Are you struggling with choosing the right type of graph to represent your data set? if yes then have a look at this presentation to choose the best statistics graph to represent your data set.
Displaying data using charts and graphsCharles Flynt
Bar charts, line graphs, pie charts, scatter plots, and histograms are commonly used types of charts. Each type of chart has distinct characteristics that make it suitable for visualizing certain types of data relationships. Bar charts are useful for comparing discrete categories, line graphs show trends over time, pie charts show proportions, scatter plots reveal correlations between two variables, and histograms display frequency distributions. Proper chart selection and design ensure data is presented clearly and accurately.
Interpret data for use in charts and graphsCharles Flynt
The document discusses various concepts for interpreting and dealing with data for use in charts and graphs, including describing the Cartesian coordinate system in 2D and 3D, explaining direct and inverse relationships between variables, and defining terms like mean, median, mode, independent and dependent variables, control, and empirically and computationally derived data.
Types of charts in Excel and How to use themVijay Perepa
There are different Chart types and some times we face difficulty to find which chart is suitable for a specific Data set. In this series of Videos, we have discussed about each chart type and when to use etc.
This document discusses different types of graphs and charts, their uses, and provides examples. It summarizes 6 common types: line graphs show trends over time; bar charts compare categorical data with bars; pie charts illustrate proportional data with slices; histograms show distributions of continuous data with columns; scatter plots show relationships between two variables with x-y axes; and Venn charts visualize logical relationships between groups with overlapping circles. The document provides examples and descriptions of when each type would be useful.
This document discusses different types of graphs and charts, their purposes and guidelines for use. It defines the key difference between graphs and charts, with graphs representing relationships between objects and charts representing data through symbols. Common chart types are described like line charts to show changes over time, bar charts to compare categories, and pie charts to show proportions of a whole. The document provides examples and guidelines for effective graph and chart creation.
Scientific illustrations like drawings, photographs, tables, and graphs can clearly show relationships and details that may be difficult to explain through text alone. Drawings can depict object details and hidden features. Photographs capture objects at a single moment. Tables organize data in rows and columns. Common graphs are line graphs showing relationships between two variables, bar graphs comparing variables, and circle graphs displaying parts of a whole. Careful analysis of scales is important when interpreting graphs.
The document discusses different types of charts including column charts, bar charts, pie charts, line charts, area charts, stock charts, radar charts, bubble charts, scatter charts, and combo charts. For each chart type, the document outlines typical uses, advantages, and disadvantages. It provides an example of each chart type to illustrate how the chart can be constructed and interpreted.
This document discusses different ways to present information visually, including tally charts, key points, bar charts, line graphs, and percentages. Tally charts can record responses to questions, using lines to show answers. Key points from sources should be highlighted and condensed into bullet points. Bar charts or line graphs can then display tallied answers or trends over time. Percentages can also represent parts of a whole, such as the proportion of people answering a question in the same way.
The document defines different types of charts and their uses. Column charts display changes over time and compare items in a group. Bar charts focus on comparing item values rather than time. Line charts show trends over intervals of time. Pie charts show the size of items in a data series. Scatter charts illustrate the relationship between numeric values. Area charts signify magnitude of change over time and contribution to a whole. Stock charts display high, low, and close values in the stock market.
Diagrams, charts, tables, and graphs are common ways to present information graphically. Diagrams can summarize processes and ideas more effectively than words. Charts such as bar charts and line graphs represent numerical data visually. Tables display key information, usually numbers, and can summarize data or start discussions. Graphs show patterns and trends when precise numbers are not needed.
This document provides information about different types of charts and graphs used to represent data visually, including pie charts, line graphs, bar charts, and tables. It explains what each of these graphical representations are through definitions and examples. Pie charts show percentages, line graphs show changes over time, bar charts show comparisons of discrete categories, and tables arrange data into rows and columns. The document is intended to teach about various ways to visually display quantitative information through graphical formats.
Topic: Dot Plot Presentation
Student Name: Misbah
Class: B.Ed. 2.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
This document discusses how to interpret charts and graphs. It explains that graphics provide information in a compact way compared to text. It identifies the most common types of graphs as line graphs, bar graphs, and pie charts. It also discusses tables and diagrams. The document emphasizes that graphics contain important information that supports the reading material, so readers should take time to carefully analyze charts, graphs, and tables.
This document discusses different types of charts that can be created in Microsoft Excel. It describes pie charts, column charts, line charts, bar charts, area charts, scatter charts, and other chart types. For each type of chart, it provides an example image and brief explanation of when and how it can be used. The document is intended to teach about the various charting capabilities in MS Excel.
