The document provides instructions for transferring data from paper questionnaires into a computer file for analysis. It describes conventions used such as different colors to denote different parts of the process. An example questionnaire is included with questions on topics of interest, predictions, health services, experience, demographics, and physical attributes. An excerpt is also shown of raw data entered on the computer with responses to the questionnaire questions.
Here are 3 sample goals for a talent brand program:
1. Increase employer brand awareness among target candidates by 15% over the next 12 months.
2. Reduce time-to-hire by 10% and cost-per-hire by 5% within the next year.
3. Achieve a 90% employee engagement score and retention rate of 90% for new hires within their first year.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
Creative operations teams expect increased AI use in 2024. Currently, over half of tasks are not AI-enabled, but this is expected to decrease in the coming year. ChatGPT is the most popular AI tool currently. Business leaders are more actively exploring AI benefits than individual contributors. Most respondents do not believe AI will impact workforce size in 2024. However, some inhibitions still exist around AI accuracy and lack of understanding. Creatives primarily want to use AI to save time on mundane tasks and boost productivity.
Organizational culture includes values, norms, systems, symbols, language, assumptions, beliefs, and habits that influence employee behaviors and how people interpret those behaviors. It is important because culture can help or hinder a company's success. Some key aspects of Netflix's culture that help it achieve results include hiring smartly so every position has stars, focusing on attitude over just aptitude, and having a strict policy against peacocks, whiners, and jerks.
Here are 3 sample goals for a talent brand program:
1. Increase employer brand awareness among target candidates by 15% over the next 12 months.
2. Reduce time-to-hire by 10% and cost-per-hire by 5% within the next year.
3. Achieve a 90% employee engagement score and retention rate of 90% for new hires within their first year.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
Creative operations teams expect increased AI use in 2024. Currently, over half of tasks are not AI-enabled, but this is expected to decrease in the coming year. ChatGPT is the most popular AI tool currently. Business leaders are more actively exploring AI benefits than individual contributors. Most respondents do not believe AI will impact workforce size in 2024. However, some inhibitions still exist around AI accuracy and lack of understanding. Creatives primarily want to use AI to save time on mundane tasks and boost productivity.
Organizational culture includes values, norms, systems, symbols, language, assumptions, beliefs, and habits that influence employee behaviors and how people interpret those behaviors. It is important because culture can help or hinder a company's success. Some key aspects of Netflix's culture that help it achieve results include hiring smartly so every position has stars, focusing on attitude over just aptitude, and having a strict policy against peacocks, whiners, and jerks.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
PEPSICO Presentation to CAGNY Conference Feb 2024Neil Kimberley
PepsiCo provided a safe harbor statement noting that any forward-looking statements are based on currently available information and are subject to risks and uncertainties. It also provided information on non-GAAP measures and directing readers to its website for disclosure and reconciliation. The document then discussed PepsiCo's business overview, including that it is a global beverage and convenient food company with iconic brands, $91 billion in net revenue in 2023, and nearly $14 billion in core operating profit. It operates through a divisional structure with a focus on local consumers.
Content Methodology: A Best Practices Report (Webinar)contently
This document provides an overview of content methodology best practices. It defines content methodology as establishing objectives, KPIs, and a culture of continuous learning and iteration. An effective methodology focuses on connecting with audiences, creating optimal content, and optimizing processes. It also discusses why a methodology is needed due to the competitive landscape, proliferation of channels, and opportunities for improvement. Components of an effective methodology include defining objectives and KPIs, audience analysis, identifying opportunities, and evaluating resources. The document concludes with recommendations around creating a content plan, testing and optimizing content over 90 days.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
PEPSICO Presentation to CAGNY Conference Feb 2024Neil Kimberley
PepsiCo provided a safe harbor statement noting that any forward-looking statements are based on currently available information and are subject to risks and uncertainties. It also provided information on non-GAAP measures and directing readers to its website for disclosure and reconciliation. The document then discussed PepsiCo's business overview, including that it is a global beverage and convenient food company with iconic brands, $91 billion in net revenue in 2023, and nearly $14 billion in core operating profit. It operates through a divisional structure with a focus on local consumers.
Content Methodology: A Best Practices Report (Webinar)contently
This document provides an overview of content methodology best practices. It defines content methodology as establishing objectives, KPIs, and a culture of continuous learning and iteration. An effective methodology focuses on connecting with audiences, creating optimal content, and optimizing processes. It also discusses why a methodology is needed due to the competitive landscape, proliferation of channels, and opportunities for improvement. Components of an effective methodology include defining objectives and KPIs, audience analysis, identifying opportunities, and evaluating resources. The document concludes with recommendations around creating a content plan, testing and optimizing content over 90 days.
