This document discusses graphical presentation of data. It covers organizing and graphing qualitative and grouped data using different chart types such as bar charts, histograms, pie charts, frequency polygons and cumulative frequency polygons. The chapter also discusses quantitative and qualitative variables in research methodology. It explains different data levels including nominal and ordinal categorical data. Finally, the document discusses business research statistical measurement based on population sampling. In summary, the chapter provides an overview of graphical data presentation and statistical concepts.
This presentation was provided by Steve Braun of Northeastern University Libraries during the NISO event, "Assessment Practices and Metrics for the 21st Century," held on Friday, November 16, 2018.
This document provides floor plans and summaries for two AutoCAD drawings: a single-detached two-storey residential building. The ground floor plan and second floor plan illustrate skills like layer management, accurate dimensions, annotations, and adhering to building code requirements. Creating clean 2D plans is an important skill for planning and development. The ability to efficiently use CAD software makes one a more versatile team member than relying on other departments.
The Center for Spatial Research (CSR) is a Russian company that has specialized in geomarketing techniques and solutions since 2003. CSR provides professional geomarketing services and solutions to over 100 B2B and B2G clients in retail, construction, banking, and other industries. CSR's projects utilize techniques such as niche occupying, data accumulation, and simple geomarketing models and tools to provide strategic and operational recommendations. CSR also engages in research and development to improve geomarketing methods and models, and provides geomarketing training programs.
Trends in managing information technology in 2020IJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these are
This document provides an introduction to data visualization. It discusses the importance of data visualization for clearly communicating complex ideas in reports and statements. The document outlines the data visualization process and different types of data and relationships that can be visualized, including quantitative and qualitative data. It also discusses various formats for visualizing data, with the goal of helping readers understand data visualization and how to create interactive visuals and analyze data.
an introduction to service science that provides the basics of: service system thinking, service system dynamics, service system re-design examples, and tries to answer the "why questions" - end notes include the birth of service science, discussion of advanced manufacturing, outsourcing, sustainability, as well as ways to learn more about service science
2021004 jim spohrer alan hartman_retirement v3ISSIP
(1) The document discusses the future of artificial intelligence and service science in a post-pandemic society from a service science perspective. (2) It compares AI, which aims to automate human intelligence, to service science, which studies how systems like businesses and societies can transform and improve lives through cooperation. (3) The document outlines how service science views systems as evolving over time through running existing practices, transforming by adopting new practices, and innovating to create new practices.
The document discusses linking service science with policymaking to enable desirable societal outcomes. It outlines that service science studies value co-creation interactions in service systems and that policies can shape rules and incentives to connect interactions with outcomes. The document also provides background on key concepts in service science like the service-dominant logic and definitions of service systems.
This presentation was provided by Steve Braun of Northeastern University Libraries during the NISO event, "Assessment Practices and Metrics for the 21st Century," held on Friday, November 16, 2018.
This document provides floor plans and summaries for two AutoCAD drawings: a single-detached two-storey residential building. The ground floor plan and second floor plan illustrate skills like layer management, accurate dimensions, annotations, and adhering to building code requirements. Creating clean 2D plans is an important skill for planning and development. The ability to efficiently use CAD software makes one a more versatile team member than relying on other departments.
The Center for Spatial Research (CSR) is a Russian company that has specialized in geomarketing techniques and solutions since 2003. CSR provides professional geomarketing services and solutions to over 100 B2B and B2G clients in retail, construction, banking, and other industries. CSR's projects utilize techniques such as niche occupying, data accumulation, and simple geomarketing models and tools to provide strategic and operational recommendations. CSR also engages in research and development to improve geomarketing methods and models, and provides geomarketing training programs.
Trends in managing information technology in 2020IJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these are
This document provides an introduction to data visualization. It discusses the importance of data visualization for clearly communicating complex ideas in reports and statements. The document outlines the data visualization process and different types of data and relationships that can be visualized, including quantitative and qualitative data. It also discusses various formats for visualizing data, with the goal of helping readers understand data visualization and how to create interactive visuals and analyze data.
an introduction to service science that provides the basics of: service system thinking, service system dynamics, service system re-design examples, and tries to answer the "why questions" - end notes include the birth of service science, discussion of advanced manufacturing, outsourcing, sustainability, as well as ways to learn more about service science
2021004 jim spohrer alan hartman_retirement v3ISSIP
(1) The document discusses the future of artificial intelligence and service science in a post-pandemic society from a service science perspective. (2) It compares AI, which aims to automate human intelligence, to service science, which studies how systems like businesses and societies can transform and improve lives through cooperation. (3) The document outlines how service science views systems as evolving over time through running existing practices, transforming by adopting new practices, and innovating to create new practices.
The document discusses linking service science with policymaking to enable desirable societal outcomes. It outlines that service science studies value co-creation interactions in service systems and that policies can shape rules and incentives to connect interactions with outcomes. The document also provides background on key concepts in service science like the service-dominant logic and definitions of service systems.
Introduction to statistics and graphical representationAMNA BUTT
This document provides an introduction to statistics, including definitions and types. It discusses descriptive statistics, which deals with summarizing and describing numerical data through tables, graphs, and measures of center. Inferential statistics makes inferences about populations based on samples. The document also covers graphical representations in statistics, such as bar graphs, line graphs, pie charts, pictograms, and histograms, which visually display statistical data.
Running head: DATA VISUALIZATION 1
DATA VISUALIZATION 2
Data Visualization
Student Name
Institution
Course
Instructor
Date
Visualizations are one of the major recent techniques used ni companies and organizations to present information to the individuals. The techniques employ the use of presentations for example graphics such as charts, bars to aid in making the information simple and easy for interpretation and understandable to the targeted groups (Saleh et al .,2015). In the visualization of data, an infographic is one of the major currently used techniques that have shown improved performance in achieving visualization objectives. Infographics achieve data visualizations by digesting the complex information to become easy for the reader to understand. An example of infographics used visualizations is informational infographics
Informational infographics serve the purpose of giving a more detailed explanation of a particular topic. In this Visualization uses a variety of interactive features that aid in making the information more understandable. Some of the interactive features used are the use of colors; color is one of the interactive features that are used in visualizations to attract the interest of the audience and thus it draws one's concentration to the infographic to want to understand the information's portrayed (Silverstein et al., 2015). Brightness is another feature is used in information infographics since it is sensitive to the sight hence make things like bars and charts to be identified with ease. Additionally, the infographic uses features such as different size and shape of the presentations to help in visualizing since they increase chances of passing information to a greater mass of audience. The size of the article makes it more visible from a distance hence being viewed by many. The last interactive feature also used is information infographics is the representation of information by the motion of visuals objects thus captures the attention of individuals.
The Interactive features used in information infographic are suitable in visualizing since they pass information easily and faster over a large number of audiences. When bars and charts are used to present information it is easy to interpret the message. Interactive features are also suitable since they bring fun to the audience and these increases the performance of the infographic to reach many individuals (Yildirim, 2016). However, some interactive features such as a presentation by moving objects could be made suitable by shortening them to save time this will help in reducing the chances of individuals getting fatigued to information presented. Also learning through interactive features brings about relaxation. Lastly; interactive features are suitable for they increase the confidence ...
