, extraneous, and error variance can impact research outcomes, and how researchers employ various techniques to manage these types of variance to ensure the validity and reliability of their studies




Briefly discuss the arguments of: Economic Determinism, Hegelian Marxism and Critical Theory


  1. Systematic Variance is associated with the ____ variable of the hypothesis and is maximized by ensuring that the methods, treatments, independent variables, etc., are not alike.
    • a) dependent
    • b) extraneous
    • c) main
  2. Extraneous variance refers to external factors that can influence the ____ variable of the study.
    • a) independent
    • b) extraneous
    • c) dependent
  3. One way to address extraneous variance is by ____ subjects to distribute external influences evenly among groups.
    • a) randomizing
    • b) measuring
    • c) excluding
  4. ____ is a strategy used to control extraneous variance by adjusting for the effects of certain variables through statistical methods.
    • a) Sampling
    • b) Randomizing
    • c) Statistical control
  5. To manage extraneous variance, researchers might include extraneous factors as ____ variables in their study.
    • a) dependent
    • b) moderator
    • c) independent
  6. Error variance in research mainly arises from issues related to ____ and individual differences.
    • a) systematic variance
    • b) extraneous variance
    • c) measurement
  7. One way to control error variance is through the use of controlled experiments and maintaining ____ conditions.
    • a) consistent
    • b) variable
    • c) unpredictable
  8. ____ in responses, such as guessing and lapses in memory, contribute to error variance in research studies.
    • a) Consistency
    • b) Inconsistencies
    • c) Reliability
  9. The use of ____ instruments is crucial to minimizing error variance in research measurements.
    • a) novel
    • b) valid and reliable
    • c) complex
  10. Experiments that control for error variance involve manipulating the ____ variable while keeping other variables constant.
    • a) independent
    • b) dependent
    • c) extraneous
  11. ____ variance is enhanced by ensuring that methods, treatments, and independent variables are distinct and dissimilar.
    • a) Extraneous
    • b) Systematic
    • c) Error
  12. Researchers address ____ variance by randomizing subjects, using statistical control, and including extraneous factors as attribute variables.
    • a) systematic
    • b) extraneous
    • c) error
  13. A technique used to minimize ____ variance is by matching subjects based on certain characteristics before assigning them to groups.
    • a) systematic
    • b) extraneous
    • c) error
  14. To manage error variance, researchers should use measurement instruments that are both valid and ____.
    • a) consistent
    • b) novel
    • c) reliable
  15. One way to control extraneous variance is by including extraneous factors as ____ variables in the study design.
    • a) dependent
    • b) moderator
    • c) systematic