How to Prepare For a Successful Job Search for 2024Albert Qian
The document provides guidance on preparing a job search for 2024. It discusses the state of the job market, focusing on growth in AI and healthcare but also continued layoffs. It recommends figuring out what you want to do by researching interests and skills, then conducting informational interviews. The job search should involve building a personal brand on LinkedIn, actively applying to jobs, tailoring resumes and interviews, maintaining job hunting as a habit, and continuing self-improvement. Once hired, the document advises setting new goals and keeping skills and networking active in case of future opportunities.
A report by thenetworkone and Kurio.
The contributing experts and agencies are (in an alphabetical order): Sylwia Rytel, Social Media Supervisor, 180heartbeats + JUNG v MATT (PL), Sharlene Jenner, Vice President - Director of Engagement Strategy, Abelson Taylor (USA), Alex Casanovas, Digital Director, Atrevia (ES), Dora Beilin, Senior Social Strategist, Barrett Hoffher (USA), Min Seo, Campaign Director, Brand New Agency (KR), Deshé M. Gully, Associate Strategist, Day One Agency (USA), Francesca Trevisan, Strategist, Different (IT), Trevor Crossman, CX and Digital Transformation Director; Olivia Hussey, Strategic Planner; Simi Srinarula, Social Media Manager, The Hallway (AUS), James Hebbert, Managing Director, Hylink (CN / UK), Mundy Álvarez, Planning Director; Pedro Rojas, Social Media Manager; Pancho González, CCO, Inbrax (CH), Oana Oprea, Head of Digital Planning, Jam Session Agency (RO), Amy Bottrill, Social Account Director, Launch (UK), Gaby Arriaga, Founder, Leonardo1452 (MX), Shantesh S Row, Creative Director, Liwa (UAE), Rajesh Mehta, Chief Strategy Officer; Dhruv Gaur, Digital Planning Lead; Leonie Mergulhao, Account Supervisor - Social Media & PR, Medulla (IN), Aurelija Plioplytė, Head of Digital & Social, Not Perfect (LI), Daiana Khaidargaliyeva, Account Manager, Osaka Labs (UK / USA), Stefanie Söhnchen, Vice President Digital, PIABO Communications (DE), Elisabeth Winiartati, Managing Consultant, Head of Global Integrated Communications; Lydia Aprina, Account Manager, Integrated Marketing and Communications; Nita Prabowo, Account Manager, Integrated Marketing and Communications; Okhi, Web Developer, PNTR Group (ID), Kei Obusan, Insights Director; Daffi Ranandi, Insights Manager, Radarr (SG), Gautam Reghunath, Co-founder & CEO, Talented (IN), Donagh Humphreys, Head of Social and Digital Innovation, THINKHOUSE (IRE), Sarah Yim, Strategy Director, Zulu Alpha Kilo (CA).
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
The search marketing landscape is evolving rapidly with new technologies, and professionals, like you, rely on innovative paid search strategies to meet changing demands.
It’s important that you’re ready to implement new strategies in 2024.
Check this out and learn the top trends in paid search advertising that are expected to gain traction, so you can drive higher ROI more efficiently in 2024.
You’ll learn:
- The latest trends in AI and automation, and what this means for an evolving paid search ecosystem.
- New developments in privacy and data regulation.
- Emerging ad formats that are expected to make an impact next year.
Watch Sreekant Lanka from iQuanti and Irina Klein from OneMain Financial as they dive into the future of paid search and explore the trends, strategies, and technologies that will shape the search marketing landscape.
If you’re looking to assess your paid search strategy and design an industry-aligned plan for 2024, then this webinar is for you.
5 Public speaking tips from TED - Visualized summarySpeakerHub
From their humble beginnings in 1984, TED has grown into the world’s most powerful amplifier for speakers and thought-leaders to share their ideas. They have over 2,400 filmed talks (not including the 30,000+ TEDx videos) freely available online, and have hosted over 17,500 events around the world.
With over one billion views in a year, it’s no wonder that so many speakers are looking to TED for ideas on how to share their message more effectively.
The article “5 Public-Speaking Tips TED Gives Its Speakers”, by Carmine Gallo for Forbes, gives speakers five practical ways to connect with their audience, and effectively share their ideas on stage.
Whether you are gearing up to get on a TED stage yourself, or just want to master the skills that so many of their speakers possess, these tips and quotes from Chris Anderson, the TED Talks Curator, will encourage you to make the most impactful impression on your audience.