1) Definition of Data visualization-Representation and prese.docxcuddietheresa
1) Definition of Data visualization-
Representation and presentation of data to facilitate understanding(Kirk, 2019, p. 29)
Data visualization is the representation of data or information in a graph, chart, or other visual format. It communicates relationships of the data with images. This is important because it allows trends and patterns to be more easily seen. With the rise of big data upon us, we need to be able to interpret increasingly larger batches of data. (Import.io, 2019)
The field of data visualization combines both art and data science. While a data visualization can be creative and pleasing to look at, it should also be functional in its visual communication of the data. (Nediger, 2020)
2) Key Components of Data Visualization-
Following are the Key components of Data Visualization,
a) Visual Representation- This will involve making decisions on how you will like to portray the data collected.This can be in the various forms,
Charts - Bar charts, Line charts, Pie charts
Maps
Table - Pivot table
Summarization Bar - Can be used in financial application when you want to see summary of the amount spent in a specific month/year/day.
b) Presentation- Presentation of the data is how do we package up the final product/Data graph.
c) Facilitate Understanding- Making it easy to understand for the audience who will be reading and consuming this data.
3) What techniques do I hope to learn from this course?
I would like to learn as many data visualization tools (Example- Tableau, SAS Business Intelligence, Google Data Studio) as I can which will help me analyze massive data and make data driven decisions to improve my company's business/processes.
Would like to learn some techniques like how can we make a data graph dynamic this will help to automate reporting when the data is refreshed real time.
Reference-
Kirk, A. (2019).
Data visualisation: A handbook for data driven design
. SAGE Publications.
Import.io. (2019, October 28).
What is Data Visualization and Why Is It Important?
Import.io.
https://www.import.io/post/what-is-data-visualization/
Nediger, M. (2020, June 05).
What is Data Visualization?(Definition, Examples, Best Practices)
Nediger.
https://venngage.com/blog/data-visualization/#1
I need to comment on this
.
Social Networking Site Data Analytics Using Game Theory ModelIRJET Journal
This document presents a study that uses game theory to analyze data from social networking sites Facebook and Instagram.
A questionnaire was used to collect data from 100 users on 7 shared characteristics of Facebook and Instagram: chat interface, live videos, private/public accounts, stories, likes/comments, groups, and security. Descriptive statistics and graphs showed trends in the data.
A 7x7 game theory model was created using intercept values from regression analysis of the data. The model was solved to find the optimal strategies for Facebook and Instagram and determine the value of the game. The results provide insights into how game theory can inform decision-making around social media strategies.
RECOMMENDED ELEMENTS OF INFOGRAPHICS IN EDUCATION (PROGRAMMING FOCUSED)ijma
ABSTRACT
This study focused on investigating the elements of infographics in the field of education especially in Programming. It was done by reviewing related literature reviews, interviewing experts in design, content, and the current infographics in programming. The findings showed that based on literature review a good infographic should consist of a good title, suitable graphs/charts/pictures/images, readable text/font, a clear story, reliable data, have an excellent use of color and an appropriate design format. Based on six design experts stated that the position, location, and identification of each element in infographics design to make it clear to the audience. Furthermore, content expert explained some important points of data structure and algorithms. The last one is taken from 6 current infographics which contained 7 elements. This is important to enhance the reader’s understanding of the content of the infographic because it should present information in a clear, concise, and effective manner.
Application of AI in customer relationship managementShashwat Shankar
The document provides an overview of applying artificial intelligence (AI) techniques in customer relationship management (CRM). It first discusses the importance and goals of CRM, including understanding customer behavior to improve acquisition, retention, loyalty and profitability. It then classifies CRM into operational and analytical approaches. The document proposes a classification framework for AI techniques in CRM, including customer identification, attraction, retention and development. It describes common AI models like association, classification, clustering, forecasting and regression. Finally, it discusses using this framework to systematically review how AI can make CRM more effective.
This document discusses the importance of acknowledgement pages in thesis writing. It recommends only including major contributors like advisors, professors, and classmates who significantly helped with research, experiments, or writing. For academics, full names and titles should be used, while only first names are needed for friends to protect identities. The document also provides guidance on listing contributors from academia versus family/friends and how to structure acknowledgement pages.
Who Is Your Business' MVP A DIY Guide to the Most Valuable PersonaseBoost Consulting
This document outlines the key components of developing personas through the 3V methodology. It demonstrates how to organize information from internal interviews, external interviews, and external research into persona reports. The document highlights that persona development is a form of strategic market segmentation that provides essential insights for conversion design and plausible user scenarios. It includes an example persona report created for a mountain biking website to illustrate the process.
- Service science is the study of service systems and value co-creation between entities as they interact and integrate resources.
- A service system is a dynamic configuration of resources including people, technology, organizations, shared information and value propositions connecting internal and external service systems.
- Service science aims to understand and improve service systems and how they scale to create value.
RECOMMENDED ELEMENTS OF INFOGRAPHICS IN EDUCATION (PROGRAMMING FOCUSED) ijma
This study focused on investigating the elements of infographics in the field of education especially in
Programming. It was done by reviewing related literature reviews, interviewing experts in design, content,
and the current infographics in programming. The findings showed that based on literature review a good
infographic should consist of a good title, suitable graphs/charts/pictures/images, readable text/font, a
clear story, reliable data, have an excellent use of color and an appropriate design format. Based on six
design experts stated that the position, location, and identification of each element in infographics design
to make it clear to the audience. Furthermore, content expert explained some important points of data
structure and algorithms. The last one is taken from 6 current infographics which contained 7 elements.
This is important to enhance the reader’s understanding of the content of the infographic because it should
present information in a clear, concise, and effective manner.
This document summarizes a presentation by Jim Spohrer from IBM on open technology, innovation, and service system evolution. Some key points:
- Spohrer discusses the multidisciplinary nature of services and the need for service scientists to study increasingly service-dominated economies and societies.
- He outlines the evolution of complex systems from the physical to sociotechnical, and how disciplines have evolved to study and design increasingly complex systems, from physics to computer science to service science.
- Spohrer summarizes the development of service science and service-dominant logic as frameworks to study value co-creation within service systems, which are dynamic configurations of resources including people, organizations, information, and technology.
2021020 jim spohrer ai for_good_conference future_of_ai v4ISSIP
Jim Spohrer serves on the Board of Directors of ISSIP and previously worked at IBM, where he directed various AI and service science initiatives. He discusses the future of AI, predicting that compute costs will decrease by a factor of 1000 every 20 years, enabling digital workers to become more capable and affordable. He presents a timeline and framework for benchmarking AI progress on open leaderboards to achieve human-level performance in various tasks over time. The best way to predict the future, he says, is to inspire students to build a better future.
The document discusses the history and future of AI at IBM, from its early work with Nathan Rochester on physical symbol systems to its current focus on open source technologies and cognitive systems through its Center for Open Source Data and AI Technologies (CODAIT). It also covers IBM's view of service science as the study of evolving service system entities, their capabilities, constraints, rights, and responsibilities. The document provides context around IBM's past, present and future work in AI and how it relates to fields like computer science, chemistry, biology and service science.
