Name: reading data patterns with histograms
Uploaded: 2023-04-30T11:13:23.000Z
Duration: 1 min 5 s
Channel: JoVE

K12 Standards

Texas Essential Knowledge and Skills

High School

Earth Systems Science

112.49.c.1.

112.49.c.1.F.

Histogram

빈도 분포 테이블은 서로 다른 가격대의 책 수와 같은 여러 범주로 정량적 데이터를 구성하는 데 도움이 된다는 점을 기억하십시오.
이러한 빈도 분포 테이블은 히스토그램을 사용하여 시각적으로 표현할 수 있으며, 히스토그램은 간격 없이 그려진 동일한 너비의 막대로 구성된 그래프입니다. 
세로 축은 각 클래스의 주파수를 나타내고 가로 축은 클래스 경계를 나타냅니다. 
그렇다면, 계급 경계란 무엇일까요? 데이터 테이블의 첫 번째 간격은 5달러에서 10달러 사이의 가격을 보여주고 두 번째 간격은 11에서 16 사이의 가격 범위를 제공합니다. 
10에서 11 사이의 가격대는 표에서 누락되었습니다. 이 간격은 클래스 경계라고 하는 중간점을 계산하여 채워집니다.
이러한 클래스 경계는 가로 축에 표시되고 해당 주파수는 세로 축에 표시됩니다. Bin이라고 하는 세로 막대는 클래스 경계와 빈도 값을 연결합니다.

히스토그램

히스토그램은 자료 집합의 자료 분포를 x-y 형식으로 그래프로 표현한 것입니다. 가로 x축에는 자료가 나타내는 내용(예: 집에서 학교까지의 거리)이 표시됩니다. 세로 y축에는 빈도 또는 상대 빈도(또는 백분율 빈도 또는 확률)로 지정됩니다. 히스토그램 그래프는 연속한(인접한) 상자로 구성됩니다. 막대의 높이는 빈도 수에 해당합니다. 그래프는 각 레이블과 동일한 모양을 갖습니다. 줄기 그림과 같은 히스토그램은 자료의 모양, 중심 및 산포를 제공할 수 있습니다. 일반적으로는 히스토그램을 사용하여 크고 연속적인 정량적 자료 집합를 표시합니다. 히스토그램의 가장 큰 장점은 대규모 자료 집합을 쉽게 표시할 수 있다는 것입니다. 경험상 자료 집합가 100개 이상의 값으로 구성된 경우 히스토그램을 사용하는 것이 좋습니다. 히스토그램을 구성하려면 클래스라고도 하는 막대 또는 간격으로 자료를 나타내는 수를 결정할 수 있습니다. 많은 히스토그램은 명확성을 위해 5~15개의 막대 또는 클래스로 구성되지만 필요한 막대 수를 선택할 수 있습니다.

히스토그램은 데이터 세트에서 x-y 형식의 데이터 분포를 그래픽으로 표현한 것입니다. 수평 x 축은 데이터가 무엇으로 레이블이 지정되어 있습니다 ...

Education

교육

JoVE Core

Statistics

통계학

Unit 1

제1단원

Summarizing and Visualizing Data

데이터 요약 및 시각화

KEY TERMS AND CONCEPTS

주요 용어 및 개념

reading data patterns with histograms

A histogram shows how data is distributed in a data set. It uses an x-y graph to display the pattern of the data. The x-axis is labeled with what the data represents, such as distance from home to school. The y-axis shows frequency, relative frequency, percent frequency, or probability.

A histogram is made of adjoining bars. The height of each bar matches the frequency value for that class. Even with different labels, the graph keeps the same overall shape. Like a stemplot, a histogram can show the shape, center, and spread of the data.

Histograms are most useful for large, continuous, quantitative data sets. They can display large data sets clearly and quickly. A common rule of thumb is to use a histogram when a data set has 100 values or more.

To build a histogram, you choose how many bars or intervals, also called classes, will represent the data. Many histograms use five to 15 bars for clarity. The right number depends on the data and the level of detail needed.

Reading Data Patterns with Histograms

review and preview

Descriptive Statistics and Graphs

Descriptive statistics help summarize data with numbers and graphs. Data are individual pieces of information collected from a population or a sample. They can be qualitative, which means categorical, or quantitative, which includes continuous and discrete data. In many studies, researchers do not measure every member of a population. Instead, they use a sample to represent the population. A random sample is a representative group chosen so that each individual has an equal chance of being...

what is a frequency distribution

Reading Frequency Tables and Histograms

Frequency distributions organize quantitative data by showing how often each value appears. A frequency is the number of times a data value occurs. When the frequency values are added together, the total equals the number of students in the sample. These distributions are useful for grouping numerical data into clear patterns. They can be shown in a table, histogram, line graph, dot plot, or pie chart. A histogram displays tabulated frequencies as adjacent rectangles over discrete intervals,...