See the full article and more summaries like this on SpeakerHub here: https://speakerhub.com/blog/5-presentation-tips-ted-gives-its-speakers
See the original article on Forbes here:
http://www.forbes.com/forbes/welcome/?toURL=http://www.forbes.com/sites/carminegallo/2016/05/06/5-public-speaking-tips-ted-gives-its-speakers/&refURL=&referrer=#5c07a8221d9b
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
Everyone is in agreement that ChatGPT (and other generative AI tools) will shape the future of work. Yet there is little consensus on exactly how, when, and to what extent this technology will change our world.
Businesses that extract maximum value from ChatGPT will use it as a collaborative tool for everything from brainstorming to technical maintenance.
For individuals, now is the time to pinpoint the skills the future professional will need to thrive in the AI age.
Check out this presentation to understand what ChatGPT is, how it will shape the future of work, and how you can prepare to take advantage.
The document provides career advice for getting into the tech field, including:
- Doing projects and internships in college to build a portfolio.
- Learning about different roles and technologies through industry research.
- Contributing to open source projects to build experience and network.
- Developing a personal brand through a website and social media presence.
- Networking through events, communities, and finding a mentor.
- Practicing interviews through mock interviews and whiteboarding coding questions.
Google's Just Not That Into You: Understanding Core Updates & Search IntentLily Ray
1. Core updates from Google periodically change how its algorithms assess and rank websites and pages. This can impact rankings through shifts in user intent, site quality issues being caught up to, world events influencing queries, and overhauls to search like the E-A-T framework.
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The six step guide to practical project managementMindGenius
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2. Fun questionnaire completed by students in first session and used for data entry
Please complete this questionnaire2 in black ink. It will be | Serial
used in the first part of the course to demonstrate how | (1-2)
questionnaire responses become data in a computer file and |
how we can classify and analyse different types of |
questions. Some questions are taken from the 1986 British |
Social Attitudes survey which we will be analysing later in |
the course, some are intended to give us some idea of your |
experience and interests and others are about yourself. If |
you cannot answer a question, or do not wish to, just leave |
it blank. The completed questionnaires will be photocopied |
for other students to use, so if you're worried about |
confidentiality, just make up your answers! |(3)Blank
_____________________________________________________________|
|
Q1. These are some of the topics covered by the 1986 |
British Social Attitudes survey. Please rank them in |
order of their interest to you. (Write 1 in the box |
against your first choice, 2 for your second and so on |
up to 5) |
__ |
Welfare State |__| | (4)
__ |
Countryside |__| | (5)
__ |
Defence and Nuclear Issues |__| | (6)
__ |
Politics |__| | (7)
__ |
Industry and Employment |__| | (8)
|
| (9)Blank
Q2. Here are a few predictions. For each one, please say |
how likely or unlikely you think it is to come true |
within the next ten years. (Tick one box for each) |
|
Very Quite Not Not at |
likely likely Very all |
likely likely |
|
There will be a serious 1 2 3 4 |
accident at a British __ __ __ __ |
nuclear power station |__| |__| |__| |__| | (10)
|
The police in our cities |
will find it impossible to |
protect our personal safety __ __ __ __ |
on the streets |__| |__| |__| |__| | (11)
|
A nuclear bomb will be |
dropped somewhere in the __ __ __ __ |
world |__| |__| |__| |__| | (12)
|
|(13)Blank
2
The handouts also included a photocopy of an 80-column Hollerith card and a transparency of the keyboard for the
computer terminals at PNL, but these would probably be superfluous these days.