TS4-3: Takumi Sato from Nagoya Institute of TechnologyJawad Haqbeen
This paper proposes a method to fully automate the classification of open-ended questionnaires using word-based clustering and distributed representations. The method was tested on 1285 opinions from a questionnaire about childcare conducted in Kasugai-shi, Japan. Labels were generated and opinions were clustered into 23 groups. The labels and groupings were evaluated by experts and general evaluators and found to have high accuracy, with 81.5% rated highly. Experts felt the automated method could greatly reduce classification costs compared to manual methods and produced practical groupings and labels for the local government's needs. The results demonstrate the proposed approach is both accurate and practical for classifying open-ended opinions from questionnaires.
Big data characteristics, value chain and challengesMusfiqur Rahman
Abstract—Recently the world is experiencing an deluge of
data from different domains such as telecom, healthcare
and supply chain systems. This growth of data has led to
an explosion, coining the term Big Data. In addition to the
growth in volume, Big Data also exhibits other unique
characteristics, such as velocity and variety. This large
volume, rapidly increasing and verities of data is becoming
the key basis of completion, underpinning new waves of
productivity growth, innovation and customer surplus. Big
Data is about to offer tremendous insight to the
organizations, but the traditional data analysis
architecture is not capable to handle Big Data. Therefore,
it calls for a sophisticated value chain and proper analytics
to unearth the opportunity it holds. This research
identifies the characteristics of Big Data and presents a
sophisticated Big Data value chain as finding of this
research. It also describes the typical challenges of Big
Data, which are required to be solved. As a part of this
research twenty experts from different industries and
academies of Finland were interviewed.
This document provides an introduction to business mathematics and statistics. It defines statistics and discusses its key characteristics. Statistics is the study of numerical data in relation to each other. It discusses the scope and applications of statistics in various fields like business, economics, physical sciences, research, and management. The document also covers classification and tabulation of data, different types of diagrams and graphs used to represent statistical data, and their various forms.
This document outlines a proposed study to model regional economic growth using a multi-agent system (MAS) approach integrated with geographical information systems (GIS). The study aims to analyze complexity in regional growth, develop a model of growth patterns, and identify how economic factors contribute to growth. It will examine firm demography and apply GIS and MAS technologies to the urban planning context of the Klang Valley region in Malaysia. Literature reviews on related topics have begun and data requirements have been identified. The expected findings are to create a growth model to help understand land use patterns and aid decision making.
This document provides an overview of a presentation on the future of AI given by Jim Spohrer from IBM. The presentation discusses IBM's past work in AI, current focus on open source technologies through CODAT, and vision for the future which includes solving problems related to trust, identity, and resilience as AI capabilities continue to advance. It also discusses different types of systems like information, physical symbol, service, and cognitive systems.
Graphs represent data in an engaging manner and make c.docxshericehewat
Graphs represent data in an engaging manner and make comparisons and analyses easier. For example, a graph depicting the number of crimes committed each year over a decade is easier to comprehend visually than reading the numerical values for each year. Before creating a graph, however, it is important to choose one that appropriately represents the data. A histogram, rather than a pie chart, is appropriate for depicting the age groups (e.g., 15–24, 25–34) of murder victims in a city. Histograms are designed to be used with variables that are categorized, but pie charts plot each value. Therefore, it would be easier to read a histogram showing bars for age groups of murder victims than a pie chart in which every single age would have to be plotted. In the past, creating graphs was cumbersome and time consuming, but present-day software programs such as Microsoft Word and Excel provide tutorials that walk you through the process. With knowledge of these software programs, you can create customized charts and figures to represent your research data in visually interesting ways. In this Assignment, you create at least two different graphs in Excel or Word that can be used to illustrate hypothetical data related to six incidents of crime.
· Create at least two different graphs in Excel or Word using the data provided in the table below:
Type of Crime
Offender’s Age
(Years)
Offender’s Gender
Time of the Incident
Theft
22
Male
Early morning
Possession of drugs
21
Female
Late evening
Theft
19
Male
Late evening
Theft
33
Female
Afternoon
Possession of drugs
47
Female
Morning
Possession of drugs
17
Male
Early morning
· Briefly describe the data represented in the graphs and/or charts you created.
· Explain why the graphs and/or charts you created best represent the data compared to other options. Be specific.
Submit the graphs you created in a document that is separate from your written Assignment.
Bachman, R. D., & Schutt, R. K. (2019). The practice of research in criminology and criminal justice (7th ed.). Thousand Oaks, CA: SAGE Publications.
· Chapter 4, “Conceptualization and Measurement” (pp. 86–116)
The Practice of Research in Criminology and Criminal Justice, 7th Edition by Bachman, R. D. & Schutt, R. K. Copyright 2019 by SAGE Publications, Inc. Reprinted by permission of SAGE Publications, Inc via the Copyright Clearance Center.
Bachman, R. D., & Schutt, R. K. (2019). The practice of research in criminology and criminal justice (7th ed.). Thousand Oaks, CA: SAGE Publications.
· Chapter 14, “Analyzing Quantitative Data” (pp. 404–415 and 426–444)
The Practice of Research in Criminology and Criminal Justice, 7th Edition by Bachman, R. D. & Schutt, R. K. Copyright 2019 by SAGE Publications, Inc. Reprinted by permission of SAGE Publications, Inc via the Copyright Clearance Center.
Trochim, W. M. K. (2006). Levels of measurement. In Research methods knowledge base. Retrieved from http://www.socialresearchmethods.net/kb/measlevl.php
Walden Univer ...
5 Tips for Creating Standard Financial ReportsEasyReports
Well-crafted financial reports serve as vital tools for decision-making and transparency within an organization. By following the undermentioned tips, you can create standardized financial reports that effectively communicate your company's financial health and performance to stakeholders.
Introduction to statistics and graphical representationAMNA BUTT
This document provides an introduction to statistics, including definitions and types. It discusses descriptive statistics, which deals with summarizing and describing numerical data through tables, graphs, and measures of center. Inferential statistics makes inferences about populations based on samples. The document also covers graphical representations in statistics, such as bar graphs, line graphs, pie charts, pictograms, and histograms, which visually display statistical data.
Running head: DATA VISUALIZATION 1
DATA VISUALIZATION 2
Data Visualization
Student Name
Institution
Course
Instructor
Date
Visualizations are one of the major recent techniques used ni companies and organizations to present information to the individuals. The techniques employ the use of presentations for example graphics such as charts, bars to aid in making the information simple and easy for interpretation and understandable to the targeted groups (Saleh et al .,2015). In the visualization of data, an infographic is one of the major currently used techniques that have shown improved performance in achieving visualization objectives. Infographics achieve data visualizations by digesting the complex information to become easy for the reader to understand. An example of infographics used visualizations is informational infographics
Informational infographics serve the purpose of giving a more detailed explanation of a particular topic. In this Visualization uses a variety of interactive features that aid in making the information more understandable. Some of the interactive features used are the use of colors; color is one of the interactive features that are used in visualizations to attract the interest of the audience and thus it draws one's concentration to the infographic to want to understand the information's portrayed (Silverstein et al., 2015). Brightness is another feature is used in information infographics since it is sensitive to the sight hence make things like bars and charts to be identified with ease. Additionally, the infographic uses features such as different size and shape of the presentations to help in visualizing since they increase chances of passing information to a greater mass of audience. The size of the article makes it more visible from a distance hence being viewed by many. The last interactive feature also used is information infographics is the representation of information by the motion of visuals objects thus captures the attention of individuals.