Curious about the different types of chart? This presentation demonstrates the variety of charts and their purpose. All these charts have been created using Chartblocks online chart building tool.
Understanding visual information:Figure, Graph, Table, and DiagramMusfera Nara Vadia
This document discusses different types of visual information including figures, graphs, tables, and diagrams. It defines two-dimensional and three-dimensional figures. It also describes the most common types of graphs such as pie charts, bar graphs, scatter plots, and line graphs. Tables are explained as presenting lists of numbers or text in columns to synthesize information or present raw data. Diagrams are defined as using graphic images to present theoretical arguments visually.
This document discusses six common types of charts used in business: column chart, stacked bar chart, line chart, XY scatter plot, pie chart, and exploded pie chart. It defines each chart and provides examples to illustrate the type of data each chart is best suited to display. The column chart compares groups of data. The stacked bar chart shows the contribution of parts to a whole. The line chart indicates trends over time. The XY scatter plot shows correlations between two variables. The pie chart displays the percentage of parts in a whole. The exploded pie chart emphasizes portions of a pie chart.
This document discusses different types of charts and graphs that can be used to visually represent data. It provides examples of pie charts, bar charts, column charts, line charts, area charts, and scatter plots. Reasons for creating charts include making trends easily recognizable, allowing quick perception of information, and aiding data interpretation. Charts can be incorporated into business reports, web pages, posters, and other documents. Proper selection of charts is important to illustrate different types of data, such as time series data displayed in line graphs or comparisons shown in bar charts.
this ppt is about charts in ms excel.there are many types of chart used in ms excel but in this ppt some common types are defined,as line chart,bar,column,area ,scatter chart etc...
This document discusses various types of charts and graphs, including organizational charts, classification charts, timelines, flowcharts, and tabular charts. It provides examples of each type of chart. The document also discusses the purpose of charts, how to design effective charts, and software that can be used to create charts and graphs, such as OpenOffice Calc and Microsoft Excel.
Top 8 Different Types Of Charts In Statistics And Their UsesStat Analytica
This document discusses different types of charts used in statistics to visually represent data, including bar charts, line charts, pie charts, histograms, scatter plots, exponential graphs, and trigonometric graphs. Bar charts and line charts are useful for comparing data across categories and showing trends over time. Pie charts show proportions of data as slices of a circle. Histograms group data into bins to summarize continuous or discrete measurements. Scatter plots show the relationship between two numeric variables using positioned dots. Exponential and trigonometric graphs visually represent their respective functions and are used in engineering and research.
The document describes different types of charts that can be used to visualize data, including column charts, bar charts, line charts, pie charts, XY charts, area charts, doughnut charts, surface charts, bubble charts, stock charts, and cylinder, cone or pyramid charts. It provides examples of subtypes for some chart types and explains what each chart shows or compares.
There are several types of graphs that can be created in Excel, each suited to displaying different types of data. Bar graphs and line graphs are commonly used to show changes in numerical data over time or between categories. Scatter plots show trends in large data sets, while pie charts represent percentages and are used to show how parts of a whole are divided.
This document discusses how to improve the clarity of tables and graphs in research articles. It provides rules for constructing clear tables, such as splitting large tables and standardizing layout. When presenting tables, common problems to avoid are poorly positioning them on the page and manipulating spacing. Both tables and their contents should be explained in the text. The document also covers best practices for visualizations like pie charts, bar charts, and line graphs, noting tables are best for exact numbers while graphs show trends.
TID Chapter 5 Introduction To Charts And GraphWanBK Leo
This document discusses different types of charts and graphs that can be used to represent data visually. It describes common chart types like pie charts, bar charts, line graphs, and scatter plots. The document explains how each type of chart is best used depending on the nature of the data and the insights that need to be conveyed. It also provides guidance on creating charts in Excel and includes an example of a hands-on exercise for practicing generating different chart types from sample data sets.
Charts in Excel can display data in a more visually appealing and easy to understand format compared to tables of numbers. There are many components that make up a chart, including axes, data series, plot area, legend and more. Excel offers different types of charts, such as column, bar, line, area, pie, doughnut, scatter, radar, surface and stock charts, each suited to displaying certain types of data trends over time or in relation to other factors.
Area charts display changes in magnitude over time using colored areas below lines. They can be 2D or 3D, stacked to show contribution, or 100% stacked to show percentage contribution over time. Scatter charts show relationships between numeric variables and are used for scientific data. Bubble charts are like scatter charts but show three variables where the third determines bubble size. Stock charts illustrate price fluctuations over time using high, low, close values or including open and volume values.