2
3. Q3. All in all, how satisfied or dissatisfied would you |
say you are with the way in which the National Health |
Service runs nowadays? (Tick one box) | (14)
__ |
Very satisfied |__| | 1
__ |
Quite satisfied |__| | 2
__ |
Neither satisfied nor dissatisfied |__| | 3
__ |
Quite dissatisfied |__| | 4
__ |
Very dissatisfied |__| | 5
|
|(15)Blank
Q4. Have you had training or practical experience in any of |
the following? (Tick as many as apply) | (16-20)
__ |
Typing |__| | 1
__ |
Wordprocessing |__| | 2
__ |
Social Statistics |__| | 3
__ |
Survey analysis using SPSS or similar packages |__| | 4
__ |
Other computing experience |__| | 5
(Please specify) |
|(21)Blank
|
| (22)
__ |
Q5. Are you ....? (Please tick) Male |__| | 1
__ |
Female |__| | 2
|
|(23)Blank
Q6. How will you be travelling to the Polytechnic? | (24)
__ |
(Tick main mode only) Public Transport |__| | 1
__ |
Car |__| | 2
__ |
M'cycle/Cycle |__| | 3
__ |
Walking |__| | 4
|
______ |(25)Blank
Q7. What was your age last birthday? (Write in) | | |
|______| | (26-27)
_______ |(28)Blank
Q8. What is your height in metres? (Write in) | | |
___________ |_______| | (29-32)
| | |(33)Blank
( or feet & inches here!! | ' " | ) |
|___________| | (34-37)
|
|
3
4. Data transfer sheet3 for use (sideways) with class exercise
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 01 Serial number
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 02
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 03 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 04 Welfare State
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 05 Countryside
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 06 Defence etc |__|__|__|__
__|__|__|__|__|__|__|__|__|__|__| 07 Politics
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 08 Industry and Employment
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 09 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 10 Nuclear accident
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 11 No personal safety
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 12 Nuclear bomb dropped
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 13 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 14 National Health
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 15 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 16 Typing
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 17 Wordprocessing
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 18 Social Statistics
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 19 Survey analysis
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 20 Other
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 21 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 22 Sex
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 23 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 24 Travel mode
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 25 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 26- Age last birthday
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| -27
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 28 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 29- Height in metres
|. |. |. |. |. |. |. |. |. |. |. |. |. |. |. | -30 (decimal point)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| -31 (centi-
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| -32 metres....)
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 33 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 34 Feet
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ 35 (Blank)
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| 36- Inches
|__|__|__|__|__|__|__|__|__|__|__|__|__|__|__| -37
3
At the beginning of the second session of the course, students were given photocopies of 15 completed questionnaires
and required to transfer data on to the above transfer sheet. Data was then to be typed (accurately) ready for input to
SPSS. On the Vax this was done using EDT, but for Windows it needs to be typed up as a *.txt Word file in a fixed
character width font (e.g. Courier) to keep the data columns properly aligned. They could also be typed direct into the
SPSS Data Editor in Data View mode, but this loses the point of learning how data originate and how to use SPSS to
read data from an external file (or sometimes from a list inside the syntax file), as many data files in the public domain
arrive as WordPerfect *.dat files in Times New Roman font, which will work with SPSS, but which need to be converted to
fixed character width to make them much easier to read or check yourself.
4
5. Extract from raw data for fun questionnaire as entered on computer 4
(first 40 cases only, one line per case)
1 35214 112 5 125 1 3 32 5 10
2 14532 233 3 1234 2 1 44 5 7
3 23415 343 5 1 1 2 32 5 8
4 12345 234 4 13 2 1 39 5 6
5 24531 143 5 125 2 2 34 5 3
6 15243 213 4 1235 2 1 27 5 5
7 15342 212 5 12 1 4 26 5 11
8 25431 212 5 1 1 1 26 5 3
9 14523 222 5 123 2 1 31 5 4
10 15324 323 4 3 2 1 22 5 3
11 24531 112 4 1235 2 1 39 1.68
12 25431 323 3 12 2 1 5 8
13 25413 2 3 3 2 4 1 1 28 5 10
14 42312 322 5 12 5 1 1 22 1.80
15 15324 213 4 23 2 1 36 5 1
16 14523 223 5 12345 1 3 28 1.74
17 24531 323 5 1234 2 1 40 5 4
18 35421 233 5 34 2 1 23 5 3
19 14253 344 4 12 2 2 37 5 7
20 12354 223 4 1234 2 1 39 5 7
21 25413 111 5 2 1 1 28 5 0
22 35412 222 4 23 5 2 1 29 5 5
23 1 112 5 123 2 1 30 5 8
24 25413 212 4 234 2 1 26 5 6
25 14235 242 5 2345 2 1 23 5 8
26 13245 233 4 3 1 1 30 1.72
27 52314 233 4 123 2 1 36 5 0
28 23415 122 4 123 2 1 23 1.66
29 15324 242 3 123 2 4 29 5 0
30 13245 222 4 23 1 1 22 5 8
30 13245 222 4 23 1 1 22 5 8
31 12453 333 4 345 2 2 31 5 2
32 15423 223 3 12345 1 4 30 1.80
33 24513 313 4 12 1 2 31 5 11
34 43215 221 2 12 1 1 32 1.65 5 5
35 25314 212 3 12345 2 1 28 5 4
36 23514 222 5 12 1 2 38 5 10
37 12435 232 5 12345 2 1 35 5 5
38 15324 223 3 1235 1 1 69 6 0
39 12543 223 4 6 2 1 31 1.65
40 13524 233 4 123 2 1 24 5 9
How do we now get SPSS to read data from this file and save them as variables for later use?
