The presentation was prepared to provide a brief overview on Regression analysis as to what it means and how it differs from related statistical measures like Correlation. The last few slides briefly discusses on the different types of data used in Econometrics.
The presentation was prepared to provide a brief overview on Regression analysis as to what it means and how it differs from related statistical measures like Correlation. The last few slides briefly discusses on the different types of data used in Econometrics.
In this session, we will discuss, how to calculate Spearman's correlation when two or more ranks are the same.
We have considered multiple situations, various permutations and combinations to clarify the concept.
For ACCA students studying P1 Governance, Risk, and Ethics
Powerpoint slide notes on the 9 concepts of corporate governance.
Probity/honesty
Integrity
Fairness
Responsibility
Independence
Judgment
Transparency
Accountability
Reputation
More resources at www.accaforstudents.com
It is quite instrumental stuff for having very basic understanding of the discipline of OB and its linkage with other related disciplines, its challenges and prospects.
What is Organizational Behavior
The study and application of knowledge about how people, individuals, and groups act in organizations.
Its framework,history and importance to manager.
QUANTITATIVE TECHNIQUES, TIME SERIES, CROSS SECTIONAL ANALYSIS, TIME SERIES RESEARCH, CROSS SECTIONAL RESEARCH, COMPARISON BETWEEN TIME SERIES AND CROSS SECTIONAL ANALYSIS, QUANTITATIVE ANALYSIS, QUANTITATIVE RESEARCH, RESEARCH METHODS, ORGANIZATION'S STUDY, LIBCORPIO786, BUSINESS ADMINISTRATION, MANAGEMENT SCIENCE, EDUCATION AND LEARNING,
PREDICTING BANKRUPTCY USING MACHINE LEARNING ALGORITHMSIJCI JOURNAL
This paper is written for predicting Bankruptcy using different Machine Learning Algorithms. Whether the company will go bankrupt or not is one of the most challenging and toughest question to answer in the 21st Century. Bankruptcy is defined as the final stage of failure for a firm. A company declares that it has gone bankrupt when at that present moment it does not have enough funds to pay the creditors. It is a global
problem. This paper provides a unique methodology to classify companies as bankrupt or healthy by applying predictive analytics. The prediction model stated in this paper yields better accuracy with standard parameters used for bankruptcy prediction than previously applied prediction methodologies.
Market Research using SPSS _ Edu4Sure Sept 2023.pptEdu4Sure
SPSS Training Related Content. There is practical training on the tool. The PPT is for reference purpose.
For any training need, kindly connect us at partner@edu4sure.com or call us at +91-9555115533.
For more courses at our LMS, you can also refer www.testformula.com
#Edu4Sure #SPSS #Training #Certificate
In this session, we will discuss, how to calculate Spearman's correlation when two or more ranks are the same.
We have considered multiple situations, various permutations and combinations to clarify the concept.
For ACCA students studying P1 Governance, Risk, and Ethics
Powerpoint slide notes on the 9 concepts of corporate governance.
Probity/honesty
Integrity
Fairness
Responsibility
Independence
Judgment
Transparency
Accountability
Reputation
More resources at www.accaforstudents.com
It is quite instrumental stuff for having very basic understanding of the discipline of OB and its linkage with other related disciplines, its challenges and prospects.
What is Organizational Behavior
The study and application of knowledge about how people, individuals, and groups act in organizations.
Its framework,history and importance to manager.
QUANTITATIVE TECHNIQUES, TIME SERIES, CROSS SECTIONAL ANALYSIS, TIME SERIES RESEARCH, CROSS SECTIONAL RESEARCH, COMPARISON BETWEEN TIME SERIES AND CROSS SECTIONAL ANALYSIS, QUANTITATIVE ANALYSIS, QUANTITATIVE RESEARCH, RESEARCH METHODS, ORGANIZATION'S STUDY, LIBCORPIO786, BUSINESS ADMINISTRATION, MANAGEMENT SCIENCE, EDUCATION AND LEARNING,
PREDICTING BANKRUPTCY USING MACHINE LEARNING ALGORITHMSIJCI JOURNAL
This paper is written for predicting Bankruptcy using different Machine Learning Algorithms. Whether the company will go bankrupt or not is one of the most challenging and toughest question to answer in the 21st Century. Bankruptcy is defined as the final stage of failure for a firm. A company declares that it has gone bankrupt when at that present moment it does not have enough funds to pay the creditors. It is a global
problem. This paper provides a unique methodology to classify companies as bankrupt or healthy by applying predictive analytics. The prediction model stated in this paper yields better accuracy with standard parameters used for bankruptcy prediction than previously applied prediction methodologies.