It helps to you understand about statistics and helps in acquiring knowledge and helps to analysing the answers , and in the present generation helps to study about statistics
This document discusses different ways to present information visually, including tally charts, key points, bar charts, line graphs, and percentages. Tally charts can record responses to questions, using lines to show answers. Key points from sources should be highlighted and condensed into bullet points. Bar charts or line graphs can then display tallied answers or trends over time. Percentages can also represent parts of a whole, such as the proportion of people answering a question in the same way.
The document defines different types of charts and their uses. Column charts display changes over time and compare items in a group. Bar charts focus on comparing item values rather than time. Line charts show trends over intervals of time. Pie charts show the size of items in a data series. Scatter charts illustrate the relationship between numeric values. Area charts signify magnitude of change over time and contribution to a whole. Stock charts display high, low, and close values in the stock market.
Diagrams, charts, tables, and graphs are common ways to present information graphically. Diagrams can summarize processes and ideas more effectively than words. Charts such as bar charts and line graphs represent numerical data visually. Tables display key information, usually numbers, and can summarize data or start discussions. Graphs show patterns and trends when precise numbers are not needed.
This document provides information about different types of charts and graphs used to represent data visually, including pie charts, line graphs, bar charts, and tables. It explains what each of these graphical representations are through definitions and examples. Pie charts show percentages, line graphs show changes over time, bar charts show comparisons of discrete categories, and tables arrange data into rows and columns. The document is intended to teach about various ways to visually display quantitative information through graphical formats.
Topic: Dot Plot Presentation
Student Name: Misbah
Class: B.Ed. 2.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
This document discusses how to interpret charts and graphs. It explains that graphics provide information in a compact way compared to text. It identifies the most common types of graphs as line graphs, bar graphs, and pie charts. It also discusses tables and diagrams. The document emphasizes that graphics contain important information that supports the reading material, so readers should take time to carefully analyze charts, graphs, and tables.
This document discusses different types of charts that can be created in Microsoft Excel. It describes pie charts, column charts, line charts, bar charts, area charts, scatter charts, and other chart types. For each type of chart, it provides an example image and brief explanation of when and how it can be used. The document is intended to teach about the various charting capabilities in MS Excel.
Curious about the different types of chart? This presentation demonstrates the variety of charts and their purpose. All these charts have been created using Chartblocks online chart building tool.
Understanding visual information:Figure, Graph, Table, and DiagramMusfera Nara Vadia
This document discusses different types of visual information including figures, graphs, tables, and diagrams. It defines two-dimensional and three-dimensional figures. It also describes the most common types of graphs such as pie charts, bar graphs, scatter plots, and line graphs. Tables are explained as presenting lists of numbers or text in columns to synthesize information or present raw data. Diagrams are defined as using graphic images to present theoretical arguments visually.
This document discusses six common types of charts used in business: column chart, stacked bar chart, line chart, XY scatter plot, pie chart, and exploded pie chart. It defines each chart and provides examples to illustrate the type of data each chart is best suited to display. The column chart compares groups of data. The stacked bar chart shows the contribution of parts to a whole. The line chart indicates trends over time. The XY scatter plot shows correlations between two variables. The pie chart displays the percentage of parts in a whole. The exploded pie chart emphasizes portions of a pie chart.
This document discusses different types of charts and graphs that can be used to visually represent data. It provides examples of pie charts, bar charts, column charts, line charts, area charts, and scatter plots. Reasons for creating charts include making trends easily recognizable, allowing quick perception of information, and aiding data interpretation. Charts can be incorporated into business reports, web pages, posters, and other documents. Proper selection of charts is important to illustrate different types of data, such as time series data displayed in line graphs or comparisons shown in bar charts.
this ppt is about charts in ms excel.there are many types of chart used in ms excel but in this ppt some common types are defined,as line chart,bar,column,area ,scatter chart etc...
This document discusses various types of charts and graphs, including organizational charts, classification charts, timelines, flowcharts, and tabular charts. It provides examples of each type of chart. The document also discusses the purpose of charts, how to design effective charts, and software that can be used to create charts and graphs, such as OpenOffice Calc and Microsoft Excel.
Top 8 Different Types Of Charts In Statistics And Their UsesStat Analytica
This document discusses different types of charts used in statistics to visually represent data, including bar charts, line charts, pie charts, histograms, scatter plots, exponential graphs, and trigonometric graphs. Bar charts and line charts are useful for comparing data across categories and showing trends over time. Pie charts show proportions of data as slices of a circle. Histograms group data into bins to summarize continuous or discrete measurements. Scatter plots show the relationship between two numeric variables using positioned dots. Exponential and trigonometric graphs visually represent their respective functions and are used in engineering and research.