We start by deciding which variables we want to define and use in our analysis and then give
4
NB The above data set had blanks deliberately inserted (on the transfer sheet) to make it clearer. Most raw
data sets will have no blanks, except possibly just after the serial number and around column 40 on an 80-
column line. This use of blanks is advisable because, on visual inspection, the blanks will show up as vertical
white lines and certain kinds of data entry errors will then be clearly visible.
5
6. them names. Variable names in SPSS can be any combination of up to 8 letters and
numbers, but the first character must always be a letter of the alphabet. For beginners it may
be easier to use a variable name which looks like plain English (e.g. SEX, AGE, HEIGHT).
These are known as mnemonic names (after the Greek for memory) and may be easier to
remember.
However, in a survey with a very large number of variables, several hundred variable names 5
may be needed, plus the generation of new and unique names for derived variables such as
grouped age or score on an attitude scale. Remembering all their names, not to mention where
they all are in the file, and to which questions they relate, constitutes a prodigious and, to me,
pointless effort which virtually guarantees errors and makes smooth working on large data files
tedious and cumbersome, especially when using point-and-click.
Let's take it one step at a time for just 3 variables, serial number, sex and age.
It helps to have a little table to refer to:
Line Variable name Position Type
1 SERIAL 1-2 Integer
1 SEX 22 Integer
1 AGE 26-27 Integer
Step 1:
Give each of your variables, including the serial number, a name. Use mnemonics for this
once! Later, we’ll use positional names for most of the remaining variables. The name must
start with a letter of the alphabet, but must not be longer than 8 characters in total. Thus:
SERIAL SEX AGE
Step 2
Work out for each variable whether it has been entered in the data as numeric or alphabetic. If
numeric, does it have any decimal places? Very few social surveys ever collect data with
decimals unless they are financial or medical, so we don't need to bother ourselves with that
just yet, but later on we shall need to read the data for height in metres to 2 decimal places. In
this example sex has already been entered as 1 for male and 2 for female, so we don’t need to
bother with alphabetic formats either.
Step 3
For each variable, work out which line of data it is on and which position it occupies in the line.
In this example there is only one line of data (or record) per case, but later examples will involve
data sets with as many as 23 records per case.
Step 4
To read the data for our chosen variables we need to know the line (record) number in which
the first variable occurs. Since there is only record per case, all three variables are therefore by
definition on line 1, and so we specify the line we want by writing a forward slash "/" followed by
the number of the line:
5
See separate document by John Hall & Jim Ring, Conventions for Naming Variables in SPSS
6
7. /1
Step 5
Next we write down the name of the first variable we want from that line. We want three
variables altogether, and they are all on the same line. The first one is SERIAL.
/1 SERIAL
Step 6
Write in the column(s) within the line where that variable is coded. If it is coded across more
than one column, write the start column followed by a hyphen, then the end column.
/1 SERIAL 1-2
Step 7
Finally, write in brackets the number of decimal places (in this case, numeric with no decimal
places, i.e. an integer )
/1 SERIAL 1-2 (0)
Well, that's our first variable specified: now let's do the rest. Repeating all the steps we get:
/1 SERIAL 1-2 (0)
SEX 22 (0)
AGE 26-27 (0)
(Note that if you have more than one variable on the same data line you only need to give the
line number once.)
What we have just done is to specify our three variables and their respective locations in the
data file exactly as they are needed as part of a data list in a syntax file (the set of instructions
you have to type in) by SPSS. However, before we can use this specification, we also need to
tell SPSS where to look for the data and how many records there are for each case.
There are two ways of doing this; one is to include the data inside the SPSS syntax file, the
other is to give the name and location of the file in which the data are stored. We shall be using
the latter method here. Because such data files are not actually part of SPSS, they are known
as external files.
We are now ready to move on to SPSS proper, but first a note on SPSS syntax.
SPSS works using commands, which must always start in column 1. Within a command there
can be sub-commands and/or specifications which can start anywhere after the command,
continuing on following lines if necessary, but not in the first column. For clarity, beginners
should use tabs to inset specifications and sub-commands, but once you get the hang of it, you
can simply use one or more spaces in column 1. Moreover SPSS is not case specific except for
user-written labels, so you can work entirely in lower case. SPSS will always print variable
names in upper case on the output. All commands must end with a full stop.