construction of frequency distribution

Building a Frequency Table from Data

A frequency distribution table organizes data by showing how often each value appears. It starts with two columns: one for the data labels and one for frequency. A third column for tally marks can be added if needed. The next step is to look at the data set and decide whether an ungrouped frequency distribution table or a grouped frequency distribution table is more suitable. If the data includes a large set of different values, a grouped frequency distribution table is the better choice. This...

relative frequency distribution

Relative Frequency in Data Tables

Relative frequency distribution shows how often each value or class appears in a data set as a fraction of the whole. To find a relative frequency, divide each class frequency by the total number of data points in the sample. The result can be written as a fraction, decimal, or percent. This type of distribution is very similar to a regular frequency distribution. The same data are grouped in classes, and the same rules are used to build those classes. The main difference is in the way the...

percentage frequency distribution

Survey Data as Percentage Frequencies

Survey data can be shown as percentage frequencies to display how observations are spread across each data point or group. This format shows the share of the total for each response or category. It is a common way to present relative frequency in survey results and other data. Percentage frequency distributions are often displayed as bar graphs, pie charts, or tables. These displays make it easier to compare groups and see how much each category contributes to the whole. They are useful...

cumulative frequency distribution

Building a Cumulative Frequency Table

A cumulative frequency distribution shows how data build up across class intervals. Instead of counting only the values in one class, it counts the values in that class and in every class to its left. It is a useful way to track how data accumulate as the table progresses. A cumulative frequency is found by adding the frequency of each class lower than the class interval or category being studied. In other words, each new total includes the current class and the frequencies from the lower...

ogive graph

Cumulative Frequency Graph for Medians

An ogive graph is a cumulative frequency graph used in statistics. It is also called a cumulative frequency polygon. Instead of showing each class on its own, it adds the cumulative percentages from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries on the horizontal x-axis. It looks similar to a histogram, but it uses single points instead of rectangles. Each point appears where the top right corner of a histogram bar would be. This graph is...

histogram

A histogram shows how data is distributed in a data set. It uses an x-y graph to display the pattern of the data. The x-axis is labeled with what the data represents, such as distance from home to school. The y-axis shows frequency, relative frequency, percent frequency, or probability. A histogram is made of adjoining bars. The height of each bar matches the frequency value for that class. Even with different labels, the graph keeps the same overall shape. Like a stemplot, a histogram can...

relative frequency histogram

Reading Relative Frequency in Histograms

A relative frequency histogram shows how data are spread across classes using percentages instead of counts. The relative frequency tells the proportion of data points in each value or class. The frequency tells the number of data points in each value or class. This graph has the same overall shape as a histogram. It uses a horizontal scale on the x-axis, and it marks the y-axis with relative frequencies, which are percentages of the whole. Each bar shows how many data values fall into a...

scatter plot

Reading Relationships in a Scatter Plot

A scatter plot shows the relationship between two variables, x and y. It is one of the easiest ways to display how the variables are connected. The graph can show the direction of the relationship. It can also show whether the points suggest a clear pattern or little pattern at all. A clear direction appears when high values of one variable go with high values of the other variable. It can also appear when low values of one variable go with low values of the other variable. Another pattern...

time-series graph

Reading Trends with Time-Series Graphs

A time-series graph shows repeated measurements taken at successive intervals of time. It is also called a time series chart. This type of line graph helps organize data that changes over time. To build a time-series graph, use both parts of a paired data set. Plot the time increments on the horizontal axis. Plot the measured values on the vertical axis. Each point then shows one time and one quantity, and the points are usually connected with straight lines in the order they occur. <br...

bar graph

Comparing Categories with Bar Charts

A bar graph, also called a bar chart, compares categories with separate bars. The bars may be horizontal or vertical. Each bar stands apart so the viewer can compare groups clearly.

multiple bar graph

Comparing Data with Multiple Bar Graphs

A multiple bar graph compares two or more sets of data with grouped bars. It works like a bar graph, but it uses several bars to show related values side by side. Each bar or column stands for one data value. This graph is useful when the data share the same unit of measurement. You can include many parameters, as long as they use that same unit. The categories are placed on the horizontal x-axis, and the frequency is shown on the vertical y-axis. Multiple bar graphs are used mainly to relate...

pareto chart

Pareto Chart for Ranking Data

A Pareto chart is a bar graph used to rank data by size or frequency. It can also combine bars with a line graph. In the chart, the bar lengths show the individual values or how often each category appears, and the line shows the cumulative total. The bars are arranged from longest on the left to shortest on the right. This order makes the data easier to read and interpret. A Pareto chart is also called a Pareto diagram or Pareto analysis. The chart is named after the Italian economist...

pie chart

Pie Chart Data and Percentages

A pie chart shows categorical data in a circular graph. It is divided into slices, and each slice shows a numerical proportion. This makes it easy to compare the relative size of parts in one chart. In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. That means larger values take up larger slices. Smaller values take up smaller slices. Pie charts are useful for real-world data such as marks...

key terms and concepts

Learn how histograms display data distribution, show frequency on the y-axis, and reveal shape, center, and spread in large quantitative data sets.