The document describes different types of charts that can be used to visualize data, including column charts, bar charts, line charts, pie charts, XY charts, area charts, doughnut charts, surface charts, bubble charts, stock charts, and cylinder, cone or pyramid charts. It provides examples of subtypes for some chart types and explains what each chart shows or compares.
There are several types of graphs that can be created in Excel, each suited to displaying different types of data. Bar graphs and line graphs are commonly used to show changes in numerical data over time or between categories. Scatter plots show trends in large data sets, while pie charts represent percentages and are used to show how parts of a whole are divided.
This document discusses how to improve the clarity of tables and graphs in research articles. It provides rules for constructing clear tables, such as splitting large tables and standardizing layout. When presenting tables, common problems to avoid are poorly positioning them on the page and manipulating spacing. Both tables and their contents should be explained in the text. The document also covers best practices for visualizations like pie charts, bar charts, and line graphs, noting tables are best for exact numbers while graphs show trends.
TID Chapter 5 Introduction To Charts And GraphWanBK Leo
This document discusses different types of charts and graphs that can be used to represent data visually. It describes common chart types like pie charts, bar charts, line graphs, and scatter plots. The document explains how each type of chart is best used depending on the nature of the data and the insights that need to be conveyed. It also provides guidance on creating charts in Excel and includes an example of a hands-on exercise for practicing generating different chart types from sample data sets.
Charts in Excel can display data in a more visually appealing and easy to understand format compared to tables of numbers. There are many components that make up a chart, including axes, data series, plot area, legend and more. Excel offers different types of charts, such as column, bar, line, area, pie, doughnut, scatter, radar, surface and stock charts, each suited to displaying certain types of data trends over time or in relation to other factors.
Area charts display changes in magnitude over time using colored areas below lines. They can be 2D or 3D, stacked to show contribution, or 100% stacked to show percentage contribution over time. Scatter charts show relationships between numeric variables and are used for scientific data. Bubble charts are like scatter charts but show three variables where the third determines bubble size. Stock charts illustrate price fluctuations over time using high, low, close values or including open and volume values.
It helps to you understand about statistics and helps in acquiring knowledge and helps to analysing the answers , and in the present generation helps to study about statistics
The document discusses graphical representation of data using statistical tools. It describes different types of graphs like bar charts, pie charts, scatter plots, and line charts. It explains how to select the appropriate graph based on the type of data and analyze the data. It also discusses limitations of graphs and statistical analysis methods like calculating mean and standard deviation to analyze data in a robust way.
This document discusses various methods for graphically displaying data in statistics, including time series graphs, bar charts, histograms, circle graphs, dot plots, stem plots, ogives, and indicators of misleading graphs. It provides examples and descriptions of how to properly interpret and construct each type of graph. Key points include showing change over time with time series graphs, comparing categories with bar charts, displaying continuous or binned data with histograms, showing percentages with circle graphs, listing all values with dot and stem plots, and calculating cumulative frequencies with ogives. Misleading graphs are identified as those that distort scale, lack labels, omit data, or have uneven bins.
This document is a lab file submitted by Sukhchain Aggarwal, a student of B.com, to their professor Harjeet Kaur. It contains an acknowledgement thanking the professors for their guidance. The document then outlines how to create different types of charts in Microsoft Excel, including line charts, bar charts, and pie charts. It provides examples of each chart type using sample data on test scores and the numbers of students in different years. Tables are included showing average, maximum, and minimum values calculated from the data using Excel formulas. Sources consulted for the file are listed in a bibliography.
The document discusses different types of graphs used in science: line graphs, bar graphs, and pie graphs. It explains that graphs are useful for organizing and analyzing quantitative data by showing relationships and allowing scientists to identify patterns and make predictions. The key types are defined as follows: line graphs show the relationship between two variables over time; bar graphs compare data categories; and pie graphs divide a whole into percentage parts to visualize proportions. Examples of each type are provided.
This document provides an overview of different types of charts used for data visualization, including column charts, bar charts, pie charts, doughnut charts, line charts, area charts, scatter charts, spider/radar charts, gauge charts, and comparison charts. It describes the purpose and use of each chart type, highlighting when each type is most effective to visualize different kinds of data relationships. The document aims to help readers select the most appropriate chart type based on their data and visualization goals.
This document discusses different types of graphs used to present statistical data. It provides examples and guidelines for bar graphs, pie charts, histograms, line graphs, and pictographs. Bar graphs can show categorical data and frequencies. Pie charts represent qualitative data through wedge-shaped slices. Histograms use bars to depict continuous data grouped into ranges or classes. Line graphs illustrate relationships that change over time. Pictographs use images to demonstrate quantities. Being able to interpret and construct these various graphs is important for analyzing real-world data.