To read data into SPSS we use the DATA LIST command, followed by two sub-commands, the
7
8. first, FILE = to specify the location of the external data file and the second, RECORDS =
to specify the number of records per case. In formal syntax (which will be used from now on for
introducing new commands in SPSS):
Command Sub-command Specification <user-supplied>
eg DATA LIST FILE = <location and name of external data file>
RECORDS = <number of records per case>
A "record" in SPSS can be a line of up to 255 columns, but in practice we tend to use only 80,
partly because that is how many columns there used to be on the industry-standard Hollerith
terminal with a visual display unit (VDU).
In this case we only have 1 record per case, so RECORDS = 1 will be needed. But what do we
do about FILE = ? SPSS sometimes needs to access a file from somewhere else in the
computer. This is known as an external file. To use such a file, SPSS needs to be given the
name of the external file enclosed in single primes (e.g. 'CLASS.DAT') and the drive, directory
or folder where it is located. In the Windows version, this can involve complex file
specifications, so for this example the raw data are assumed to have been written to a file called
class.dat on a floppy disk in drive a: and will henceforth be referred to as ‘a:class.dat’.
So here we go! Call up SPSS and when the menu for requests comes up, click on Cancel to
arrive at the blank SPSS Data Editor illustrated below:
Figure 1: Initial Data Editor in Variable View
This is the default Variable View in which the variable names will appear in the left hand
column and various additional information about them in the other columns. Now click on the
8
9. Data View tab at bottom left to get:
Figure 2: Initial Data Editor in Data View
. . . in which the variables are arranged in columns and the cases in the rows. This is the same
format as an Excel spreadsheet (from which SPSS can also import data direct, but that’s
another story). Click on the Variable View tab to return to the previous display.
Now click top left. . .
File….
New….
Syntax
. . . to obtain:
9
10. Figure 3: Blank Data Editor in Variable View overlaid with blank Syntax Editor
The cursor will be flashing in the top left corner of the syntax window. Type in carefully the
following command after the cursor (don’t forget to start the first line in column 1 and inset the
continuation lines with at least one space. For clarity the example below uses tabs to inset the
sub-commands and continuation lines. Don’t forget the full stop at the end of the last line!):
data list file = ‘a:class.dat’
records = 1
/1 serial 1-2
sex 22
age 26-27.
To run SPSS, make sure the cursor is somewhere in the text you have typed and press [CTRL]
+R on the keyboard or click on Run at the top of the window. SPSS will read the data
specifications and display the following output file output1.spo in the Viewer Window.
Data List will read 1 records from a:class.dat
Variable Rec Start End Format
SERIAL 1 1 2 F2.0
SEX 1 22 22 F1.0
AGE 1 26 27 F2.0
10
11. There will be a new small icon at the bottom of the screen (SPSS in red above a white rectangle
with the corner folded down). Click on this to see the SPSS Data Editor with your syntax
file syntax1.sps in front of it like this:
Figure 4: Syntax file with command as entered and Data Editor with variables defined
However, if you click on Data View in the bottom left corner of the Data Editor, you will get a
blank matrix. Do not panic! You have not lost your data: SPSS hasn’t actually read it yet!
You’ve only told it what to expect. If you look carefully at the top of the screen you will see
a small difference: your three variable names, serial, sex and age appear at the top of the
first three columns instead of var, var, var. This is because SPSS doesn’t actually read
the data until you ask for some analysis or use any of the special commands such as
listing the data. For instance you can click on the syntax file and add a line asking to see
the data for the first 5 cases by:
list /cases = 5. . .press [CTRL]+R and SPSS will produce a table:
SERIAL SEX AGE
1 1 32
2 2 44
3 1 32
4 2 39
5 2 34
Number of cases read: 5 Number of cases listed: 5
11
12. The Data Editor in Data View will now look like this:
Figure 5: Data Editor in Data View after reading raw data
In the above window, you can see that SPSS has copied the raw data for your three variables
as numeric values into cells in a data matrix, in which the rows denote the cases and the
columns denote the variables. Wherever it found a blank entry in the data, it has substituted a
full stop, which it will always treat as a missing value.
If you scroll down the file you will notice that the serial numbers stop at 99 and start again at 0,
then stop at 50 and start again at 0. This is because the questionnaire was used with several
waves of students on the course, but only two columns were allowed for the serial number in
each wave6. The data used here are accumulated across all waves.
It’s now time to have a shot at the real thing, reading in data for all variables in the fun
questionnaire. Try writing out your DATA LIST command before you read the next page.
