In this presentation, we look at using line graphs in technical writing; looking at what type of data they are used for, how to make them and how to describe them.
How to use line graphs in technical writing; what kid of data they're used to show, different kinds of charts, how to describe them and language tips for describing change and time.
How to use line graphs in technical writing; what kid of data they're used to show, different kinds of charts, how to describe them and language tips for describing change and time.
Column charts explained simply. Types of charts, and how to choose the right type of column chart and format it well.
Simple instructions for beginners, some knowledge of excel needed.
Level - Easy. 1st in a series on Column Charts, 3rd in my series on Charts.
Line, bar and Pie graphsNameInstitution 1.docxsmile790243
Line, bar and Pie graphs
Name
Institution
1
Introduction
Businesses report research reports regularly
Business mostly use bar, line and pie graphs to present data
Graphs are visual representation of data
Graphs make the information easy to understand
Graphs help in incorporating numerical data in reports
Makes numerical data easy to read and understand
Presentation reviews the bar, line and pie graphs
Business present reports on a regular basis. One common feature in business reports is colorful graphics used to convey information in an easy to understand manner. The graphs help to describe something about the business such as describing the sales of a company in the last ten weeks. Numerical data is hard to understand for most people but presenting them in graphs makes it easier to digest and understand. A graph can be defined as a visual representation of data. Representing information and numerical data in graphs makes it easy to understand for people who are not mathematically savvy. Some of the graphs commonly used by businesses and discussed in this presentation are line, bar and pie graphs.
2
Line graph
Line graphs represent data that change with time, which helps in showing the manner in which data changes with time. it also helps in comparing two different types of information by showing the manner n which they are similar of differ.
The graph above shows the sales per month for various six models for six months. The labels on the vertical axis indicate the number of units sold by various car model manufacturers. The labels on the horizontal axis is the months during which the data was recorded. Therefore, this line graph presents the data for car models sold between January and June. The graph uses line with different colors with each color representing each model. For instance, the red color represents the Toyota Camry car model. The sales for Honda Accord during the month of February is 20,000 units.
3
Bar graphs
The bar graph is similar to the line graph only that the bar graph only that this type of graphs uses horizontal or vertical bars that represent a different value. Bar graphs also helps in comparing things between different groups of tracking changes that occur over time. Each bar graph represents a separate quantity.
The bar graph measures the units sales (in thousands) of a company between the fiscal years of 2014 to 2018. The labels on the vertical axis indicates that the vertical axis represents the units of sales made by the company. The labels of the horizontal axis shows that the horizontal axis represents the fiscal years during which the data was collected.
4
Pie graph
The pie graph is a graphical presentation of data as proportionally sized slices using percentage values. The graph shows the sizes of parts of some total quantity at a specific time. The pie graph above measures the percentages of the Nissan Leaf car model newly registered in various European countries b ...
ASSESSMENT CASE PAPER ANALYSIS / TUTORIALOUTLET DOT COMjorge0048
A report broken down into the following sections:
Summary results and recommendations—up front, concise, and to the point.
Answers to the 6 questions asked—devote a paragraph to each, with individual headings
Time Series Analysis - 1 | Time Series in R | Time Series Forecasting | Data ...Simplilearn
This Time Series Analysis (Part-1) in R presentation will help you understand what is time series, why time series, components of time series, when not to use time series, why does a time series have to be stationary, how to make a time series stationary and at the end, you will also see a use case where we will forecast car sales for 5th year using the given data. A time series is a sequence of data being recorded at specific time intervals. The past values are analyzed to forecast a future which is time-dependent. Compared to other forecast algorithms, with time series we deal with a single variable which is dependent on time. So, lets deep dive into this presentation and understand what is time series and how to implement time series using R.
Below topics are explained in this "Time Series in R Tutorial" -
1. Why time series?
2. What is time series?
3. Components of a time series
4. When not to use time series?
5. Why does a time series have to be stationary?
6. How to make a time series stationary?
7. Example: Forcast car sales for the 5th year
Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment.
Why learn Data Science with R?