Graphs are pictorial representations that organize data visually. There are four main types of graphs: line graphs, bar graphs, histograms, and pie charts. Graphs are widely used in fields like business, science, and medicine to clarify trends, estimate key values at a glance, see variations in data, and permit visual checks of calculations. They show relationships between variables and are useful for comparing data across groups or tracking changes over time.
The document discusses different types of bar graphs, including vertical, horizontal, stacked, and grouped bar graphs. It provides examples of how to represent data using bar graphs and tips for creating bar graphs. Some key points covered include that bar graphs show data using rectangular bars of varying heights, they can represent categorical or quantitative data, and they are useful for comparing quantities across different categories.
Graphical representations are useful tools for presenting statistical data in a visual format that is easier to understand compared to textual or tabular representations. They translate complex numerical concepts into simple, concrete forms through the use of diagrams, charts, and plots. Some key advantages of graphical representations are that they facilitate comparisons, help identify relationships and patterns in the data, and attract attention in a time-efficient manner. However, they also have limitations such as only conveying vague ideas, providing limited precision and information, and restricting further data analysis. Common types of graphical representations used in statistics include histograms, frequency polygons, pie charts, scatter plots, and time series graphs.
This document provides an overview of data visualization techniques that can help non-technical audiences understand and make sense of data. It discusses the importance of selecting the right chart type for the data, such as using histograms to show variation, line graphs for trends over time, and Pareto charts to identify the vital few causes of issues. The document also covers techniques for smoothing time series data, such as moving averages, to identify underlying trends. The goal is to help organizations at all levels make better decisions and improve performance through effective data communication and interpretation.
BUSINESS INTELLIGENCE AND DATA ANALYTICS presentationMohit Negi
SIX SIGMA APPROACH, DIFFERENT TYPES OF CHARTS AND THEIR FUNCTION, DASHBOARD, BUSINESS INTELLIGENCE, DATA VISUALISATION INFORMATION VISUALISATION, PERFORMANCE DASHBOARD, BUSINESS REPORTING, BALANCE SCORECARD
The document discusses the importance and uses of visual aids in communication. It notes that visual aids like illustrations, tables, graphs and diagrams are more effective than plain text alone. They help reduce space, increase understanding and make complex ideas and data more easily comprehensible. The document also provides examples of different types of visual aids like tables, bar graphs, flowcharts and maps and discusses when and how they should be used.
This PowerPoint presentation is about organizing and presenting data. It will show you which types of graphs to use when presenting your data. Feel free to save and share it! Please do like my PPT THANKS!!
All pictures and descriptions are from Google (I can't find the links).
note: this presentation doesn't have complete information about organizing and presenting data and only shows important pieces of information about organizing and presenting data and the common graphs that are used in data presentation.
Understanding between Visual Studio vs Visual Studio Code may depend on your work style and features and the language support you need. Here's the difference.
Do you need Excel homework help? Hire our MS Excel experts to get the best Help With Excel Homework. Ask us to do my Excel Homework at affordable prices.
Most prominent methods of how to find outliers in statisticsStat Analytica
This document discusses two prominent methods for finding outliers in statistics: the interquartile range (IQR) method and the Tukey method. Both methods use quartiles to determine a range of values that are not outliers, and then identify outliers as any data points that fall above or below this range. The document provides examples of each method being applied to sample data sets to identify outlier values. It concludes by encouraging the use of these IQR and Tukey methods to solve problems involving outliers.
The Comprehensive Guide on Branches of MathematicsStat Analytica
Are you struggling to get all the branches of mathematics? If yes then here is the best ever presentation that will help you to get all the branches of math. Here we have mentioned the basic mathematics branches to the advanced level.
Top 10 importance of mathematics in everyday lifeStat Analytica
Would you like to know the importance of mathematics? If yes, then have a look at this presentation to explore the top uses of mathematics in our daily life. Watch the presentation till the end to explore the importance of mathematics.
The document discusses data classification, which involves organizing data into categories to make it easier to analyze and retrieve. It covers the objectives of classification like arranging large volumes of data and highlighting similarities. The key types are one-way, two-way, and multi-way classification. Classification provides benefits like confidentiality, integrity, and availability of data. Methods involve scanning, identifying, separating data, and creating a classification policy.
Analysis of variance (ANOVA) everything you need to knowStat Analytica
Most of the students may struggle with the analysis of variance (ANOVA). Here in this presentation you can clear all your doubts in analysis of variance with suitable examples.