The Interactive features used in information infographic are suitable in visualizing since they pass information easily and faster over a large number of audiences. When bars and charts are used to present information it is easy to interpret the message. Interactive features are also suitable since they bring fun to the audience and these increases the performance of the infographic to reach many individuals (Yildirim, 2016). However, some interactive features such as a presentation by moving objects could be made suitable by shortening them to save time this will help in reducing the chances of individuals getting fatigued to information presented. Also learning through interactive features brings about relaxation. Lastly; interactive features are suitable for they increase the confidence ...
1) Definition of Data visualization-Representation and prese.docxcuddietheresa
1) Definition of Data visualization-
Representation and presentation of data to facilitate understanding(Kirk, 2019, p. 29)
Data visualization is the representation of data or information in a graph, chart, or other visual format. It communicates relationships of the data with images. This is important because it allows trends and patterns to be more easily seen. With the rise of big data upon us, we need to be able to interpret increasingly larger batches of data. (Import.io, 2019)
The field of data visualization combines both art and data science. While a data visualization can be creative and pleasing to look at, it should also be functional in its visual communication of the data. (Nediger, 2020)
2) Key Components of Data Visualization-
Following are the Key components of Data Visualization,
a) Visual Representation- This will involve making decisions on how you will like to portray the data collected.This can be in the various forms,
Charts - Bar charts, Line charts, Pie charts
Maps
Table - Pivot table
Summarization Bar - Can be used in financial application when you want to see summary of the amount spent in a specific month/year/day.
b) Presentation- Presentation of the data is how do we package up the final product/Data graph.
c) Facilitate Understanding- Making it easy to understand for the audience who will be reading and consuming this data.
3) What techniques do I hope to learn from this course?
I would like to learn as many data visualization tools (Example- Tableau, SAS Business Intelligence, Google Data Studio) as I can which will help me analyze massive data and make data driven decisions to improve my company's business/processes.
Would like to learn some techniques like how can we make a data graph dynamic this will help to automate reporting when the data is refreshed real time.
Reference-
Kirk, A. (2019).
Data visualisation: A handbook for data driven design
. SAGE Publications.
Import.io. (2019, October 28).
What is Data Visualization and Why Is It Important?
Import.io.
https://www.import.io/post/what-is-data-visualization/
Nediger, M. (2020, June 05).
What is Data Visualization?(Definition, Examples, Best Practices)
Nediger.
https://venngage.com/blog/data-visualization/#1
I need to comment on this
.
Social Networking Site Data Analytics Using Game Theory ModelIRJET Journal
This document presents a study that uses game theory to analyze data from social networking sites Facebook and Instagram.
A questionnaire was used to collect data from 100 users on 7 shared characteristics of Facebook and Instagram: chat interface, live videos, private/public accounts, stories, likes/comments, groups, and security. Descriptive statistics and graphs showed trends in the data.
A 7x7 game theory model was created using intercept values from regression analysis of the data. The model was solved to find the optimal strategies for Facebook and Instagram and determine the value of the game. The results provide insights into how game theory can inform decision-making around social media strategies.
RECOMMENDED ELEMENTS OF INFOGRAPHICS IN EDUCATION (PROGRAMMING FOCUSED)ijma
ABSTRACT
This study focused on investigating the elements of infographics in the field of education especially in Programming. It was done by reviewing related literature reviews, interviewing experts in design, content, and the current infographics in programming. The findings showed that based on literature review a good infographic should consist of a good title, suitable graphs/charts/pictures/images, readable text/font, a clear story, reliable data, have an excellent use of color and an appropriate design format. Based on six design experts stated that the position, location, and identification of each element in infographics design to make it clear to the audience. Furthermore, content expert explained some important points of data structure and algorithms. The last one is taken from 6 current infographics which contained 7 elements. This is important to enhance the reader’s understanding of the content of the infographic because it should present information in a clear, concise, and effective manner.
Application of AI in customer relationship managementShashwat Shankar
The document provides an overview of applying artificial intelligence (AI) techniques in customer relationship management (CRM). It first discusses the importance and goals of CRM, including understanding customer behavior to improve acquisition, retention, loyalty and profitability. It then classifies CRM into operational and analytical approaches. The document proposes a classification framework for AI techniques in CRM, including customer identification, attraction, retention and development. It describes common AI models like association, classification, clustering, forecasting and regression. Finally, it discusses using this framework to systematically review how AI can make CRM more effective.
This document discusses the importance of acknowledgement pages in thesis writing. It recommends only including major contributors like advisors, professors, and classmates who significantly helped with research, experiments, or writing. For academics, full names and titles should be used, while only first names are needed for friends to protect identities. The document also provides guidance on listing contributors from academia versus family/friends and how to structure acknowledgement pages.
Who Is Your Business' MVP A DIY Guide to the Most Valuable PersonaseBoost Consulting
This document outlines the key components of developing personas through the 3V methodology. It demonstrates how to organize information from internal interviews, external interviews, and external research into persona reports. The document highlights that persona development is a form of strategic market segmentation that provides essential insights for conversion design and plausible user scenarios. It includes an example persona report created for a mountain biking website to illustrate the process.
- Service science is the study of service systems and value co-creation between entities as they interact and integrate resources.
- A service system is a dynamic configuration of resources including people, technology, organizations, shared information and value propositions connecting internal and external service systems.
- Service science aims to understand and improve service systems and how they scale to create value.
RECOMMENDED ELEMENTS OF INFOGRAPHICS IN EDUCATION (PROGRAMMING FOCUSED) ijma
This study focused on investigating the elements of infographics in the field of education especially in
Programming. It was done by reviewing related literature reviews, interviewing experts in design, content,
and the current infographics in programming. The findings showed that based on literature review a good
infographic should consist of a good title, suitable graphs/charts/pictures/images, readable text/font, a
clear story, reliable data, have an excellent use of color and an appropriate design format. Based on six
design experts stated that the position, location, and identification of each element in infographics design
to make it clear to the audience. Furthermore, content expert explained some important points of data
structure and algorithms. The last one is taken from 6 current infographics which contained 7 elements.
This is important to enhance the reader’s understanding of the content of the infographic because it should
present information in a clear, concise, and effective manner.
This document summarizes a presentation by Jim Spohrer from IBM on open technology, innovation, and service system evolution. Some key points:
- Spohrer discusses the multidisciplinary nature of services and the need for service scientists to study increasingly service-dominated economies and societies.
- He outlines the evolution of complex systems from the physical to sociotechnical, and how disciplines have evolved to study and design increasingly complex systems, from physics to computer science to service science.
- Spohrer summarizes the development of service science and service-dominant logic as frameworks to study value co-creation within service systems, which are dynamic configurations of resources including people, organizations, information, and technology.