1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc
2. According to marketsandmarkets.com, the advanced analytics market will be worth $29.53 Billion by 2019
3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is $118,709
4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT
The Data Science with R is recommended for:
1. IT professionals looking for a career switch into data science and analytics
2. Software developers looking for a career switch into data science and analytics
3. Professionals working in data and business analytics
4. Graduates looking to build a career in analytics and data science
5. Anyone with a genuine interest in the data science field
6. Experienced professionals who would like to harness data science in their fields
Learn more at: https://www.simplilearn.com/
In this presentation, we go through the process of analyzing and describing a bar chart in detail. We look at identifying trends and giving examples that support the trend.
We then look at identifying a second trend in the same chart and describing that one.
A guide to using bar charts in technical writing, including, the type of data they are used, design guidelines, and how to analyze and describe them.
The presentation includes a detailed walkthrough of the process of analyzing and describing a bar chart, including identifying a trend and providing evidence for it.
In this lesson, we look at the reason we use graphics and visuals and some important things to bear in mind when using them. We also look at how to describe them.
Column charts explained simply. Types of charts, and how to choose the right type of column chart and format it well.
Simple instructions for beginners, some knowledge of excel needed.
Level - Easy. 1st in a series on Column Charts, 3rd in my series on Charts.
Line, bar and Pie graphsNameInstitution 1.docxsmile790243
Line, bar and Pie graphs
Name
Institution
1
Introduction
Businesses report research reports regularly
Business mostly use bar, line and pie graphs to present data
Graphs are visual representation of data
Graphs make the information easy to understand
Graphs help in incorporating numerical data in reports
Makes numerical data easy to read and understand
Presentation reviews the bar, line and pie graphs
Business present reports on a regular basis. One common feature in business reports is colorful graphics used to convey information in an easy to understand manner. The graphs help to describe something about the business such as describing the sales of a company in the last ten weeks. Numerical data is hard to understand for most people but presenting them in graphs makes it easier to digest and understand. A graph can be defined as a visual representation of data. Representing information and numerical data in graphs makes it easy to understand for people who are not mathematically savvy. Some of the graphs commonly used by businesses and discussed in this presentation are line, bar and pie graphs.
2
Line graph
Line graphs represent data that change with time, which helps in showing the manner in which data changes with time. it also helps in comparing two different types of information by showing the manner n which they are similar of differ.
The graph above shows the sales per month for various six models for six months. The labels on the vertical axis indicate the number of units sold by various car model manufacturers. The labels on the horizontal axis is the months during which the data was recorded. Therefore, this line graph presents the data for car models sold between January and June. The graph uses line with different colors with each color representing each model. For instance, the red color represents the Toyota Camry car model. The sales for Honda Accord during the month of February is 20,000 units.
3
Bar graphs
The bar graph is similar to the line graph only that the bar graph only that this type of graphs uses horizontal or vertical bars that represent a different value. Bar graphs also helps in comparing things between different groups of tracking changes that occur over time. Each bar graph represents a separate quantity.
The bar graph measures the units sales (in thousands) of a company between the fiscal years of 2014 to 2018. The labels on the vertical axis indicates that the vertical axis represents the units of sales made by the company. The labels of the horizontal axis shows that the horizontal axis represents the fiscal years during which the data was collected.
4
Pie graph
The pie graph is a graphical presentation of data as proportionally sized slices using percentage values. The graph shows the sizes of parts of some total quantity at a specific time. The pie graph above measures the percentages of the Nissan Leaf car model newly registered in various European countries b ...
ASSESSMENT CASE PAPER ANALYSIS / TUTORIALOUTLET DOT COMjorge0048
A report broken down into the following sections:
Summary results and recommendations—up front, concise, and to the point.
Answers to the 6 questions asked—devote a paragraph to each, with individual headings
Time Series Analysis - 1 | Time Series in R | Time Series Forecasting | Data ...Simplilearn
This Time Series Analysis (Part-1) in R presentation will help you understand what is time series, why time series, components of time series, when not to use time series, why does a time series have to be stationary, how to make a time series stationary and at the end, you will also see a use case where we will forecast car sales for 5th year using the given data. A time series is a sequence of data being recorded at specific time intervals. The past values are analyzed to forecast a future which is time-dependent. Compared to other forecast algorithms, with time series we deal with a single variable which is dependent on time. So, lets deep dive into this presentation and understand what is time series and how to implement time series using R.