The Basics of Statistics for Data Science By StatisticiansStat Analytica
Want to learn data science, but don't know how to start learn data science from scratch? Here in this presentation you will going to learn the basics of statistics for data science. Start learn these basic statistics to get the good command over data science.
Top tips on how to learn math with these simple waysStat Analytica
Finding it difficult to learn math? If yes, then here are the best ever tips on how to learn math from basic to the advanced level. Follow all these tips to start leaning math and get decent command over math.
What are the uses of excel in our daily life?Stat Analytica
Excel is one of the most powerful spreadsheet software in the world. There are plenty of uses of excel in our daily life. Have a look on the top uses of excel in the world. Watch the presentation till the end to explore all the uses of excel.
Math is a subject which is simple for some students and also complicated for some students, so we will discuss a topic related to math that How to solve math problems and which types of math problems can we solve quickly by step by step. In many ways, Math problems can be solved, but now the question is how to solve math problems.
If you want math homework help than you can get the math homework helpers here. Homework help in math from our experts and homework help with math gives the perfect math homework help online. My math homework help is the best way to get help me math homework. college math homework help also available here.
The Best Ever Tips on How to Study for ExamsStat Analytica
Only a few week left for the exams. Do you want to get the best ever tips on how to study for exams? Here are the best among the best tricks on how to study for exams. Follow all these tips mentioned in the presentation to do the proper study for exams.
A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 795 from Texas, New Mexico, Oklahoma, and Kansas. 95 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
Understanding P–N Junction Semiconductors: A Beginner’s GuideGS Virdi
Dive into the fundamentals of P–N junctions, the heart of every diode and semiconductor device. In this concise presentation, Dr. G.S. Virdi (Former Chief Scientist, CSIR-CEERI Pilani) covers:
What Is a P–N Junction? Learn how P-type and N-type materials join to create a diode.
Depletion Region & Biasing: See how forward and reverse bias shape the voltage–current behavior.
V–I Characteristics: Understand the curve that defines diode operation.
Real-World Uses: Discover common applications in rectifiers, signal clipping, and more.
Ideal for electronics students, hobbyists, and engineers seeking a clear, practical introduction to P–N junction semiconductors.
How to track Cost and Revenue using Analytic Accounts in odoo Accounting, App...Celine George
Analytic accounts are used to track and manage financial transactions related to specific projects, departments, or business units. They provide detailed insights into costs and revenues at a granular level, independent of the main accounting system. This helps to better understand profitability, performance, and resource allocation, making it easier to make informed financial decisions and strategic planning.
Exploring Substances:
Acidic, Basic, and
Neutral
Welcome to the fascinating world of acids and bases! Join siblings Ashwin and
Keerthi as they explore the colorful world of substances at their school's
National Science Day fair. Their adventure begins with a mysterious white paper
that reveals hidden messages when sprayed with a special liquid.
In this presentation, we'll discover how different substances can be classified as
acidic, basic, or neutral. We'll explore natural indicators like litmus, red rose
extract, and turmeric that help us identify these substances through color
changes. We'll also learn about neutralization reactions and their applications in
our daily lives.
by sandeep swamy
A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 817 from Texas, New Mexico, Oklahoma, and Kansas. 97 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
CURRENT CASE COUNT: 817 (As of 05/3/2025)
• Texas: 688 (+20)(62% of these cases are in Gaines County).
• New Mexico: 67 (+1 )(92.4% of the cases are from Eddy County)
• Oklahoma: 16 (+1)
• Kansas: 46 (32% of the cases are from Gray County)
HOSPITALIZATIONS: 97 (+2)
• Texas: 89 (+2) - This is 13.02% of all TX cases.
• New Mexico: 7 - This is 10.6% of all NM cases.
• Kansas: 1 - This is 2.7% of all KS cases.
DEATHS: 3
• Texas: 2 – This is 0.31% of all cases
• New Mexico: 1 – This is 1.54% of all cases
US NATIONAL CASE COUNT: 967 (Confirmed and suspected):
INTERNATIONAL SPREAD (As of 4/2/2025)
• Mexico – 865 (+58)
‒Chihuahua, Mexico: 844 (+58) cases, 3 hospitalizations, 1 fatality
• Canada: 1531 (+270) (This reflects Ontario's Outbreak, which began 11/24)
‒Ontario, Canada – 1243 (+223) cases, 84 hospitalizations.
• Europe: 6,814
CBSE - Grade 8 - Science - Chemistry - Metals and Non Metals - WorksheetSritoma Majumder
Introduction
All the materials around us are made up of elements. These elements can be broadly divided into two major groups:
Metals
Non-Metals
Each group has its own unique physical and chemical properties. Let's understand them one by one.
