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Statistics By Jim

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Halo Effect: Definition & Examples

By Jim Frost 1 Comment

What is the Halo Effect?

The halo effect is a cognitive bias relating to our tendency to transfer a positive impression of one characteristic of a person or object to their other features. A classic example is that when you perceive someone as attractive, you are likely to assume they have other positive attributes, such as intelligence, kindness, and trustworthiness. [Read more…] about Halo Effect: Definition & Examples

Filed Under: Basics Tagged With: bias sources, conceptual

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

By Jim Frost Leave a Comment

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

What is a Ratio and Proportion?

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Ratios and proportions are related concepts in mathematics and statistics. A ratio compares two quantities and shows their relative sizes. For example, a veterinary office might have 1 dog to 2 cats as patients. This comparison tells us that they see twice as many cats as dogs. [Read more…] about What is a Ratio and Proportion?

Filed Under: Basics Tagged With: 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

Random Variable: Discrete & Continuous

By Jim Frost Leave a Comment

What is a Random Variable?

A random variable is a variable where chance determines its value. They can take on either discrete or continuous values, and understanding the properties of each type is essential in many statistical applications. Random variables are a key concept in statistics and probability theory. [Read more…] about Random Variable: Discrete & Continuous

Filed Under: Probability Tagged With: analysis example, conceptual, distributions, graphs

Least Squares Regression: Definition, Formulas & Example

By Jim Frost 1 Comment

A least squares regression line represents the relationship between variables in a scatterplot. The procedure fits the line to the data points in a way that minimizes the sum of the squared vertical distances between the line and the points. It is also known as a line of best fit or a trend line. [Read more…] about Least Squares Regression: Definition, Formulas & Example

Filed Under: Regression Tagged With: analysis example, graphs, interpreting results

Sampling Frame: Definition & Examples

By Jim Frost Leave a Comment

What is a Sampling Frame?

A sampling frame lists all members of the population you’re studying. Your target population is the general concept of the group you’re assessing, while a sampling frame specifically lists all population members and how to contact them. It might also include demographic information for each person because some methods, such as stratified sampling, require it. [Read more…] about Sampling Frame: Definition & Examples

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

Probability Mass Function: Definition, Uses & Example

By Jim Frost Leave a Comment

What is a Probability Mass Function?

A probability mass function (PMF) is a mathematical function that calculates the probability a discrete random variable will be a specific value. PMFs also describe the probability distribution for the full range of values for a discrete variable. A discrete random variable can take on a finite or countably infinite number of possible values, such as the number of heads in a series of coin flips or the number of customers who visit a store on a given day. [Read more…] about Probability Mass Function: Definition, Uses & Example

Filed Under: Probability Tagged With: distributions, graphs

Using Scientific Notation

By Jim Frost Leave a Comment

What is Scientific Notation?

Scientific notation is a compact way of writing numbers that are too large or too small to be conveniently written in decimal form. It is a shorthand letting us write numbers using powers of 10. Scientific fields such as astronomy, physics, chemistry, and statistics frequently use scientific notation.

Below is an example of shorthand notation:

  • 3.2 X 108
  • 3.2 X 10^8
  • 3.2E8

All three forms of scientific notation are equivalent. In the last format, the E stands for exponent.

In this blog post, you’ll learn how to interpret scientific notation, convert numbers to this format, and how to use it for multiplication and division. [Read more…] about Using Scientific Notation

Filed Under: Basics

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

ANCOVA: Uses, Assumptions & Example

By Jim Frost Leave a Comment

What is ANCOVA?

ANCOVA, or the analysis of covariance, is a powerful statistical method that analyzes the differences between three or more group means while controlling for the effects of at least one continuous covariate. [Read more…] about ANCOVA: Uses, Assumptions & Example

Filed Under: ANOVA Tagged With: analysis example, assumptions, choosing analysis, interpreting results

Fibonacci Sequence: Formula & Uses

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What is the Fibonacci Sequence?

The Fibonacci sequence is a series of numbers that appears in surprisingly many aspects of nature, from the branching of trees to the spiral shapes of shells. This series is named after the Italian mathematician Leonardo Fibonacci. [Read more…] about Fibonacci Sequence: Formula & Uses

Filed Under: Basics Tagged With: conceptual

Undercoverage Bias: Definition & Examples

By Jim Frost Leave a Comment

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

Matched Pairs Design: Uses & Examples

By Jim Frost Leave a Comment

What is a Matched Pairs Design?

A matched pairs design is an experimental design where researchers match pairs of participants by relevant characteristics. Then the researchers randomly assign one person from each pair to the treatment group and the other to the control group. This type of experiment is also known as a matching pairs design. [Read more…] about Matched Pairs Design: Uses & Examples

Filed Under: Basics Tagged With: experimental design

Nonresponse Bias: Definition & Reducing

By Jim Frost Leave a Comment

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

Cumulative Distribution Function (CDF): Uses, Graphs & vs PDF

By Jim Frost Leave a Comment

What is a Cumulative Distribution Function?

A cumulative distribution function (CDF) describes the probabilities of a random variable having values less than or equal to x. It is a cumulative function because it sums the total likelihood up to that point. Its output always ranges between 0 and 1. [Read more…] about Cumulative Distribution Function (CDF): Uses, Graphs & vs PDF

Filed Under: Probability Tagged With: analysis example, conceptual, distributions, graphs, interpreting results

Slope Intercept Form of Linear Equations: A Guide

By Jim Frost Leave a Comment

What is Slope Intercept Form?

The slope intercept form of linear equations is an algebraic representation of straight lines: y = mx + b. [Read more…] about Slope Intercept Form of Linear Equations: A Guide

Filed Under: Basics Tagged With: analysis example, graphs, interpreting results

Population vs Sample: Uses and Examples

By Jim Frost Leave a Comment

What is a Population vs Sample?

Population vs sample is a crucial distinction in statistics. Typically, researchers use samples to learn about populations. Let’s explore the differences between these concepts! [Read more…] about Population vs Sample: Uses and Examples

Filed Under: Basics Tagged With: conceptual, sampling methods

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