히스토그램

수학노트
둘러보기로 가기 검색하러 가기

노트

  • As a second step, histogram allow to compare the distribution of a few variables.[1]
  • Don’t compare more than ~3 groups in the same histogram.[1]
  • The quantitative variable displayed in the histogram is the cost of engagement rings.[2]
  • The histogram summarizes the distribution of a data set composed of 50 integers.[2]
  • On a technical level, the software is looking at how the log-chrominance histogram of each photo shifts with varying tints.[2]
  • Histograms are great for summarizing several statistics.[3]
  • oh my!), creating a histogram in Excel isn’t always that great.[3]
  • Let’s look at three ways you can do more with histograms in Minitab.[3]
  • In histograms, they are shown as bars.[3]
  • A histogram is a graphical method for displaying the shape of a distribution.[4]
  • In a histogram, the class frequencies are represented by bars.[4]
  • A histogram of these data is shown in Figure 1.[4]
  • The histogram makes it plain that most of the scores are in the middle of the distribution, with fewer scores in the extremes.[4]
  • This tool will create a histogram representing the frequency distribution of your data.[5]
  • Histograms are a great way to visualise data and track key performance indicators because they are so clear and simple to read.[6]
  • The histogram is a graph that is often used in mathematics and statistics.[6]
  • Histograms are used to measure how frequently values or value ranges appear in a set of data.[6]
  • Some histograms will show two peaks.[6]
  • A field to store pre-aggregated numerical data representing a histogram.[7]
  • A values array of double numbers, representing the buckets for the histogram.[7]
  • array of numbers, representing the buckets for the histogram.[7]
  • A histogram field can only store a single pair of values and count arrays per document.[7]
  • Histograms aggregate numerical data into equal interval groups, called bins, and display the frequency of values within each bin.[8]
  • Create a histogram To create a histogram, complete the following steps: or rate/ratio field .[8]
  • Create the histogram using the following steps: Drag the selected fields to a new card.[8]
  • Drop the selected fields on Histogram .[8]
  • Histograms are graphs that display the distribution of your continuous data.[9]
  • Use histograms when you have continuous measurements and want to understand the distribution of values and look for outliers.[9]
  • In the histogram below, you can see that the center is near 50.[9]
  • A difference in means shifts the distributions horizontally along the X-axis (unless the histogram is rotated).[9]
  • While bar charts can be shown either vertically or horizontally, a histogram will always be vertical.[10]
  • In a histogram, the horizontal x-axis is always labeled with the midpoints, class ranges or class boundaries.[10]
  • When we transform our customer survey data into a histogram it’s easy to see the frequency distribution of our data set.[10]
  • There are a few instances where a histogram is going to be your best option for displaying your data.[10]
  • A call to a function to create a histogram contains the name of the continuous variable that contains the values to be plotted.[11]
  • With the Histogram() function, that variable name is the first argument passed to the function.[11]
  • the bin labels look different, but the histograms are the same.[12]
  • Similarly, the histogram graph with labels can be created from a histogram graph by enable labels on the Label tab.[13]
  • The illustration, below, is a histogram showing the results of a final exam given to a hypothetical class of students.[14]
  • Some histograms are presented with the independent variable along the vertical axis and the dependent variable along the horizontal axis.[14]
  • A histogram represents the frequencies of values of a variable bucketed into ranges.[15]
  • Histogram is similar to bar chat but the difference is it groups the values into continuous ranges.[15]
  • R creates histogram using hist() function.[15]
  • Histograms can be built with ggplot2 thanks to the geom_histogram() function.[16]
  • The density parameter, which normalizes bin heights so that the integral of the histogram is 1.[17]
  • Selecting different bin counts and sizes can significantly affect the shape of a histogram.[17]
  • A Histogram visualises the distribution of data over a continuous interval or certain time period.[18]
  • A histogram is a chart that groups numeric data into bins, displaying the bins as segmented columns.[19]
  • To construct a histogram, the first step is to bin the range of values, and then count how many values fall into each interval.[19]
  • Example We used the same set of data to construct these three histograms of student scores.[20]
  • Are you surprised by how different the distribution looks in each histogram?[20]
  • To create the middle histogram, we changed the bin width to 10 but kept the first bin starting at 40.[20]
  • To create the last histogram, we kept the bin width at 10 but started the first bin at 45.[20]
  • gsn_histogram is the function for creating histograms.[21]
  • : The first plot shows how to draw a default histogram, where we let NCL pick the bin intervals to use.[21]
  • Note that with these different sized bins, the size of the histogram column remains the same by default.[21]
  • gsnHistogramCompare, will create two histograms, one set of bars drawn behind the other.[21]
  • The way this behaviour is implemented in Histogram is quite simple.[22]
  • Histogram captures this way of working and makes it an inherent part of its type system.[22]
  • This is a somewhat ad-hoc decision made by the tool authors and Histogram provides a more principled way of capturing it.[22]
  • Type providers are similar to the way Histogram works in that some code is evaluated in order to give more precise type information.[22]