Market Research using SPSS _ Edu4Sure Sept 2023.pptEdu4Sure
SPSS Training Related Content. There is practical training on the tool. The PPT is for reference purpose.
For any training need, kindly connect us at partner@edu4sure.com or call us at +91-9555115533.
For more courses at our LMS, you can also refer www.testformula.com
#Edu4Sure #SPSS #Training #Certificate
Case Study 2 SCADA WormProtecting the nation’s critical infra.docxwendolynhalbert
Case Study 2: SCADA Worm
Protecting the nation’s critical infrastructure is a major security challenge within the U.S. Likewise, the responsibility for protecting the nation’s critical infrastructure encompasses all sectors of government, including private sector cooperation. Search on the Internet for information on the SCADA Worm, such as the article located athttp://www.theregister.co.uk/2010/09/22/stuxnet_worm_weapon/.
Write a three to five (3-5) page paper in which you:
1. Describe the impact and the vulnerability of the SCADA / Stuxnet Worm on the critical infrastructure of the United States.
2. Describe the methods to mitigate the vulnerabilities, as they relate to the seven (7) domains.
3. Assess the levels of responsibility between government agencies and the private sector for mitigating threats and vulnerabilities to our critical infrastructure.
4. Assess the elements of an effective IT Security Policy Framework, and how these elements, if properly implemented, could prevent or mitigate and attack similar to the SCADA / Stuxnet Worm.
5. Use at least three (3) quality resources in this assignment. Note: Wikipedia and similar Websites do not qualify as quality resources.
Your assignment must follow these formatting requirements:
· Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions.
· Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length.
The specific course learning outcomes associated with this assignment are:
· Identify the role of an information systems security (ISS) policy framework in overcoming business challenges.
· Compare and contrast the different methods, roles, responsibilities, and accountabilities of personnel, along with the governance and compliance of security policy framework.
· Describe the different ISS policies associated with the user domain.
· Analyze the different ISS policies associated with the IT infrastructure.
· Use technology and information resources to research issues in security strategy and policy formation.
· Write clearly and concisely about Information Systems Security Policy topics using proper writing mechanics and technical style conventions.
DataIDSalaryCompaMidpoint AgePerformance RatingServiceGenderRaiseDegreeGender1GrStudents: Copy the Student Data file data values into this sheet to assist in doing your weekly assignments.1601.053573485805.70METhe ongoing question that the weekly assignments will focus on is: Are males and females paid the same for equal work (under the Equal Pay Act)? 226.80.866315280703.90MBNote: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.334.71.120313075513.61FB457.91.01657 ...
Week 3 Lecture 11
Regression Analysis
Regression analysis is the development of an equation that shows the impact of the
independent variables (the inputs we can generally control) on the output result. While the
mathematical language may sound strange, most of you are quite familiar with regression like
instructions and use them quite regularly.
To make a cake, we take 1 box mix, add 1¼ cups of water, ½ cup of oil, and 3 eggs. All
of this is combined and cooked. The recipe is an example of a regression equation. The output
(or result or dependent variable) is the cake, the inputs (or independent variables) are the inputs
used. Each input is accompanied by a coefficient (AKA weight or amount) that tells us how
“much” of the variable is “used” or weighted into the outcome.
So, in an equation format, this cake recipe might look like:
Y = 1X1 + 1.25X2 + .5X3 + 3X4 where:
Y = cake
X1 = box mix
X2 = cups of water
X3 = cups of oil
X4 = an egg.
Of course, for the cake, the recipe needs to go through the cooking process; while for
other regression equations the outputs need to go through whatever “process” turns the inputs
into the output – this is often called “life.”