2021020 jim spohrer ai for_good_conference future_of_ai v4ISSIP
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TS4-3: Takumi Sato from Nagoya Institute of TechnologyJawad Haqbeen
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Data is about to offer tremendous insight to the
organizations, but the traditional data analysis
architecture is not capable to handle Big Data. Therefore,
it calls for a sophisticated value chain and proper analytics
to unearth the opportunity it holds. This research
identifies the characteristics of Big Data and presents a
sophisticated Big Data value chain as finding of this
research. It also describes the typical challenges of Big
Data, which are required to be solved. As a part of this
research twenty experts from different industries and
academies of Finland were interviewed.
This document provides an introduction to business mathematics and statistics. It defines statistics and discusses its key characteristics. Statistics is the study of numerical data in relation to each other. It discusses the scope and applications of statistics in various fields like business, economics, physical sciences, research, and management. The document also covers classification and tabulation of data, different types of diagrams and graphs used to represent statistical data, and their various forms.
This document outlines a proposed study to model regional economic growth using a multi-agent system (MAS) approach integrated with geographical information systems (GIS). The study aims to analyze complexity in regional growth, develop a model of growth patterns, and identify how economic factors contribute to growth. It will examine firm demography and apply GIS and MAS technologies to the urban planning context of the Klang Valley region in Malaysia. Literature reviews on related topics have begun and data requirements have been identified. The expected findings are to create a growth model to help understand land use patterns and aid decision making.
This document provides an overview of a presentation on the future of AI given by Jim Spohrer from IBM. The presentation discusses IBM's past work in AI, current focus on open source technologies through CODAT, and vision for the future which includes solving problems related to trust, identity, and resilience as AI capabilities continue to advance. It also discusses different types of systems like information, physical symbol, service, and cognitive systems.
Graphs represent data in an engaging manner and make c.docxshericehewat
Graphs represent data in an engaging manner and make comparisons and analyses easier. For example, a graph depicting the number of crimes committed each year over a decade is easier to comprehend visually than reading the numerical values for each year. Before creating a graph, however, it is important to choose one that appropriately represents the data. A histogram, rather than a pie chart, is appropriate for depicting the age groups (e.g., 15–24, 25–34) of murder victims in a city. Histograms are designed to be used with variables that are categorized, but pie charts plot each value. Therefore, it would be easier to read a histogram showing bars for age groups of murder victims than a pie chart in which every single age would have to be plotted. In the past, creating graphs was cumbersome and time consuming, but present-day software programs such as Microsoft Word and Excel provide tutorials that walk you through the process. With knowledge of these software programs, you can create customized charts and figures to represent your research data in visually interesting ways. In this Assignment, you create at least two different graphs in Excel or Word that can be used to illustrate hypothetical data related to six incidents of crime.
· Create at least two different graphs in Excel or Word using the data provided in the table below:
Type of Crime
Offender’s Age
(Years)
Offender’s Gender
Time of the Incident
Theft
22
Male
Early morning
Possession of drugs
21
Female
Late evening
Theft
19
Male
Late evening
Theft
33
Female
Afternoon
Possession of drugs
47
Female
Morning
Possession of drugs
17
Male
Early morning
· Briefly describe the data represented in the graphs and/or charts you created.
· Explain why the graphs and/or charts you created best represent the data compared to other options. Be specific.
Submit the graphs you created in a document that is separate from your written Assignment.
Bachman, R. D., & Schutt, R. K. (2019). The practice of research in criminology and criminal justice (7th ed.). Thousand Oaks, CA: SAGE Publications.
· Chapter 4, “Conceptualization and Measurement” (pp. 86–116)
The Practice of Research in Criminology and Criminal Justice, 7th Edition by Bachman, R. D. & Schutt, R. K. Copyright 2019 by SAGE Publications, Inc. Reprinted by permission of SAGE Publications, Inc via the Copyright Clearance Center.
Bachman, R. D., & Schutt, R. K. (2019). The practice of research in criminology and criminal justice (7th ed.). Thousand Oaks, CA: SAGE Publications.
· Chapter 14, “Analyzing Quantitative Data” (pp. 404–415 and 426–444)
The Practice of Research in Criminology and Criminal Justice, 7th Edition by Bachman, R. D. & Schutt, R. K. Copyright 2019 by SAGE Publications, Inc. Reprinted by permission of SAGE Publications, Inc via the Copyright Clearance Center.
Trochim, W. M. K. (2006). Levels of measurement. In Research methods knowledge base. Retrieved from http://www.socialresearchmethods.net/kb/measlevl.php
Walden Univer ...
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Three chapter 3 graphical learningkit
1. 31 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
CHAPTER
3
[Graphical Presentation]
Subtopics:-
[3.1] [Organizing and Graphing Qualitative Data]
[3.2] [Organizing and Graphing Grouped Data]
[Learning Objectives]
[Recognizing Charts For Quantitative Data]
[Understanding The Principles Of Proper
Graphical Data Presentation]
[Histogram]
[Polygon]
[Cumulative Polygon]
2. 32 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.1] [Organizing and Graphing Qualitative Data]
[A graphical representation is a visual display of data and statistical1 results. It is more
often and effective than presenting data in tabular form. There are different types of
graphical representation which is used depends on the nature of the data. Grade One
Company in the future may be probably to be recommended to provide measurement
analysis as shown in the X2 statistics ((F Lai, M Griffin, BJ Babin) (2009), Journal Of Business
Research, Elsiever, Vol 62, Issue 10, October 2009, Pages 980-986, Cited by 593)].
[3.1.1] [Understanding Of Graphic Integrated Statistical Packages Communication]
[The understanding of graphic integrated statistical packages communication using the
typography graphic communication is one of the conveyance of ideas information
culture2 which is associated with visual communication through two dimensional images
inclusive corporate context in relations with the company policy stress sensitivity was a
latest variables. The “Intercultural Sensitivity Development Model (IDSIM3)” employed
parametric statistics to generate the parametric assumption that could be significant
towards the change of attractive packaging of :-]
[Colour4 Images]
[Electronic56 resources]
[Illustration]
[Graphic Design]
[Drawing]
[Signboards]
[Attributes7]
[While graphic elements are a strong visual means of, overusing them adds visual clutter
and reduces the space available on a surface. They should be used sparingly. A design
trend in Microsoft Windows is a simpler, cleaner appearance by eliminating unnecessary
1 G Gay, Education and Urban Society Journal (1993)”Building Cultural Bridges: A Bold Proposal For Tender
Education”; RM Paige, Applied Cross Cultural Psychology (1990), Cited by 314 ; F Trompenaars, C Hampden
Turner (2011) “Riding The Waves Of Culture : Understanding Diversity In Global Business”; Cited By 10,345; J R
Betancourt (2003), Academic Medicine Journals “Cross Cultural Medical Education : Conceptual
Approaches and Frameworks For Evaluation, Cited by 481.
2 JJ Dahlggard, S M Dahlgaard Park – The TQM Imagine (2006) Emerald Sight.com Journal, “Lean Production,
Six Sigma Quality, TQM and Company Culture”.