  • The following histogram displays the pattern of the distribution.[23]
  • It is a graph derived from a typical histogram.[23]
  • It consists of connected line segments formed by joining the midpoints of the upper edges of the histogram’s bars.[23]
  • Frequency polygons are used as an alternative to overlapping histograms to compare simultaneously two or more frequency distributions.[23]
  • For histograms, we usually want to have from 5 to 20 intervals.[24]
  • Note that different choices of class intervals will result in different histograms.[24]
  • While histograms look like bar charts, they are different in that each bar is an interval of values of a metric.[25]
  • This histogram shows the frequency of visitors to a restaurant in one hour bins within the range of a time frame.[25]
  • Histograms are useful for analyzing numerical data sets.[25]
  • In statistics, histograms are used to graph the probability distribution of the data.[25]
  • Since our bar chart wasn't any good, we now try and run a histogram on our data.[26]
  • On top of that, histograms also give us a much more complete information about our data.[26]
  • Keep in mind that you can reasonably estimate a variable’s mean, standard deviation, skewness and kurtosis from a histogram.[26]
  • However, you can't estimate a variable’s histogram from the aforementioned statistics.[26]
  • Histograms are similar to bar charts; they are a way to display counts of data.[27]
  • Unlike a bar chart, the area of a bar in a histogram represents the frequency, not the height.[27]
  • The height of a bar in a histogram indicates frequency (counts) only if the bin widths are evenly spaced.[27]
  • A bihistogram is a graph made from two histograms (“bi” = two) in opposite directions.[27]
  • Histograms are graphs of a distribution of data designed to show centering, dispersion (spread), and shape (relative frequency) of the data.[28]
  • The first step in constructing a histogram is to decide how the process should be measured - what data should be collected.[28]
  • You can then construct a histogram by several methods.[28]
  • If there are too many, the distribution will spread out, and the histogram will look flat.[28]
  • The histogram tells us that the most common bin is < 10 meters, and that there's only one dinosaur over 40 meters.[29]
  • The code to generate this histogram is shown below.[29]
  • By default, Google Charts will choose the bucket size automatically, using a well-known algorithm for histograms.[29]
  • The values are still included in the histogram, but do not affect how they're bucketed.[29]
  • The histogram is a very familiar graphical display device for representing the distribution of a single batch of data.[30]
  • Example histograms are shown in Figure 3.6.[30]
  • Histograms quickly reveal such attributes of the data distribution as location, spread, and symmetry.[30]
  • The main issue to be confronted when constructing a histogram is choice of the binwidth.[30]
  • A histogram is used to summarize discrete or continuous data.[31]
  • The title: The title describes the information included in the histogram.[31]
  • Creating a histogram provides a visual representation of data distribution.[31]
  • That is, half the numbers return values that are greater than the median and distribution of the data can be determined by a histogram.[31]
  • A histogram is a chart that plots the distribution of a numeric variable’s values as a series of bars.[32]
  • The histogram above shows a frequency distribution for time to response for tickets sent into a fictional support system.[32]
  • Histograms are good for showing general distributional features of dataset variables.[32]
  • In order to use a histogram, we simply require a variable that takes continuous numeric values.[32]
  • To construct a histogram from a continuous variable you first need to split the data into intervals, called bins .[33]
  • A histogram is a plot that lets you discover, and show, the underlying frequency distribution (shape) of a set of continuous data.[33]
  • In a histogram, it is the area of the bar that indicates the frequency of occurrences for each bin.[33]
  • A histogram is a graphical representation that organizes a group of data points into user-specified ranges.[34]
  • Histograms are commonly used in statistics to demonstrate how many of a certain type of variable occurs within a specific range.[34]
  • Traders often overlook the MACD histogram when using this indicator to make trading decisions.[34]
  • The MACD histogram helps to alleviate this problem by generating earlier entry signals.[34]
  • And the visualization that we're gonna create, this is called a histogram.[35]
  • But as a histogram, we're able to put them into buckets.[35]
  • A histogram may also be normalized to display "relative" frequencies.[36]
  • The total area of a histogram used for probability density is always normalized to 1.[36]
  • A histogram can be thought of as a simplistic kernel density estimation, which uses a kernel to smooth frequencies over the bins.[36]
  • The density estimate could be plotted as an alternative to the histogram, and is usually drawn as a curve rather than a set of boxes.[36]
  • histogram ignores all NaN and NaT values.[37]
  • Similarly, histogram ignores Inf and -Inf values, unless the bin edges explicitly specify Inf or -Inf as a bin edge.[37]
  • histogram automatically bins the input data using double precision, which lacks integer precision for numbers greater than flintmax .[37]
  • A histogram is the most commonly used graph to show frequency distributions.[38]
  • Use a histogram worksheet to set up the histogram.[38]
  • The spaces between these numbers will be the bars of the histogram.[38]
  • Before drawing any conclusions from your histogram, be sure that the process was operating normally during the time period being studied.[38]

