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Statistics By Jim

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distributions

Difference Between Standard Deviation and Standard Error

By Jim Frost 8 Comments

The difference between a standard deviation and a standard error can seem murky. Let’s clear that up in this post!

Standard deviation (SD) and standard error (SE) both measure variability. High values of either statistic indicate more dispersion. However, that’s where the similarities end. The standard deviation is not the same as the standard error. [Read more…] about Difference Between Standard Deviation and Standard Error

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

Beta Distribution: Uses, Parameters & Examples

By Jim Frost 6 Comments

The beta distribution is a continuous probability distribution that models random variables with values falling inside a finite interval. Use it to model subject areas with both an upper and lower bound for possible values. Analysts commonly use it to model the time to complete a task, the distribution of order statistics, and the prior distribution for binomial proportions in Bayesian analysis. [Read more…] about Beta Distribution: Uses, Parameters & Examples

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

Geometric Distribution: Uses, Calculator & Formula

By Jim Frost Leave a Comment

What is a Geometric Distribution?

The geometric distribution is a discrete probability distribution that calculates the probability of the first success occurring during a specific trial. In other words, during a series of attempts, what is the probability of success first occurring during each attempt? Use this distribution when you need to understand how many attempts are necessary to produce the first successful outcome. [Read more…] about Geometric Distribution: Uses, Calculator & Formula

Filed Under: Probability Tagged With: distributions, graphs

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

Contingency Table: Definition, Examples & Interpreting

By Jim Frost 2 Comments

What is a Contingency Table?

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

Filed Under: Basics Tagged With: conceptual, distributions

Cumulative Frequency: Finding & Interpreting

By Jim Frost Leave a 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 4 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

Bimodal Distribution: Definition, Examples & Analysis

By Jim Frost 1 Comment

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

Quartile: Definition, Finding, and Using

By Jim Frost Leave a Comment

What are Quartiles?

Quartiles are three values that split your dataset into quarters. [Read more…] about Quartile: Definition, Finding, and Using

Filed Under: Basics Tagged With: conceptual, distributions

Kurtosis: Definition, Leptokurtic & Platykurtic

By Jim Frost 3 Comments

What is Kurtosis?

Kurtosis is a statistic that measures the extent to which a distribution contains outliers. It assesses the propensity of a distribution to have extreme values within its tails. There are three kinds of kurtosis: leptokurtic, platykurtic, and mesokurtic. Statisticians define these types relative to the normal distribution. Higher kurtosis values indicate that the distribution has more outliers falling relatively far from the mean. Distributions with smaller values have a lower tendency for producing extreme values. When you’re assessing a sample, outliers have the greatest impact on this statistic. [Read more…] about Kurtosis: Definition, Leptokurtic & Platykurtic

Filed Under: Basics Tagged With: conceptual, distributions

Binomial Distribution: Uses & Calculator

By Jim Frost 2 Comments

What is the Binomial Distribution?

The binomial distribution is a discrete probability distribution that calculates the likelihood an event will occur a specific number of times in a set number of opportunities. Use this distribution when you have a binomial random variable. These variables count how often an event occurs within a fixed number of trials. They have only two possible outcomes that are mutually exclusive. [Read more…] about Binomial Distribution: Uses & Calculator

Filed Under: Probability Tagged With: distributions, graphs

F-table

By Jim Frost Leave a Comment

These F-tables provide the critical values for right-tail F-tests. Your F-test results are statistically significant when its test statistic is greater than this value. [Read more…] about F-table

Filed Under: Hypothesis Testing Tagged With: conceptual, distributions, graphs

Sampling Distribution: Definition, Formula & Examples

By Jim Frost 5 Comments

What is a Sampling Distribution?

A sampling distribution of a statistic is a type of probability distribution created by drawing many random samples of a given size from the same population. These distributions help you understand how a sample statistic varies from sample to sample. [Read more…] about Sampling Distribution: Definition, Formula & Examples

Filed Under: Hypothesis Testing Tagged With: conceptual, distributions, graphs

Critical Value: Definition, Finding & Calculator

By Jim Frost Leave a Comment

What is a Critical Value?

A critical value defines regions in the sampling distribution of a test statistic. These values play a role in both hypothesis tests and confidence intervals. In hypothesis tests, critical values determine whether the results are statistically significant. For confidence intervals, they help calculate the upper and lower limits. [Read more…] about Critical Value: Definition, Finding & Calculator

Filed Under: Hypothesis Testing Tagged With: conceptual, distributions, graphs

Chi-Square Table

By Jim Frost 2 Comments

This chi-square table provides the critical values for chi-square (χ2) hypothesis tests. The column and row intersections are the right-tail critical values for a given probability and degrees of freedom. [Read more…] about Chi-Square Table

Filed Under: Hypothesis Testing Tagged With: distributions, graphs

Z-table

By Jim Frost 7 Comments

Z-Score Table

A z-table, also known as the standard normal table, provides the area under the curve to the left of a z-score. This area represents the probability that z-values will fall within a region of the standard normal distribution. Use a z-table to find probabilities corresponding to ranges of z-scores and to find p-values for z-tests. [Read more…] about Z-table

Filed Under: Hypothesis Testing Tagged With: distributions, graphs

T-Distribution Table of Critical Values

By Jim Frost 5 Comments

This t-distribution table provides the critical t-values for both one-tailed and two-tailed t-tests, and confidence intervals. Learn how to use this t-table with the information, examples, and illustrations below the table. [Read more…] about T-Distribution Table of Critical Values

Filed Under: Hypothesis Testing Tagged With: distributions

5 Number Summary: Definition, Finding & Using

By Jim Frost 6 Comments

What is the 5 Number Summary?

The 5 number summary is an exploratory data analysis tool that provides insight into the distribution of values for one variable. Collectively, this set of statistics describes where data values occur, their central tendency, variability, and the general shape of their distribution. [Read more…] about 5 Number Summary: Definition, Finding & Using

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

Lognormal Distribution: Uses, Parameters & Examples

By Jim Frost 5 Comments

What is the Lognormal Distribution?

The lognormal distribution is a continuous probability distribution that models right-skewed data. The unimodal shape of the lognormal distribution is comparable to the Weibull and loglogistic distributions. [Read more…] about Lognormal Distribution: Uses, Parameters & Examples

Filed Under: Probability Tagged With: distributions, graphs

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    Top Posts

    • How to Interpret P-values and Coefficients in Regression Analysis
    • F-table
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    • Z-table
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    • How to Find the P value: Process and Calculations
    • Weighted Average: Formula & Calculation Examples
    • T-Distribution Table of Critical Values
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