You’ll be doing a lot of runs with SPSS, so it’s a good idea to put some sort of heading or title on
each run to remind you (and others) what you are doing. You can use RUN NAME at the
beginning or TITLE anywhere, followed by text in single primes, then a full stop eg.:
run name 'Read raw data from a:class.dat'.
6
With hindsight the course code, starting month and year of the course should have been coded somewhere as
well. Data from all courses were later concatenated to produce a larger data set, but there are no duplicate cases.
Examination of the ages might help to find the separation point for each wave since post-graduates taking SR501
were normally older than undergraduates taking SR206.
12
13. Reading of raw data file into initial SPSS data editor using DATA LIST
run name 'Read raw data from a:class.dat'.
data list file ‘a:class.dat’ (or wherever and whatever your raw data file is called)
records 1
/1 serial 1-2
v4 to v8 4-8
v10 to v12 10-12
v14 14
v16 to v20 16 - 20
sex 22
v24 24
age 26-27
metres 29-32
feet 34
inches 36-37.
The SPSS output looks like this..
Data List will read 1 record from ‘a:class.dat’
Variable7 Record Start End Format8
column column
SERIAL 1 1 2 F2.0
V4 1 4 4 F1.0
V5 1 5 5 F1.0
V6 1 6 6 F1.0
V7 1 7 7 F1.0
V8 1 8 8 F1.0
V10 1 10 10 F1.0
V11 1 11 11 F1.0
V12 1 12 12 F1.0
V14 1 14 14 F1.0
V16 1 16 16 F1.0
V17 1 17 17 F1.0
V18 1 18 18 F1.0
V19 1 19 19 F1.0
V20 1 20 20 F1.0
SEX 1 22 22 F1.0
V24 1 24 24 F1.0
AGE 1 26 27 F2.0
METRES 1 29 32 F4.2
FEET 1 34 34 F1.0
INCHES 1 36 37 F2.0
7
Note that using positional variable names has the added advantage of enabling you to check visually that the
data for each variable has been read from the correct column(s).
8
Floating point decimal: tells the computer how many digits come after the decimal point. F1.0 means a number
one column wide with no decimal places, F2.0 means 2 columns wide with no decimals. Notice METRES has
been read as F4.2, or 4 columns with 2 decimals. This is because METRES is read from a field of 4 columns with
the decimal point actually entered in the raw data. If it had been entered in 3 columns without the decimal point
(eg 165 instead of 1.65) SPSS would read it as F3.2 and put the decimal point in for you. SPSS default for
numeric input is an integer with no decimal places.
13
14. The SPSS Data Editor will have filled up to look like this:
Figure 6: Data Editor in Variable View after all data has been defined, but not yet read in.
This is the default display in Variable View.
SPSS does not actually read the raw data until required to by some task or other, so the Data
View will again be empty for the moment but you can display the variable names by:
display.
. . . which gives:
Currently Defined Variables
SERIAL V6 V10 V14 V18 SEX METRES
V4 V7 V11 V16 V19 V24 FEET
V5 V8 V12 V17 V20 AGE INCHES
(ordered downwards in columns: confusing at first as some users expect left to right in rows)
14
16. The Data Editor in Data View will now look like this:
Figure 7: Data Editor in Data View after data read in
Use the bar at bottom right to scroll to the right to see rest of the data up to inches, or the side bar at
right to scroll down through all the cases.
If you like you can add your own answers to the full data set by completing the questionnaire,
transferring your data to the coding sheet and then entering your data directly into the Data Editor in
Data View mode after the last case. This will help you understand how the original data set was
generated and possibly show you how mistakes can happen. You will be surprised how easy it is to
get correct data in the wrong position or even incorrect data in the right position, especially if you are
entering data from long batteries of attitude or similar scales.
Most students only gave their heights in either metres or feet and inches, so we now need to calculate
a derived variable, height 9 in metres for all cases. A bit complicated for beginners, but this is dealt
with later in the course. For the moment it has been calculated and entered into the last column.
9
The SPSS commands for this are:
compute height = metres.
if missing (metres) height =((feet*12+inches)/39.3).
NB The double brackets are needed to avoid SPSS interpreting the decimal point as a full stop ending the command
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17. The SPSS command display. produces:
Currently Defined Variables
SERIAL V6 V10 V14 V18 SEX METRES INCHES
V4 V7 V11 V16 V19 V24 FEET HEIGHT
V5 V8 V12 V17 V20 AGE
If you want to see what the data look like inside SPSS, click on Data View. You can slide the
column markers between the variable names to make the columns narrower and get all the
variables into view, thus:
Figure 8: Data from fun questionnaire in Data View mode
At this point it is good practice to save the first edition of your work. At every stage successfully
completed after this, it is also advisable to save your work. Very small surveys or data sets can
be generated in a single run, but this is not advisable for beginners, or even for experienced
researchers, especially if you want to keep track of your work. On very large data sets, several
runs may be needed before the final version is achieved.
