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Statistics By Jim

Making statistics intuitive

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What is Power in Statistics?

By Jim Frost 1 Comment

Power in statistics is the probability that a hypothesis test can detect an effect in a sample when it exists in the population. It is the sensitivity of a hypothesis test. When an effect exists in the population, how likely is the test to detect it in your sample? [Read more…] about What is Power in Statistics?

Filed Under: Hypothesis Testing Tagged With: conceptual

Conditional Distribution: Definition & Finding

By Jim Frost Leave a Comment

What is a Conditional Distribution?

A conditional distribution is a distribution of values for one variable that exists when you specify the values of other variables. This type of distribution allows you to assess the dispersal of your variable of interest under specific conditions, hence the name. [Read more…] about Conditional Distribution: Definition & Finding

Filed Under: Basics Tagged With: conceptual, distributions

Marginal Distribution: Definition & Finding

By Jim Frost Leave a Comment

What is a Marginal Distribution?

A marginal distribution is a distribution of values for one variable that ignores a more extensive set of related variables in a dataset.

That definition sounds a bit convoluted, but the concept is simple. The idea is that when you have a larger set of related variables that you collected for a study, you might want to focus on one of them to answer a specific question. [Read more…] about Marginal Distribution: Definition & Finding

Filed Under: Basics Tagged With: conceptual, distributions

Content Validity: Definition, Examples & Measuring

By Jim Frost Leave a Comment

What is Content Validity?

Content validity is the degree to which a test or assessment instrument evaluates all aspects of the topic, construct, or behavior that it is designed to measure. Do the items fully cover the subject? High content validity indicates that the test fully covers the topic for the target audience. Lower results suggest that the test does not contain relevant facets of the subject matter. [Read more…] about Content Validity: Definition, Examples & Measuring

Filed Under: Basics Tagged With: conceptual

Parameter vs Statistic: Examples & Differences

By Jim Frost 5 Comments

Parameters are numbers that describe the properties of entire populations. Statistics are numbers that describe the properties of samples. [Read more…] about Parameter vs Statistic: Examples & Differences

Filed Under: Basics Tagged With: conceptual

Spurious Correlation: Definition, Examples & Detecting

By Jim Frost 5 Comments

What is a Spurious Correlation?

A spurious correlation occurs when two variables are correlated but don’t have a causal relationship. In other words, it appears like values of one variable cause changes in the other variable, but that’s not actually happening. [Read more…] about Spurious Correlation: Definition, Examples & Detecting

Filed Under: Basics Tagged With: conceptual

Contingency Table: Definition, Examples & Interpreting

By Jim Frost 9 Comments

What is a Contingency Table?

A contingency table displays frequencies for combinations of two categorical variables. Analysts also refer to contingency tables as cross tabulation and two-way tables. [Read more…] about Contingency Table: Definition, Examples & Interpreting

Filed Under: Basics Tagged With: conceptual, distributions

Permutation vs Combination: Differences & Examples

By Jim Frost 11 Comments

In mathematics and statistics, permutations vs combinations are two different ways to take a set of items or options and create subsets. For example, if you have ten people, how many subsets of three can you make? While permutation and combination seem like synonyms in everyday language, they have distinct definitions mathematically.

  • Permutations: The order of outcomes matters.
  • Combinations: The order does not matter.

Let’s understand this difference between permutation vs combination in greater detail. And then you’ll learn how to calculate the total number of each. [Read more…] about Permutation vs Combination: Differences & Examples

Filed Under: Probability Tagged With: conceptual

Cumulative Frequency: Finding & Interpreting

By Jim Frost 1 Comment

What is Cumulative Frequency?

Cumulative frequency is the running total of frequencies in a table. Use cumulative frequencies to answer questions about how often a characteristic occurs above or below a particular value. It is also known as a cumulative frequency distribution.

For example, how many students are in the 4th grade or lower at a school? [Read more…] about Cumulative Frequency: Finding & Interpreting

Filed Under: Basics Tagged With: conceptual, distributions

Chi-Square Goodness of Fit Test: Uses & Examples

By Jim Frost 6 Comments

What is the Chi Square Goodness of Fit Test?

The chi-square goodness of fit test evaluates whether proportions of categorical or discrete outcomes in a sample follow a population distribution with hypothesized proportions. In other words, when you draw a random sample, do the observed proportions follow the values that theory suggests. [Read more…] about Chi-Square Goodness of Fit Test: Uses & Examples

Filed Under: Hypothesis Testing Tagged With: analysis example, conceptual, distributions, interpreting results

Sampling Error: Definition, Sources & Minimizing

By Jim Frost 8 Comments

What is Sampling Error?