Physical Properties
1. Appearance
Metals: Shiny (lustrous). Example: gold, silver, copper.
Non-metals: Dull appearance (except iodine, which is shiny).
2. Hardness
Metals: Generally hard. Example: iron.
Non-metals: Usually soft (except diamond, a form of carbon, which is very hard).
3. State
Metals: Mostly solids at room temperature (except mercury, which is a liquid).
Non-metals: Can be solids, liquids, or gases. Example: oxygen (gas), bromine (liquid), sulphur (solid).
4. Malleability
Metals: Can be hammered into thin sheets (malleable).
Non-metals: Not malleable. They break when hammered (brittle).
5. Ductility
Metals: Can be drawn into wires (ductile).
Non-metals: Not ductile.
6. Conductivity
Metals: Good conductors of heat and electricity.
Non-metals: Poor conductors (except graphite, which is a good conductor).
7. Sonorous Nature
Metals: Produce a ringing sound when struck.
Non-metals: Do not produce sound.
Chemical Properties
1. Reaction with Oxygen
Metals react with oxygen to form metal oxides.
These metal oxides are usually basic.
Non-metals react with oxygen to form non-metallic oxides.
These oxides are usually acidic.
2. Reaction with Water
Metals:
Some react vigorously (e.g., sodium).
Some react slowly (e.g., iron).
Some do not react at all (e.g., gold, silver).
Non-metals: Generally do not react with water.
3. Reaction with Acids
Metals react with acids to produce salt and hydrogen gas.
Non-metals: Do not react with acids.
4. Reaction with Bases
Some non-metals react with bases to form salts, but this is rare.
Metals generally do not react with bases directly (except amphoteric metals like aluminum and zinc).
Displacement Reaction
More reactive metals can displace less reactive metals from their salt solutions.
Uses of Metals
Iron: Making machines, tools, and buildings.
Aluminum: Used in aircraft, utensils.
Copper: Electrical wires.
Gold and Silver: Jewelry.
Zinc: Coating iron to prevent rusting (galvanization).
Uses of Non-Metals
Oxygen: Breathing.
Nitrogen: Fertilizers.
Chlorine: Water purification.
Carbon: Fuel (coal), steel-making (coke).
Iodine: Medicines.
Alloys
An alloy is a mixture of metals or a metal with a non-metal.
Alloys have improved properties like strength, resistance to rusting.
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This chapter provides an in-depth overview of the viscosity of macromolecules, an essential concept in biophysics and medical sciences, especially in understanding fluid behavior like blood flow in the human body.
Key concepts covered include:
✅ Definition and Types of Viscosity: Dynamic vs. Kinematic viscosity, cohesion, and adhesion.
⚙️ Methods of Measuring Viscosity:
Rotary Viscometer
Vibrational Viscometer
Falling Object Method
Capillary Viscometer
🌡️ Factors Affecting Viscosity: Temperature, composition, flow rate.
🩺 Clinical Relevance: Impact of blood viscosity in cardiovascular health.
🌊 Fluid Dynamics: Laminar vs. turbulent flow, Reynolds number.
🔬 Extension Techniques:
Chromatography (adsorption, partition, TLC, etc.)
Electrophoresis (protein/DNA separation)
Sedimentation and Centrifugation methods.
How to Manage Opening & Closing Controls in Odoo 17 POSCeline George
In Odoo 17 Point of Sale, the opening and closing controls are key for cash management. At the start of a shift, cashiers log in and enter the starting cash amount, marking the beginning of financial tracking. Throughout the shift, every transaction is recorded, creating an audit trail.
INTRO TO STATISTICS
INTRO TO SPSS INTERFACE
CLEANING MULTIPLE CHOICE RESPONSE DATA WITH EXCEL
ANALYZING MULTIPLE CHOICE RESPONSE DATA
INTERPRETATION
Q & A SESSION
PRACTICAL HANDS-ON ACTIVITY
Title: A Quick and Illustrated Guide to APA Style Referencing (7th Edition)
This visual and beginner-friendly guide simplifies the APA referencing style (7th edition) for academic writing. Designed especially for commerce students and research beginners, it includes:
✅ Real examples from original research papers
✅ Color-coded diagrams for clarity
✅ Key rules for in-text citation and reference list formatting
✅ Free citation tools like Mendeley & Zotero explained
Whether you're writing a college assignment, dissertation, or academic article, this guide will help you cite your sources correctly, confidently, and consistent.
Created by: Prof. Ishika Ghosh,
Faculty.