3 MJ Bennett (1998) “Developmental Model Of Intercultural Sensitivity”, Wiley Online Library.
4 F Lai, M Griffin, BJ Babin, Journal Of Business Research (2009), Elsevier, Vol 62, Issue 10, October (2009),
Pages 980-986.
5 L Wilkinson (1992) “SYSTAT For Windows Statistics, Graphics, Data, Getting Started, Versions 5”, Cited By
9130; TC Ozawa, S J Kang, Journal Of Applied Crystallography (2004), “Balls & Sticks Easy To Use Structure
Visualization and Animation Program”.
6ST Kerr, Information Design Journal, (1984), “Learning To Use Electronic Test : An Agenda For Research Or
Typography, Graphics and Interpersonal Navigation”, Cited By 18.
7 Hue, White, Alex “The Elements of Graphic Design” New York NY Press” pp 81-105 ISBN01781-58115-762-8.
3. 33 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
graphics and lines. For example, according to ((R E Horn) (1999, )Information Design
Journal “Information Design Emergence Of A New Profession : Typography Graphic
Presentation”, Cited by 224, “When I was a CEO of an information design consulting company I
often asked documentation and training IT Information design consulting company often asked
documentation and training. There are business graphics and statistical packages advertising that
the charts words and images are tightly integrated in most business”) ideology8 as a new screen
design which may hypertext to others virtually became extinct handwriting styles for business
advocate.]
Figure 3.1 : Typography and Mathematics Relationships Towards New Trend Presentation
8 C Kostelnick (2004) Defining Visual Rhetorics Journal; “Melting Pot Ideology, Modernist Aesthetics And The
Emergence Of Graphical Conventions : The Statistical Atlases Of The United States (1874-1925).
4. 34 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
3.2 [Organizing and Graphing Grouped Data]
Figure 3.2 : Integrative Statistical Communication Data9
[In order to organize the graphical illustration, there is a need to establish a cross cultural
perspective from universities, antecedents and the statistical quality may control the
consequences of positive (+) or negative (-) relationship.]
[Moreover, without undertaking a cross cultural study analysing the surrounding society
relating to (PEST) political, environment, social and technology impacts with quality10
values business relationship may interrelate the organizational business performance
relationships.]
[Although multiracial ethnic background, with the availability of the graphical integrative
statistical with e-commerce technology settings, it is shown another alternative defensive
strategies. While, the educational institutions are very susceptible to the opinions of
business and industry.]
[The academic medicine journal refers to (J R Betancourt, (2003) “Cross Cultural Medical
Education: Conceptual Approaches and Frameworks For Evaluation”, The Hispanic
education using statistical portrait11.]
[Apart of more profitable, it is true that this integrative statistical packages creates prompt
services can be achievable through the maximization of cross cultural12 method analysis
9 www.google.integrativestatisticalcommunicationdata.com
10 S R Segarra Moliner, MA Moliner Tena, (2013) Marketing Emerald Insight Research Gate net Journal,
“Relationship Quality In Business To Business: A Cross Cultural Perspective From Universities”.
11 G Gay (1993) Education and Urban Society Journal, “Building Cultural Bridges : A Bold Proposal For
Teacher Education”.
5. 35 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
effects especially perceived from the service quality dimensions on internal stakeholders
(students, employees, lecturer, Top Management) or (customers, disabled, public, VIP)
external stakeholders’ satisfaction that may establish the cross cultural psychological
educational improvement13 achievement strategies.]
3.2.1 [ Bar, Histogram, Line, Pie Graphical Chart]
[A graph made of bars whose heights represent the frequencies of respective categories
is called a bar graph. The bar graphs and histograms have been used formulation for
graphical presentation for numerous hundreds of years.]
Table 3.4: The Pie Is Divided Into Different Portions That Represent the Percentages of the
Population or Sample Belonging To Different Categories
[As we know, a circle contains 360 degrees. To construct a pie chart, we multiply 360 by
the relative frequency for each category to obtain the degree measure or size of the
angle for the corresponding category.]
12 N Kassim, N Asiah Abdullah, (2010), Asia Pacific Journal Of Marketing, “The Effect Of Perceived Service
Quality Dimensions On Customer Satisfaction, Trust and Loyalty In e-Commerce Settings : A Cross Cultural
Analysis”, Cited By 418.
13 N Kassim, N Asiah Abdullah, (2010), Asia Pacific Journal Of Marketing emerald sight com, “The Effect Of
Perceived Service Quality Dimensions On Customer Satisfaction, Trust and Loyalty In e-Commerce Settings :
A Cross Cultural Analysis; F Lai, M Griffin, B J Babin, (2009), Journal Of Business Research, Elsiever, Vol 62,
Issue 10, October 2009, Pages 980-986; G Gay (1993), Education and Urban Society Journal sagepub.com,
“Building Cultural Bridges: A Bold Proposal For Teacher Education, Cited by 314; RM Paige (1990) Applied
Cross Cultural Psychology, “Cross Cultural Psychological Perspectives”; D Valentine, RS Cheney,(2001)
Business Communication Journal sagepub.com, “Intercultural Business Communication, International
Students and Experiential Learning; F Trompenaars, C Hampden Turner (2011), ”Riding The Waves Of Culture :
Understanding Diversity In Global Business.”
Formula to find degree of each
category:
Percentage = (Frequency / Total
Frequency) x 100
Degree =
6. 36 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.2] [Frequency Polygon]
[A polygon is another device that can be used to present quantitative data in graphic
form. This is the same as marking the midpoint at the top of each bar in a histogram. The
resulting line graph is called a frequency polygon or simply a polygon. In a frequency
polygon, the class midpoints are connected with a line segment.]
Table 3.5: The Resulting Line Graph Representing the Frequency Polygon
7. 37 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
Rental Rates Number Of Apartments Midpoints
350-379 3 364.5
380-409 8 394.5
410-439 10 424.5
440-469 13 454.5
470-499 33 484.5
500-529 40 5144.5
530-559 35 544.5
560-589 30 574.5
590-619 16 604.5
620-649 12 634.5
Total ∑f=200
0
5
10
15
364.5 394.5 424.5 454.5
Frequency
Midpoint
Table 3.6 : The Resulting Line Point Graph Chart Representing The Frequency
Polygon
Number of
apartment
MONTHLY APARTMENT RENTAL RATES
0
5
10
15
20
25
30
35
40
45
MIDPOINT
FREQUENCY
8. 38 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[While according to William Playfair and Karl Pearson are commonly cited of the bar
graph (Spence (2005), Spence, I (2005), “No Humble Pie: The Origins and Usage Of A
Statistical Chart, “Journal of Educational and Behavioral Statistics, 30, 353-368, SAGE”.
According to Naomi Robbins January 4, 2012, Forbes Contributions explains that a
histogram is not a bar chart. Histograms are used to show distribution of variables. Bar
chart is used to compare variables. According to Naomi Robbins January 4, 2012, Forbes
Contributions explains that a histogram is not a bar chart. Histograms are used to show
distribution of variables. Bar chart is used to compare variables.]
