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bias sources

Random Error vs Systematic Error

By Jim Frost Leave a Comment

Random error and systematic error are the two main types of measurement error. Measurement error occurs when the measured value differs from the true value of the quantity being measured. [Read more…] about Random Error vs Systematic Error

Filed Under: Basics Tagged With: bias sources, conceptual, measurement error

Dunning Kruger Effect: Definition & Examples

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What is the Dunning Kruger Effect?

The Dunning-Kruger effect is a cognitive bias that causes people with low abilities or knowledge to overestimate themselves compared to others. Conversely, people with high skills tend to underestimate themselves. In short, it is a psychological phenomenon that distorts our self-evaluation. [Read more…] about Dunning Kruger Effect: Definition & Examples

Filed Under: Basics Tagged With: bias sources, conceptual

Confirmation Bias Definition and Examples

By Jim Frost Leave a Comment

What is Confirmation Bias?

Confirmation bias is the tendency to seek information confirming preexisting beliefs while ignoring information contradicting them. This bias can be particularly problematic when making important decisions, leading to flawed reasoning and inaccurate conclusions. It is a type of cognitive bias. [Read more…] about Confirmation Bias Definition and Examples

Filed Under: Basics Tagged With: bias sources, conceptual

Cognitive Bias: Definition & Examples

By Jim Frost Leave a Comment

What is Cognitive Bias?

A cognitive bias is a systematic fault in thinking and decision-making that can affect our judgments and perceptions. These biases can arise due to our limited mental capacity, the complexity of the environment, and the influence of our prior experiences and beliefs. [Read more…] about Cognitive Bias: Definition & Examples

Filed Under: Basics Tagged With: bias sources, conceptual

Selection Bias: Definition & Examples

By Jim Frost Leave a Comment

What is Selection Bias?

Selection bias occurs when researchers make decisions that cause a sample to be systematically different from the population of interest.

Selection bias can arise from various decisions, such as:

  • Using an improper sampling method.
  • Making particular methodology and data choices.
  • Choosing a study design that affects the continued participation of subjects.

[Read more…] about Selection Bias: Definition & Examples

Filed Under: Basics Tagged With: bias sources, conceptual, experimental design, sampling methods

Undercoverage Bias: Definition & Examples

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What is Undercoverage Bias?

Undercoverage bias occurs when the population list from which the researchers select their sample (aka the sampling frame) does not include all population members. When that happens, the sample cannot contain the unlisted individuals, potentially producing a biased sample that doesn’t fully represent the population. [Read more…] about Undercoverage Bias: Definition & Examples

Filed Under: Basics Tagged With: bias sources, conceptual, experimental design

Nonresponse Bias: Definition & Reducing

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What is Nonresponse Bias?

Nonresponse bias occurs when people who do not participate in a survey or study have different characteristics or opinions than those who do participate. In this situation, the sample data overrepresent the subpopulations who tend to respond instead of reflecting the whole population. [Read more…] about Nonresponse Bias: Definition & Reducing

Filed Under: Basics Tagged With: bias sources, conceptual, experimental design

Simpsons Paradox Explained

By Jim Frost 4 Comments

What is Simpsons Paradox?

Simpsons Paradox is a statistical phenomenon that occurs when you combine subgroups into one group. The process of aggregating data can cause the apparent direction and strength of the relationship between two variables to change. [Read more…] about Simpsons Paradox Explained

Filed Under: Basics Tagged With: bias sources, conceptual

Sampling Bias: Definition & Examples

By Jim Frost 2 Comments

What is Sampling Bias?

Sampling bias in statistics occurs when a sample does not accurately represent the characteristics of the population from which it was drawn. When this bias occurs, sample attributes are systematically different from the actual population values. Hence, sampling bias produces a distorted view of the population. Sampling bias often involves human subjects, but it can also apply to samples of objects and animals. Medical researchers refer to this problem as ascertainment bias. [Read more…] about Sampling Bias: Definition & Examples

Filed Under: Basics Tagged With: bias sources, conceptual, experimental design, sampling methods

Confounding Variable: Definition & Examples

By Jim Frost 86 Comments

Confounding Variable Definition

In studies examining possible causal links, a confounding variable is an unaccounted factor that impacts both the potential cause and effect and can distort the results. Recognizing and addressing these variables in your experimental design is crucial for producing valid findings. Statisticians also refer to confounding variables that cause bias as confounders, omitted variables, and lurking variables. [Read more…] about Confounding Variable: Definition & Examples

Filed Under: Regression Tagged With: assumptions, bias sources, conceptual

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