📩 For queries or feedback: [email protected]
Top 7 types of Statistics Graphs for Data Representation
1. 01 Top 7 Types of
Statistics Graphs
for Data
Representation
Statanalytica
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2. Overview
Statistics is one of the most crucial parts of our life.
Without statistics, data is nothing. We can’t utilize
different data without the use of statistics. Therefore
the significant role of statistics is to represent the
data in a meaningful way. In this way, anyone can
understand the data without in-depth knowledge of
statistics. Most of the time, the statistics data sets
contain massive amounts of values. It is hard to
represent these values in the form of lists and articles.
That is why the graphs come into existence to
represent the aggregate statistic value in clean and
well-managed order. Here in this blog, we will share
with you the top 7 types of statistics graphs commonly
used in statistics.
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3. A Pareto diagram is also known as a bar chart. It is the best
way to represent the qualitative data. It was developed in
the early 1900s by Vilfredo Pareto. He used this graph to
conduct his study on wealth and poverty. This chart offers
two ways to display the data. You can either represent the
data horizontally or vertically. You can use it to compare
data, such as amounts, characteristics, times, and
frequency. The bar of this graph is emphasized with
essential categories. You can quickly get an idea from this
bar that which category has the highest amount of data.
There are three types of bars in this chart i.e., single,
stacked, and grouped.
Pareto Diagram or Bar
Graph
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4. A circle graph is also known as Pie charts. It is also one of
the widely used statistics graphs in the world. Statisticians
commonly used these graphs to represent the data
graphically. As the name suggests, this graph looks like a
circular pie with a few slices. Besides, we use this type of
statistics graph to represent that qualitative data.
Qualitative data means the data is not presented in
numerical form. Besides, we put the different categories in
each slice of the pie. The size of slices varies upon the data.
Some slices might be more significant, and some might be
smaller.
Pie Chart or Circle Graph
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5. The histogram is another best statistics graph to represent
the data. We use it to express quantitative data. In this
graph, the range of values is known as classes. If the
classes contain the lower frequencies, then it would have
the shorter as compared with the taller ones that contain,
the higher frequency. Most of the students get confused
with the bar chart and the histogram. Because both of these
look quite similar. But these graphs are different from each
other in terms of the data measurement levels. In bar
charts, the frequency of categorical data is the primary
factor. While in the histogram, the data with ordinal values
are the primary factor. Ordinal values are not easily
measured i.e., feelings, opinions, suggestions.
Histogram
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6. A stem and leaf plot is one of the best statistics graphs to
represent the quantitative data. This graph breaks each
value of a quantitative data set into two pieces. These
pieces are often known as the stem and the leaf.
Furthermore, the higher places values are known as the
stem, and the other places values are known as the leaf.
We can list all the data values in a compact form with the
help of this graph. It is a device that is used to represent the
data set. It evolved in the early 1900s from Arthur Bowley’s
work. Most of the statisticians use it for data analysis work.
Stem and Leaf Plot
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06
7. It is not that much of a famous statistics graph. Most of the
experts say that it is a hybrid of the histogram and a stem
and leaf plot. In this type of graph, each value is
represented as the dot, and this dot is placed above the
appropriate class. We use this graph to represent
quantitative data values. Likewise, we use the rectangles
and bars in histograms. In the same way, we use the dots
which are joined with the help of simple lines. We use
these graphs to compare the data of many individuals.
Dot Plot
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8. Scatterplots graphs are one of the famous statistics graphs
that use in most of the powerful statistics software. It is
used to display data based on the horizontal axis and
vertical axis. I have mentioned earlier that the statistics
tools of correlation of regression are used to show trends
with the scatterplot. In the scatterplot, the lines or curve is
used to show the data. This chart goes upside down and left
to right. Scatter means to place the points at different
places to each other. It is the statistics chart to uncover the
potential of the dataset.
Scatterplots
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9. The time-series graph is one of the most popular statistics
graphs among statisticians. It is used to represent the data
points in time. It is the statistics graph that is used for a
certain kind of paired data. We use this graph to measure
the trends over a certain period of time. Here in this
statistics graph, the timeframe can contain the minutes,
hours, days, months, years, decades, or even centuries.
Time-Series Graphs
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10. Conclusion
All these seven types of statistics graphs are the major
ones. Apart from that, there are other types of statistics
graphs, too i.e., the statistics bar graphs, statistics
misleading graphs, statistics line graphs, and even
statistics bad graphs. Most of the statistics students are
also well aware of exponentials graphs, logarithmic
graphs, trigonometric graphs, cartesian graphs, and
frequency distributions graphs.
Now you will be more confident about the use of graphs
for different kinds of data. At last, I would like to say that
you should use the right statistics graph as per your
data set.
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