Statistical charts and diagrams

Functional boxplot

In statistical graphics, the functional boxplot is an informative exploratory tool that has been proposed for visualizing functional data. Analogous to the classical boxplot, the descriptive statistics of a functional boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope. To construct a functional boxplot, data ordering is the first step. In functional data analysis, each observation is a real function, therefore, different from the classical boxplot where data are simply ordered from the smallest sample value to the largest, in a functional boxplot, functional data, e.g. curves or images, are ordered by a notion of band depth or a modified band depth. It allows for ordering functional data from the center outwards and, thus, introduces a measure to define functional quantiles and the centrality or outlyingness of an observation. Having the ranks of functional data, the functional boxplot is a natural extension of the classical boxplot. (Wikipedia).

Functional boxplot
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Boxplots in SPSS | An Easy Guide | Part 1

Boxplots are extremely helpful in describing data. In these two videos I demonstrate how to generate Boxplots in SPSS and interpret them. I will also show the effect of conventional and extreme outliers on the shape of Boxplots. For more information about normality, please watch this ser

From playlist Boxplots

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What is Functional Programming?

We will discuss the state of functional programming in brief across several languages. Also a discussion on the broader goals of functional programming and this meetup. EVENT: OKC FP 2020 SPEAKER: Scott Murphy PUBLICATION PERMISSIONS: The conference organizer provided Coding Tech wit

From playlist Functional Programming

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Boxplots in SPSS | An Easy Guide | Part 2

Boxplots are extremely helpful in describing data. In these two videos I demonstrate how to generate Boxplots in SPSS and interpret them. I will also show the effect of conventional and extreme outliers on the shape of Boxplots. For more information about normality, please watch this ser

From playlist Boxplots

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The Essence of Functional Programming

This talk dives into the origins of functional programming, going all the way back to where the term was first introduced, to see how it evolved over time into our modern understanding of what FP essentially involves. PUBLICATION PERMISSIONS: Original video was published with the Creative

From playlist Functional Programming

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Creating Box Plots with SPSS

This demonstration shows you how to create boxplots with SPSS. This demonstration corresponds to Introduction to Statistics, Think & Do, by Scott Stevens (http://www.StevensStats.com).

From playlist SPSS Demonstrations

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We go over the box plot. I show some hidden gems not in the documentation and explain what the various parts of the box plot are. Associated Github Commit: https://github.com/knathanieltucker/seaborn-weird-parts/commit/b0ffec52f518455141f8af9da326fa02bea5e418 Associated Seaborn Links: ht

From playlist Seaborn: Understanding the Weird Parts

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This video explains what a mathematical function is and how it defines a relationship between two sets, the domain and the range. It also introduces three important categories of function: injective, surjective and bijective.

From playlist Foundational Math

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Functional Programming for Beginners: Pure Functions Explained

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From playlist Functional Programming

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From playlist Discovering Statistics with JASP

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5.1: Introduction to Box2D - The Nature of Code

This video is an introduction to a tutorial series on the physics engine Box2D. The programming language is Java (with the jbox2d port). The Box2D for Processing library is demonstrated. In the video it's called the old name: "PBox2D" Read along: http://natureofcode.com/book/chapter-5

From playlist Box2D Physics

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From playlist Introduction to dplyr

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How to Make Boxplots in R

Boxplots provide a visual representation of the distribution of numeric variables that include key values such as the median, 25th and 75th percentiles. Side-by-side boxplots let you break plots out by a second categorical variable to compare differences across groups. #Rprogramming #Data

From playlist Code Clips: R Plots

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From playlist Statistics

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The easiest way to draw parallel boxplots on computer

There is a website that draws boxplots for you! After you're done, you can copy and paste the boxplot to Word, Excel or where ever you want. A lot of your statistics math assignments at school may need you to draw a boxplot with your computer, to make it look professional. However, it's qu

From playlist Maths B / Methods Course, Grade 11/12, High School, Queensland, Australia.

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Boxplots & Outliers in SPSS – Identify and Deal with Outliers (4-8)

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From playlist WK4 Statistical Graphing - Online Statistics for the Flipped Classroom

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Cumulative Frequency: Compare Boxplots (Grade 6) - OnMaths GCSE Maths Revision

Topic: Cumulative Frequency: Compare Boxplots Do this paper online for free: https://www.onmaths.com/cumulative-frequency/ Grade: 6 This question appears on calculator and non-calculator higher GCSE papers. Practise and revise with OnMaths. Go to onmaths.com for more resources, like predi

From playlist Cumulative Frequency

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The Benefits of Functional Architectures | Systems Engineering, Part 3

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From playlist Systems Engineering

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The 5-Number Summary and BOXPLOTS (6-10)

The Five-Number Summary gives multiple measures of variability that describe the distribution. A boxplot is the graphic equivalent to a five-number summary. Both show the center and spread of the data, and boxplots can be used to identify skewness and outliers. The five numbers are: Minim

From playlist Depicting Distributions from Boxplots to z-Scores (WK 6 QBA 237)

Related pages

Statsmodels | MATLAB | Bagplot | Interquartile range | Median | Statistical graphics | Box plot | R (programming language) | Functional data analysis | Descriptive statistics