You are best advised to assemble your SPSS saved files in stages, starting with DATA LIST,
then follow with MISSING VALUES, VARIABLE LABELS and VALUE LABELS in that order,
followed by generation of derived variables. This may sound cumbersome, but years of
experience have shown it to be more effective and much less frustrating in the long run.
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18. Files need to have the correct extension if SPSS is to read or write them properly (*.sps for
syntax files, *.sav for data editors, *.spo for output files and *.por for portable files) This is
usually done automatically by SPSS using point-and-click, one of the few occasions on which
this method triumphs over syntax mode. Initial raw data files can use *.dat which will appear as
WordPerfect files on screen, but you can also input raw data directly into the data editor as well.
Although this is only a fun exercise, you should get into the habit of saving your work every
so often. This applies to data sets, syntax files and your working SPSS Data Editor. However,
there is no point in saving output files resulting from runs with errors in them. SPSS is so fast
on modern PC’s that, when errors occur, it is better to close the output file and then click on
No when asked if you want to save it. Otherwise you’ll finish up with dozens of error filled
output files clogging your machine. In the old days, this used to be reams of printout, so at least
we’re saving a few trees! Just go back to the syntax file, correct the error(s) and run it again
(and again) until you get the correct results. SPSS generates its own names in sequence for
syntax, output and saved files, but you would be well advised to change these when you save
them with save as … since you won’t necessarily remember what you did in syntax109.sps!
Recommended practice would be to create a new folder and keep all the related files for this
survey together in the same folder. If the number of files gets too large, you can always create
sub-folders.
Since this is the first exercise you could call all the files myclass1 in a folder called myclass.
First create a new folder myclass in your working area and then go back to the SPSS Data
Editor. If you now type myclass1 in the box then click on save, SPSS will create a file called
myclass1.sav in folder myclass and the filename displayed at top left of the Data Editor will
change from Untitled to myclass1. From now on, any attempt to close a data, syntax or output
file which has been modified will result in an SPSS prompt asking you if you want to save the
changes.
Thus left click in the top left of the window on:
File….
Save as…..
SPSS will display the window below, with the cursor flashing in the file name: box.
NB: If the folder contains any other SPSS files in *.sav format, they will be displayed as icons,
but if this is your first attempt the window will be empty. Don’t panic! There may be other types
of files in the same folder, but they will not be displayed.
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19. Figure 9: Window for saving Data Editor
SPSS will automatically assign the extension .sav to the file to be saved. If you want the work
saved in a different area or folder, browse until you arrive at your selected folder, then type your
file name in the box and click on save.
Now follow the same procedure with the syntax file and save it as myclass1.sps and, if you
want to save it, the output file as myclass1.spo. SPSS will add the extensions automatically.
The next set can then be called myclass2.* and so on. This way all files relating to a particular
run will have the same file name part and you will be able to keep track of your work, or at least
know which files go together. The author also uses file names such as freq*.* and tab*.* etc.
(to indicate frequency and tabulation runs) or names indicating the substantive content (eg
protest*.* or anomy*.*).
Until you are absolutely certain of the accuracy and completeness of any subsequent files, you
should always keep the earlier and current editions and also copy them to an external medium
(eg, dsk:a) in case of computer crashes, power failures or other incidents such as accidental
deletion.
You have been warned! Don’t find out the hard way!
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20. Figure 9: Window for saving Data Editor
SPSS will automatically assign the extension .sav to the file to be saved. If you want the work
saved in a different area or folder, browse until you arrive at your selected folder, then type your
file name in the box and click on save.
Now follow the same procedure with the syntax file and save it as myclass1.sps and, if you
want to save it, the output file as myclass1.spo. SPSS will add the extensions automatically.
The next set can then be called myclass2.* and so on. This way all files relating to a particular
run will have the same file name part and you will be able to keep track of your work, or at least
know which files go together. The author also uses file names such as freq*.* and tab*.* etc.
(to indicate frequency and tabulation runs) or names indicating the substantive content (eg
protest*.* or anomy*.*).
Until you are absolutely certain of the accuracy and completeness of any subsequent files, you
should always keep the earlier and current editions and also copy them to an external medium
(eg, dsk:a) in case of computer crashes, power failures or other incidents such as accidental
deletion.
You have been warned! Don’t find out the hard way!
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