Sampling error is the difference between a sample statistic and the population parameter it estimates. It is a crucial consideration in inferential statistics where you use a sample to estimate the properties of an entire population. [Read more…] about Sampling Error: Definition, Sources & Minimizing

Filed Under: Hypothesis Testing Tagged With: conceptual

Cohort Study: Definition, Benefits & Examples

By Jim Frost Leave a Comment

What is a Cohort Study?

A cohort study is a longitudinal experimental design that follows a group of participants who share a defining characteristic. For example, a cohort study can select subjects who have exposure to a risk factor, are in the same profession, population or generation, or experience a particular event, such as a medical procedure. This design determines whether exposure to a risk factor affects an outcome. Cohort studies are a type of longitudinal study because they track the same set of subjects over time. They hold a mid-to-high position in the level of evidence ranking, providing valuable observational insights over time. [Read more…] about Cohort Study: Definition, Benefits & Examples

Filed Under: Basics Tagged With: conceptual, experimental design

Inter-Rater Reliability: Definition, Examples & Assessing

By Jim Frost Leave a Comment

What is Inter-Rater Reliability?

Inter-rater reliability measures the agreement between subjective ratings by multiple raters, inspectors, judges, or appraisers. It answers the question, is the rating system consistent? High inter-rater reliability indicates that multiple raters’ ratings for the same item are consistent. Conversely, low reliability means they are inconsistent. [Read more…] about Inter-Rater Reliability: Definition, Examples & Assessing

Filed Under: Hypothesis Testing Tagged With: analysis example, conceptual, interpreting results

How to Find the Mode

By Jim Frost Leave a Comment

There are several ways to find the mode depending upon the data type and sample size. In statistics, the mode is the most frequently occurring value in a data set. It is a measure of central tendency. To learn more about the mode, read my post, Measures of Central Tendency. [Read more…] about How to Find the Mode

Filed Under: Basics Tagged With: conceptual

Bimodal Distribution: Definition, Examples & Analysis

By Jim Frost 4 Comments

A bimodal distribution has two peaks. In the context of a continuous probability distribution, modes are peaks in the distribution. The graph below shows a bimodal distribution. [Read more…] about Bimodal Distribution: Definition, Examples & Analysis

Filed Under: Basics Tagged With: conceptual, distributions, graphs

Margin of Error: Formula and Interpreting

By Jim Frost 4 Comments

What is the Margin of Error?

The margin of error (MOE) for a survey tells you how near you can expect the survey results to be to the correct population value. For example, a survey indicates that 72% of respondents favor Brand A over Brand B with a 3% margin of error. In this case, the actual population percentage that prefers Brand A likely falls within the range of 72% ± 3%, or 69 – 75%. [Read more…] about Margin of Error: Formula and Interpreting

Filed Under: Hypothesis Testing Tagged With: conceptual, interpreting results

Quartile: Definition, Finding, and Using

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What are Quartiles?

Quartiles are three values that split your dataset into quarters. They are a type of quantile that splits the data into four equal-sized groups and tells you where a score stands relative to other scores. [Read more…] about Quartile: Definition, Finding, and Using

Filed Under: Basics Tagged With: conceptual, distributions

Construct Validity: Definition and Assessment

By Jim Frost Leave a Comment

What is Construct Validity?

Construct validity relates to the soundness of inferences that you draw from test scores and other measurements. Specifically, it addresses whether a test measures the intended construct. For example, does a test that evaluates self-esteem truly measure that construct or something else? [Read more…] about Construct Validity: Definition and Assessment

Filed Under: Basics Tagged With: conceptual

Qualitative Research: Goals, Methods & Benefits

By Jim Frost 5 Comments

Qualitative research aims to understand ideas, experiences, and opinions using non-numeric data, such as text, audio, and visual recordings. The focus is on language, behaviors, and social structures. Qualitative researchers want to present personal experiences and produce narrative stories that use natural language to provide meaningful answers to their research questions. [Read more…] about Qualitative Research: Goals, Methods & Benefits

Filed Under: Basics Tagged With: conceptual

What is a Variable?

By Jim Frost Leave a Comment

The definition of a variable changes depending on the context. Typically, a letter represents them, and it stands in for a numerical value. In algebra, a variable represents an unknown value that you need to find. For mathematical functions and equations, you input their values to calculate the output. In an equation, a coefficient is a fixed value by which you multiply the variable.

In statistics, a variable is a characteristic of interest that you measure, record, and analyze. Statisticians understand them by defining the type of information they record and their role in an experiment or study. [Read more…] about What is a Variable?

Filed Under: Basics Tagged With: conceptual

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