Figure 3.1 : A Histogram Having The Distribution Of
Times Visitors
Figure 3.2 : A Bar Chart Comparing The
Median Times Visitors
9. 39 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[A chart, also called a graph, is a graphical
representation of data, in which "the data is
represented by symbols, such as bars in a bar
chart, lines in a line chart, or slices in a pie
chart". A circle divided into portions that
represent the relative frequencies or
percentages of a population or a sample
belonging to different categories is called a
pie chart.
Table 3.3: Different Categories of Pie Charts
Organizing and
graphing
qualitative
data
Bar charts
Organizing and
graphing
qualitative data
Pie chart
Organizing and
graphing qualitative
data
Histogram charts.
Portray a frequency
distribution in a
histogram, frequency
polygon and
cumulative frequency
polygon
Develop
Charts
For
qualitative
quantitative
data
Figure 3.5 : Examples Of Graphical Presentation For Information, Education, Business
Documentation In Association Of Statistical Packages Advertising The Words and Images Are
Tightly Integrated In Most Business, Graphic Sounds Elements and Education14 As A Cross Selling.
14S Yurtkuran (2013) “Use Of The Semantics Of Typography In Architectural Design Education”.
10. 40 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.3] [Organizing Graphical Illustration Applying Basic Terms Methodology Variables]
[3.2.3.1] [Basic Terms]
[On completion of this course, students should be able to differentiate quantitative and
qualitative data as well as the bigger picture of statistics which related to the below
mentioned examples:-]
[3.2.3.2] [Quantitative Variables Research Methodology Terms]
[Quantitative research is the systematic empirical investigation of observable phenomena
via inferential statistical techniques application. This is a systematic empirical investigation
that uses mathematical formula or computational techniques. The main objective of
quantitative research is to develop graphical presentation by employing some
phenomena having a significant probability related values of :-]
1. Research Problems Logical Reasoning Selection On The Research
Topic or Title
2. Research Objectives Logical Reasoning Selection On The Research
Topic or Title
3. Research Hypothesis Introducing The Research Subjects or Title
11. 41 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
4. Research Literature Collection Of Journal Theories Application On
Validating The Statistical Concept Data
5. Research Methodology Application On Mathematical Models
[Quantitative data can be classified into categories or classes. They can best be
presented in the form of Frequency distribution, bar chart, pie chart and contingency
table. ]
[3.3.3.1b] [Qualitative Variable Research Methodology Terms]
[According to Wikipedia, explained that qualitative research is applying some descriptive
statistics. Technique to obtain more valuable information that can be explained uses
various academic disciplines Including psychological sense, emotional intelligence,
observational consumers’ experiences. Examination in the fields of sociology, social
sciences and pure statistical science method example of:-]
A. [Research Question Inquiry that may employ a different academic discipline]
B. [In depth Knowledge, interview, and understanding technological graphic
presentation skills and Public Speaking Skills Through Mini Research
Conference
C. Assessment by Top Management]
D. [Knowledge of business research and statistics mathematical tools]
[Provide a working knowledge of the mathematical tools, language,
and thought processes used by statisticians.]
[Provide a lasting security of their ability to discuss comfortably any
simple statistical task in the normal course of their work.]
[Recognize the relevance and importance of statistical methods that
may be applied to (PEST) Political, Environment, Social and
Technological as well as for economics, mathematical, psychology,
business and health science.]
[Choose and apply appropriate graphical and numerical tools for
organizing, describing, and exploring data.]
[Adopting new body knowledge and confidence accuracy to make
an effective and efficient decision analysis presentation especially
under such condition of imperfect information analysis and uncertainty
business performance.]
12. 42 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.3.3] [Research Methodology Measurement Based On Categorical Data Level
Application on Graphical Illustration Integrative Statistical Excel Microsoft 2007
Communication Data]
[There are two types of categorical data which illustrates the business research statistics
methodology as follows: -]
[3.4.1] [Nominal Categorical Data]
[3.4.2] [Ordinal Categorical Data]
[3.2.3.3a] [Nominal Data Level]
[The nominal level data can be categorical data that lack an ordering scheme.]
[3.2.3.3b] [Ordinal Data Level]
[The ordinal level data are categorical data that lack an ordering scheme; ordinal level
data are which having an ordering scheme whether one value is better or higher than
another value.]
13. 43 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4] [Business Research Statistical Measurement Based On Population Sampling]
[The Chapter One complete report is requiring the researchers or statistics students to
explain the necessary details as in the Table 1, what is their title or subject, objectives,
problem statement that attract their attention to explore further on their case study
business research statistics to determine their quality analytical work which carries almost
5% - 20% for their carry marks grading assessment.]
[3.2.4.1] [Population Data Sampling]
Table 3.7: Example of Business Research Statistics Variables: Population Data Sampling
[Population is needed to be recognized by the researcher which can be unbiased and
can be generalized result in a larger population. On the other hand, statistics can be
reliable information if inquires deeply into specific experiences with the intention of
describing and exploring meaning of the research area describing about the whole
population through descriptive statistics text, narrative visual aid data or by developing
awareness theme to that particular set of participants or population. Another hand, if it
uses the research questionnaires design application on the quantitative data variables
which must be displayed in the form of :
Dependent Variables Data
Independent Variables Data
Numerical Values Data
Inferential Statistics Techniques
Graphical Data Percentages Figures Data
14. 44 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[Table 2 refers to page 26 explains the example of business research statistics variables in
association of investigating and selecting WHO, WHAT, WHERE, WHEN and HOW the
population can be a complete collection of people which can analyze their
demographic profile and others usage statistical techniques measurement:-
Age
Elements
Job
Characteristics
Objects
Measurements
[3.2.4.2] [Sample Population Act As Data Sampling]
[In statistics and quantitative research methodology, a data sample is a part of the data
collection that explains WHO, WHAT, WHERE, WHEN all about your population that we are
interested in to investigate which defined its statistical procedure. The elements of a
sample are known as sample points or sampling units or observations. The sample usually
represents a subset of manageable size. Samples are collected and statistics are
calculated from the samples which coming either from descriptive data or inferential
data interrelated with the sample to the whole populations.]
[There are two basic ways to gather data: either through experiment or observational
studies. In an experiment, we apply s treatment and measure its effect. In an
observational study, we simply observe and record data. We select our samples using
probability sampling. There are different types of sampling inclusive:-]
a. [Random Sampling]
b. [Systematic Sampling]
c. [Stratified Sampling]
d. [Cluster Sampling]
e. [Convenience Sampling]
15. 45 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4.3] [Research Objectives]
[The Chapter One is requiring researcher to illustrate their understanding on what appears
on their brain cognitive systems that probably create the following examples of research
objectives:-]
[To study the average weight of newborn baby measurement inclusive statistical
founder responses in New Zealand for year 2012]
[To identify the members and record data after asking their opinions]
[In case study on business research statistical packages will be useful especially
integrating it with an experiment for applied educational knowledge research. This may
cater a sound academic and quality leadership among the researchers and BDM111
statistics for the entire Diploma until Professional level students. It caters a treatment and
measures for testifying their knowledge and cognitive skills of effective and efficient
communication effects performance. Any observational study or experiment in which the
sample is not representative of the population may produce poor data and unreliable
results. The selection of a sample is very important step in a statistical project. This case
study also to visualize the students’ understanding on how to employ the probability
sampling in choosing their sample by applying it with the technology as well as Microsoft
Excel and T1-83 to randomly generate numbers in the computer software packages. The
other sampling is a systematic sampling. This may have a list of numbers of sample such as
customers at a restaurant every day for an entire year and selected every 21st entry; the
data need to be selected on the same day of the week.]