Reading Data Patterns with Histograms | JoVE K12

statistics

JoVE Core Statistics introduces the concepts and application of the collection, analysis, presentation, and interpretation of data to students. These animated lessons provide an understanding of statistics beneficial to students from a wide range of disciplines. Additionally, the scientist-in-action videos demonstrate the application of related concepts in classical and original research experiments performed in today's laboratories worldwide

ohios-learning-standards-and-model-curriculum

Ohio’s Learning Standards and Model Curriculum

9-12

Biology

Diversity And Interdependence Of Life

Ecosystems

Virginia  Standards of Learning

HIgh School

BIO.1

BIO.1.c

Chemistry

CH.1

CH.1.c

Earth Science

ES.1

ES.1.c

ES.1.e

Life Science

LS.1

LS.1.c

LS.1.e

Physical Science

PS.1

PS.1.c

Physics

PH.1

PH.1.c

PH.1.e

Specialised Topic in Science

112.51.c.1.

112.51.c.1.F.

new-jersey-student-learning-standards-for-science

New Jersey Student Learning Standards for Science

ecosystems-interactions-energy-and-dynamics

Ecosystems: Interactions, Energy, and Dynamics

HS-LS2-1

CHEM.1

CHEM.1.F

Alabama Course of Study Science

Ecosystems: Interactions Energy and Dynamics

9-12.B.2.8

Next Generation Science Standards

BIO.1.F

PHYS.1

PHYS.1.F

Chemistry and Physics

IPC.1

IPC.1.F

Using GIS to Investigate Urban Forestry

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Use appropriate tools such as a drawing compass, magnetic compass, bar magnets, topographical and geological maps, satellite imagery and other remote sensing data, Geographic Information Systems (GIS), Global Positioning System (GPS), hand lenses, and fossil and rock sample kits;

112.49.c.1.D.

Ogive Graph

An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, ...

The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data ...

Relative Frequency Histogram

The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. ...

Scatter Plot

The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a ...

Time-Series Graph

A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct ...

Bar Graph

A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show ...

Multiple Bar Graph

As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can ...

Pareto Chart

A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the ...

Pie Chart

A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each ...

overview-of-microsoft-excel-as-a-data-analysis-tool

Overview of Microsoft Excel as a Data Analysis Tool

Microsoft Excel is a statistical tool widely used for data analysis and interpretation.
Excel simplifies data analysis by offering a spreadsheet format ...

performing-a-simple-data-analysis-using-ms-excel-function

Performing a Simple Data Analysis using MS-Excel Function

Microsoft Excel facilitates simple and complex statistical data analysis with various functions.
A simple function like AVERAGE calculates the arithmetic ...

statistical-package-for-the-social-sciences-spss

Statistical Package for the Social Sciences (SPSS)

The Statistical Package for the Social Sciences, or SPSS, is a data analysis software initially designed for social sciences.
SPSS&#39;s key features ...

Introduction to R

R is an open-source software environment for statistical computing and graphics widely used in biostatistics, econometrics, and social sciences.
The R ...

Statistical Analysis System (SAS)

The Statistical Analysis System, or SAS, was developed by the SAS Institute in the 1970s for data management, analysis, and visualization.
It is utilized ...

Introduction to MATLAB

MATLAB, short for Matrix Laboratory, is a programming language and computing platform created by MathWorks.
It has various industrial applications, ...

Overview of Minitab

Minitab, developed at Pennsylvania State University in 1972, is renowned for its statistical analysis prowess.
It simplifies data visualization and ...

Econometric Views (EViews)

Econometric Views or EViews is a robust statistical tool for econometric analysis. It is equipped for time series analysis, forecasting, and model ...

Statgraphics

Statgraphics, initially developed at Princeton University in 1980, is a statistical software suite with extensive data analysis capabilities.
The suite ...

Organize quantitative and qualitative data using scatter plots, line graphs, bar graphs, charts, data tables, digital tools, diagrams, scientific drawings, and student-prepared models;

Modeling and Similitude

A scaled model of a dam is tested in a controlled environment to observe how it will manage water flow, turbulence, and pressure.
This setup predicts the ...

Typical Model Studies

Typical model studies analyze scaled-down systems to predict fluid behavior, focusing on interactions with free surfaces and flow around immersed bodies.
...

Develop and use models to represent phenomena, systems, processes, or solutions to engineering problems; and

112.49.c.1.G.

Scientific and engineering practices. The student, for at least 40% of instructional time, asks questions, identifies problems, and plans and safely conducts classroom, laboratory, and field investigations to explain phenomena or design solutions using appropriate tools and models. The student is expected to:

Reading Data Patterns with Histograms

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