Below topics are explained in this "Time Series in R Tutorial" -
1. Why time series?
2. What is time series?
3. Components of a time series
4. When not to use time series?
5. Why does a time series have to be stationary?
6. How to make a time series stationary?
7. Example: Forcast car sales for the 5th year
Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment.
Why learn Data Science with R?
1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc
2. According to marketsandmarkets.com, the advanced analytics market will be worth $29.53 Billion by 2019
3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is $118,709
4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT
The Data Science with R is recommended for:
1. IT professionals looking for a career switch into data science and analytics
2. Software developers looking for a career switch into data science and analytics
3. Professionals working in data and business analytics
4. Graduates looking to build a career in analytics and data science
5. Anyone with a genuine interest in the data science field
6. Experienced professionals who would like to harness data science in their fields
Learn more at: https://www.simplilearn.com/
In this presentation, we go through the process of analyzing and describing a bar chart in detail. We look at identifying trends and giving examples that support the trend.
We then look at identifying a second trend in the same chart and describing that one.
A guide to using bar charts in technical writing, including, the type of data they are used, design guidelines, and how to analyze and describe them.
The presentation includes a detailed walkthrough of the process of analyzing and describing a bar chart, including identifying a trend and providing evidence for it.
In this lesson, we look at the reason we use graphics and visuals and some important things to bear in mind when using them. We also look at how to describe them.
An introduction to using pie charts in technical writing; what kind of data they are used to show, when to use them, how to make them and how to discuss their contents.
How to write a technical process description; how to describe a process; what information to include; how to incorporate visuals into your description.
An introduction to using graphics and visual aids in technical writing; how to use visuals, how to choose the right ones and how to use them professionally.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
37. 1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
11,000
January February March April May
Camaro
Mustang
Figure 1. Total Sales Camaro and Mustang: January - May, 2019
Sales of the Chevrolet Camaro rose steadily from 5,500 to 11,000
between January and April. This was followed by a slight drop to around
10,000 sales in May. Similarly, sales for the Ford Mustang started at
around 3,000 in January and rose slightly in February before there was a
sharp increase to around 8,250 in March. However, sales of the Mustang
then steadily declined in the following two months.
39. 1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
11,000
January February March April May
Camaro
Mustang
Figure 1. Total Sales Camaro and Mustang: January - May, 2019
Sales of the Chevrolet Camaro rose steadily from 5,500 to 11,000
between January and April. This was followed by a slight drop to around
10,000 sales in May. Similarly, sales for the Ford Mustang started at
around 3,000 in January and rose slightly in February before there was a
sharp increase to around 8,250 in March. However, sales of the Mustang
then steadily declined in the following two months.
41. 1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
11,000
January February March April May
Camaro
Mustang
Figure 1. Total Sales Camaro and Mustang: January - May, 2019
Sales of the Chevrolet Camaro rose steadily from 5,500 to 11,000
between January and April. This was followed by a slight drop to around
10,000 sales in May. Similarly, sales for the Ford Mustang started at
around 3,000 in January and rose slightly in February before there was a
sharp increase to around 8,250 in March. However, sales of the Mustang
then steadily declined in the following two months.
43. 1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
11,000
January February March April May
Camaro
Mustang
Figure 1. Total Sales Camaro and Mustang: January - May, 2019
Sales of the Chevrolet Camaro rose steadily from 5,500 to 11,000
between January and April. This was followed by a slight drop to around
10,000 sales in May. Similarly, sales for the Ford Mustang started at
around 3,000 in January and rose slightly in February before there was a
sharp increase to around 8,250 in March. However, sales of the Mustang
then steadily declined in the following two months.
49. Use a combination of
‘adjective + noun’ and ‘noun
+ adjective’ structures.
Tip:
50. 1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
11,000
January February March April May
Camaro
Mustang
Figure 1. Total Sales Camaro and Mustang: January - May, 2019
Sales of the Chevrolet Camaro rose steadily from 5,500 to 11,000
between January and April. This was followed by a slight drop to around
10,000 sales in May. Similarly, sales for the Ford Mustang started at
around 3,000 in January and rose slightly in February before there was a
sharp increase to around 8,250 in March. However, sales of the Mustang
then steadily declined in the following two months.