16. 46 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4.4] [Research Methodology Measurement Based On Variables]
[This Chapter Three display the need of Research Methodology for data findings report
which are requiring the researchers or Business Research Statistic BDM111 to be more
capable to understand theoretically and producing the statistic data by adopting the
recognition of research variables as an important valuable product opportunities
motivation element trend for Cosmopoint College achievement for educational
knowledge application.]
[3.2.4] [Research Question 1]
[Which of the following statements are descriptive and which statements make an
inference?]
[3.2.4.1] [Research Findings Answering the Research Question 1 tally with the
research objectives 1(one)]
[In the last four semesters that the instructor taught intermediate algebra, an average
of 15 people passed the class. Answer 1: This statement is descriptive, because we
can verify that the average for these four semesters is 15.]
[3.2.4.2] [Research Question 2:]
[What is descriptive and which statements make an inference statistics data?]
[3.2.4.2a] [Research Findings Answering the Research Questions 2 tally with the
research objectives 2 (two)]
[The instructor will never pass more than 20 people in an intermediate algebra class.
Answer 2: This statement is an inference; it makes a prediction based on the fact that the
instructor did not pass the course in these four semesters.]
[3.2.4.3] [Research Question 3]
[How do you analyze the following statements are descriptive and which statements
make an inference?]
17. 47 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.4.3a] [Research Findings Answering the Research Questions 3 tally with the
research objectives]
[Only four people passed one semester because the instructor was in a bad Mood the
entire semester. Answer 3: This statement makes an inference because we are not told
that the instructor was in a bad mood that semester.] [Elements or Members or
Populations]
[3.2.5] [How To Construct A Bar Graph?]
Step 1: We mark the various categories on the horizontal axis
Categories on the horizontal X-axis:
Categorize on the EDUCATION level-
Diploma
Degree/bachelor
Master
Step 2: We mark the frequencies on the vertical axis
a. Categories on the horizontal X-axis:
b. Mark the frequencies on the vertical y- axis
c. Earnings
RM18000
RM 36000
RM 72000
Step 3: Notes that all categories are represented by intervals of the same
width
Step 4: Then we draw one bar for each category such that the height of
the bar represents the frequency of the corresponding category
18. 48 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
Table 3.2: Typical Annual Earnings Based On Education Level
19. 49 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[3.2.6 ] [How To Construct A Combo Graph?]
Example On How To Construct Combo Graph Through Microsoft Excel Window
Step 1 : Start Windows
Step 2 : Select Program Excel Spreadsheet Application
Step 3 : Add on the particular variables information to be described
Step 4 : Fill in the lines backgrounds for each variables to illustrate your data relationship
Step 5 : Split off the variables to different page with different type of chart
Step 6 : Transpose the variables with graphical design accordingly
Step 7 : Sort out all the variables with population sampling differences by decoding them
either numerical 1 or using identity card accordingly
Step 8 : Filter out all the errors and select the best graphical design with percentages
values
Table 3.3 : Assessment on Data Information Findings Source Obtained by Contract Lecturer
Namely Lizinis Cassendra Frederick Dony Integrating Graphical Statistic Students’ Grading
Subject of BDM111 For September, 2017, Cosmopoint College, Kota
Kinabalu, Sabah, Malaysia
Year Born Demographic Final Exam Carry Marks Assessments
1997-0611 34% 41%
1997-1215 39% 54%
1998-0920 28% 42%
1998-0215 27% 51%
1998-1219 20% 40%
20. 50 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
Solution For Graphical Integrated Microsoft Office Excel 2007 Windows Applying Linear Statistical
Regression Presentation
Figure 3.6 : The Linear Regression Analysis Relationship Comparison Assessment On
Cosmopoint, Kota Kinabalu, Sabah, Malaysia Among The Population Sampling Variables
Characteristics Of Students’ Grade Comparison Between Carry Marks 60% and 40% For
September, 2017
21. 51 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[Based on page 43, the Figure 3.6 is to confirm that this chapter 4 is to visualize the Table
3.2 information is quantifying the strength of the linear relationship between a pair of
variables. Whereas the regression also having a positive (0.416) and negative15 (-0.04x)
close to 1.]
[This indicates that there is a strong linear statistical relationship for final exam grade
assessment in blue line chart coding narrowing down shown that most of the students
unable to adopt and memorize the statistical knowledge.]
[However, both findings indicates that Cosmopoint College education policy is providing
new opportunity for students to obtain better carry marks 60% (sixty percentage) to
entitled them having an excellent grade for Statistic BDM111.]
[Hence, this chapter 4 is to confirm that the mini research conference, international
research publication skills and knowledge among the students or lecturers on the business
health research statistical concept should be prioritized by the Cosmopoint College
management to produce a significant attention for quality leadership development.]
[Therefore, by obtaining more research grant integration this can increase quality lean
productivity for Cosmopoint College which can be explained by the movement of the
graphical line chart (red color) decoding with statistical excel Microsoft Office Version
Year 2007 Presentation displaying the variable as follows:-]
[Table 3.4 : The Carry Marks and Final Exam Assessment Outcome For Linear Regression
Variables Table Of Graphical BDM 111 Statistical Trend Characteristics Of Cosmopoint
Students’ Grade Comparison For Year September, 2017 Analysis]
[Carry Marks Assessments] [Final Exam Assessments]
[y = - 0.0647 + 0.4707] [y = -0.04x + 0.416]
[R2 = 0.0131] [R2 = 0.7648]
15 V Bewick (2003)(5 November 2003 “Statistics Review 7: Correlation and Regression – NCBI”.
22. 52 | P a g e C h a p t e r 3 : G r a p h i c a l P r e s e n t a t i o n
[References]
1. Fundamentals of Business Statistics, 6th Edition, Dennis J. Sweeney, Thomas A.
William, David R. Anderson, Thomson South Western, 2013.
2. Statistics, 3rd Edition, Lau Too Kya, Phang Yook Ngor & Zainudin Awang, Oxford
Fajar, 2015, CICT Library 10KK000001220 HA 35.L3882015.
3. Research Methods For Business : A Skill Building Approach, Fourth Edition, Uma
Sekaran, Southern Illinois University at Carbondale, Copyright 2003, John Wiley &
Sons, Inc, CICT Library, 03KLG000000070 HD30.4.S4352003.
Supplementary References Materials:
1. Basic Statistics for Business & Economics, 8th Edition, Douglas A. Lind, Coastal
Carolina University and The University of Toledo, William G. Marchal, The University of
Toledo, Samuel A. Wathen, Coastal Carolina University, Mc Graw Hill, 2012.
2. Introductory Statistics, Neil A. Weiss, 8th Edition, Pearson, 2011.
3. Basic Statistics For Business & Economics, Eighth Edition, Lind / Marchal / Wathen,
CICT Library 14KK2000000806 HA29.L5632013.