소스

  1. ↑ 이동: 1.0 1.1 Histogram
  2. ↑ 이동: 2.0 2.1 2.2 Definition of Histogram by Merriam-Webster
  3. ↑ 이동: 3.0 3.1 3.2 3.3 3 Ways Minitab Makes Plotting Histograms More Automatic and Easier than Excel
  4. ↑ 이동: 4.0 4.1 4.2 4.3 Histograms
  5. ↑ Easy Histogram Maker
  6. ↑ 이동: 6.0 6.1 6.2 6.3 Frequency Distribution: Histogram Diagrams
  7. ↑ 이동: 7.0 7.1 7.2 7.3 Elasticsearch Reference [7.10]
  8. ↑ 이동: 8.0 8.1 8.2 8.3 Create and use a histogram—ArcGIS Insights
  9. ↑ 이동: 9.0 9.1 9.2 9.3 Using Histograms to Understand Your Data
  10. ↑ 이동: 10.0 10.1 10.2 10.3 How to Make a Histogram Your Audience Will Understand
  11. ↑ 이동: 11.0 11.1 Histograms
  12. ↑ Histogram in Excel
  13. ↑ Histogram/Distribution Graph
  14. ↑ 이동: 14.0 14.1 Definition from WhatIs.com
  15. ↑ 이동: 15.0 15.1 15.2 Tutorialspoint
  16. ↑ the R Graph Gallery
  17. ↑ 이동: 17.0 17.1 Some features of the histogram (hist) function — Matplotlib 3.3.3 documentation
  18. ↑ Learn about this chart and tools to create it
  19. ↑ 이동: 19.0 19.1 Data Viz Project
  20. ↑ 이동: 20.0 20.1 20.2 20.3 Concepts in Statistics
  21. ↑ 이동: 21.0 21.1 21.2 21.3 NCL Graphics: Histograms
  22. ↑ 이동: 22.0 22.1 22.2 22.3 Histogram: You have to know the past to understand the present
  23. ↑ 이동: 23.0 23.1 23.2 23.3 Histograms, Why & How, Storytelling, Tips & Extensions
  24. ↑ 이동: 24.0 24.1 1.6.2 - Histograms
  25. ↑ 이동: 25.0 25.1 25.2 25.3 How to make a histogram in Tableau, Excel, and Google Sheets
  26. ↑ 이동: 26.0 26.1 26.2 26.3 Quick Introduction
  27. ↑ 이동: 27.0 27.1 27.2 27.3 Histogram: Make a Chart in Easy Steps
  28. ↑ 이동: 28.0 28.1 28.2 28.3 Histogram Tutorial
  29. ↑ 이동: 29.0 29.1 29.2 29.3 Google Developers
  30. ↑ 이동: 30.0 30.1 30.2 30.3 Histogram - an overview
  31. ↑ 이동: 31.0 31.1 31.2 31.3 Examples, Types, and How to Make Histograms
  32. ↑ 이동: 32.0 32.1 32.2 32.3 A Complete Guide to Histograms
  33. ↑ 이동: 33.0 33.1 33.2 Histograms - Understanding the properties of histograms, what they show, and when and how to use them
  34. ↑ 이동: 34.0 34.1 34.2 34.3 Histogram Definition
  35. ↑ 이동: 35.0 35.1 How to make a histogram
  36. ↑ 이동: 36.0 36.1 36.2 36.3 Histogram
  37. ↑ 이동: 37.0 37.1 37.2 Histogram plot
  38. ↑ 이동: 38.0 38.1 38.2 38.3 What are Histograms? Analysis & Frequency Distribution

메타데이터

위키데이터

Spacy 패턴 목록

  • [{'LEMMA': 'histogram'}]
원본 주소 "https://wiki.mathnt.net/index.php?title=히스토그램&oldid=51465"