Example
With a regression analysis, we can identify what factors influence an outcome. So, with
our Salary issue, the natural question to help us answer our research question of do males and
females get equal pay for equal work would be: what factors influence or explain an individual’s
pay? This is a perfect question for a multi-variate regression. Multi-variate simply means we have
multiple input variables with a single output variable (Lind, Marchel, & Wathen, 2008).
Variables. A regression analysis uses two distinct types of data. The first are variables
that are at least interval level or better (the same as the other techniques we have used so far).
The other is called a dummy variable, a variable that can be coded 0 or 1 indicating the presence
of some characteristic. In our data set, we have two variables that can be used as dummy coded
variables in a regression, Degree and Gender; both coded 0 or 1. In the case of Degree, the 0
stands for having a bachelor’s degree and the 1 stands for having an advanced degree. For
Gender, 0 means a male and 1 means a female. How these are interpreted in a regression output
will be discussed below. For now, the significance of dummy coding is that it allows us to
include nominal or ordinal data in our analysis.
Excel Approach. For our question of what factors influence pay, we will use Excel’s
Regression function found in the Data Analysis section. This function will produce two output
tables of interest. The first table tests to see if the entire regression equation is statistically
significant; that is, do the input variables significantly impact the output variable. If so, we
would then examine the second table – the coefficients used in a regression equation for e.
Multivariate data analysis regression, cluster and factor analysis on spssAditya Banerjee
Using multiple techniques to analyse data on SPSS. A basic software that can easily help run the numbers. Multivariate Data Analysis runs regressions models, factor analyses, and clustering models apart from many more
Explains the concept of autovalidation that can be used to select predictive models with data from designed experiments where a true validation set is not available. Contains three case studies to demonstrate the approach
BUS 308 Week 5 Lecture 3 A Different View Effect Sizes .docxcurwenmichaela
BUS 308 Week 5 Lecture 3
A Different View: Effect Sizes
Expected Outcomes
After reading this lecture, the student should be familiar with:
1. What effect size measures exist for different statistical tests.
2. How to interpret an effect size measure.
3. How to calculate an effect size measure for different tests.
Overview
While confidence intervals can give us a sense of how much variation is in our decisions,
effect size measures help us understand the practical significance of our decision to reject the
null hypothesis. Not all statistically significant results are of the same importance in decision
making. A difference in means of 25 cents is more important with means around a dollar than
with means in the millions of dollars, yet with the right sample size both groups can have this
difference be statistically significant.
Effect size measures help us understand the practice importance of our decision to reject
the null hypothesis.
Excel has limited functions available for us to use on Effect Size measures. We generally
need to take the output from the other functions and generate our Effect Size values.
Effect Sizes
One issue many have with statistical significance is the influence of sample size on the
decision to reject the null hypothesis. If the average difference in preference for a soft drink was
found to be ½ of 1%; most of us would not expect this to be statistically significant. And,
indeed, with typical sample sizes (even up to 100), a statistical test is unlikely to find any
significant difference. However, if the sample size were much larger; for example, 100,000; we
would suddenly find this miniscule difference to be significant!
Statistical significance is not the same as practical significance. If for example, our
sample of 100,000 was 1% more in favor of an expensive product change, would it really be
worthwhile making the change? Regardless of how large the sample was, it does not seem
reasonable to base a business decision on such a small difference.
Enter the idea of Effect Size. The name is descriptive but at the same time not very
illuminating on what this measure does. We will get to specific measures shortly, but for now,
let’s look at how an Effect Size measure can help us understand our findings. First, the name:
Effect Size. What effect? What size? In very general terms, the effect we are monitoring is the
effect that occurs when we change one of the variables. For example, is there an effect on the
average compa-ratio when we change from male to female. Certainly, but not all that much, as
we found no significant difference between the average male and female compa-ratios. Is there
an effect when we change from male to female on the average salary? Definitely. And it is
much larger than what we observed on the compa-ratio means. We found a significant
difference in the average salary for males than females – around $14,000.
The Effect Siz.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.