This document outlines the syllabus for a biostatistics course offered at Nova Southeastern University. The course is designed to enable students to apply statistical methods to solve problems in healthcare research. It will cover topics like experimental design, hypothesis testing, probability distributions, and the analysis of variance. Students will learn to generate, interpret, and evaluate clinical research. They will complete homework problem sets, exams, and readings from the required textbook to earn a letter grade for the course.
This presentation is on using repeated measures design in the area of social sciences, behavioural sciences, management, sports, physical education etc.
This presentation discusses the procedure involved in two-way mixed ANOVA design. The procedure has been discussed by solving a problem using SPSS functionality.
This presentation is on using repeated measures design in the area of social sciences, behavioural sciences, management, sports, physical education etc.
This presentation discusses the procedure involved in two-way mixed ANOVA design. The procedure has been discussed by solving a problem using SPSS functionality.
This presentation discusses in detail about the procedure involved in two-factor MANOVA. Both the analysis i.e. multivariate as well as univariate has been shown in this design by solving an illustration using SPSS software.
Analysis of Variance and Repeated Measures DesignJ P Verma
This presentation discusses the basic concept used in analysis of variance and it shows the difference between independent measures ANOVA and Repeated measures ANOVA
This presentation discusses the application of discriminant analysis in sports research. One can understand the steps involved in the analysis and testing its assumptions.
Each technological age has been marked by a shift in how the industrial platform enables companies to rethink their business processes and create wealth. In the talk I argue that we are limiting our view of what this next industrial/digital age can offer because of how we read, measure and through that perceive the world (how we cherry pick data). Companies are locked in metrics and quantitative measures, data that can fit into a spreadsheet. And by that they see the digital transformation merely as an efficiency tool to the fossil fuel age. But we need to stretch further…
This presentation discusses in detail about the procedure involved in two-factor MANOVA. Both the analysis i.e. multivariate as well as univariate has been shown in this design by solving an illustration using SPSS software.
Analysis of Variance and Repeated Measures DesignJ P Verma
This presentation discusses the basic concept used in analysis of variance and it shows the difference between independent measures ANOVA and Repeated measures ANOVA
This presentation discusses the application of discriminant analysis in sports research. One can understand the steps involved in the analysis and testing its assumptions.
Each technological age has been marked by a shift in how the industrial platform enables companies to rethink their business processes and create wealth. In the talk I argue that we are limiting our view of what this next industrial/digital age can offer because of how we read, measure and through that perceive the world (how we cherry pick data). Companies are locked in metrics and quantitative measures, data that can fit into a spreadsheet. And by that they see the digital transformation merely as an efficiency tool to the fossil fuel age. But we need to stretch further…
To Analysing Data for Genomics is designed to provide you with basic knowledge and skills to independently design, execute and explain the results of data analysis in the context of a genomics/proteomics experiment.
See More: https://bit.ly/2KWDgBG
This presentation is meant to help choose the appropriate statistical analysis for IBDP Biology IAs. It was created as support for teachers but also useful for students.
Within the presentation, we discuss different types of biological data, and how to describe and analyse it using mathematics.
An Adaptive Evaluation System to Test Student Caliber using Item Response TheoryEditor IJMTER
Computational creativity research has produced many computational systems that are
described as creative [1]. A comprehensive literature survey reveals that although such systems are
labelled as creative, there is a distinct lack of evaluation of the Creativity of creative systems [1].
Nowadays, a number of online testing websites exist but the drawback of these tests is that every
student who gives a particular test will always be given the same set of questions irrespective of their
caliber. Thus, a student with a very high Intelligence Quotient (IQ) may be forced to answer basic
level questions and in the same way weaker students may be asked very challenging questions which
they cannot response. This method of testing results into a wastage of time for the high IQ students
and can be quite frustrating for the weaker students. This would never benefit a teacher to understand
a particular student’s caliber for the subject under Consideration. Each learner has different learning
status and therefore different test items should be used in their evaluation. This paper proposes an
Adaptive Evaluation System developed based on an Item Response Theory and would be created for
mobile end user keeping in mind the flexibility of students to attempt the test from anywhere. This
application would not only dynamically customize questions for students based on the previous
question he/she has answered but also by adjusting the degree of difficulty for test questions
depending on student ability, a teacher can acquire a valid & reliable measurement of student’s
competency.
This is a North Central University paper about analyzing quasi-emperimental designs. It is written in APA format, includes references, and is graded an instructor.
12/24/16, 11(23 AMModule 8: Mastery Exercise | Schoology
Page 1 of 3https://app.schoology.com/assignment/885059160/assessment
Statistics and SPSS: WINTER16-B-8-MIS445-1
Module 8: Mastery Exercise
Question 1 (1 point)
In a body weight loss trial, the calculated F-value was 5.91 and the tabulated F (0.95, 3, 16) = 3.2; what should be the conclusion?
a Since F-calculated, 5.91 is bigger than F-tabulated, 3.2, therefore, reject the null hypothesis that dietary treatments were
similar in reducing body weight.
b Accept the null hypothesis of no dietary treatments effects.
c Nothing can be calculated.
Question 2 (1 point)
Some of the assumptions, for the data used in ANOVA are _________.
a data follows a normal distribution
b population means have similar variance (or standard deviation)
c samples are randomly selected and independent of one another
d all of the above
Question 3 (1 point)
Researchers wish to examine the effectiveness of a new weight-loss pill. A total of 200 obese adults are randomly assigned to one of
four conditions: weight-loss pill alone, weight-loss pill with a low-fat diet, placebo pill alone, or placebo pill with a low-fat diet. The
weight loss after six months of treatment is recorded in pounds for each subject. To analyze this data, you would use __________.
a a z-test
b a t-test
c an ANOVA F test
d a Chi-square test
Question 4 (1 point)
A medical research team is interested in determining whether a new drug has an effect on creatine kinase (CK), which is often assayed in
blood tests as an indicator of myocardial infarction. A random selection of 20 patients from a pool of possible subjects is selected, and
each subject is given the medication. The subjects’ CK levels are observed initially, after three (3) weeks, and again after six (6) weeks.
The purpose is to study the CK levels over time. Here is a summary of the findings:
Time (weeks) Mean CK level (U/L) Standard devia9on (U/L)
0 121 20.37
3 106 16.09
6 100 10.21
In this example, we notice that ____________.
a the data shows very strong evidence of a violation of the assumption that the three populations have the same standard
deviation
Questions 1-10 of 10 | Page 1 of 1
https://app.schoology.com/course/885058852
12/24/16, 11(23 AMModule 8: Mastery Exercise | Schoology
Page 2 of 3https://app.schoology.com/assignment/885059160/assessment
b ANOVA cannot be used on this data because the sample sizes are much too small
c the assumption that the data is independent for the three time points is unreasonable because the same subjects were
observed each time
d there is no reason not to use ANOVA in this situation
Question 5 (1 point)
The degree of freedom for the total number of observations in ANOVA will be ________.
a total number of observations less one
b total number of observations less two
c total number of observations plus one
d total number of observations plus two
Question 6 (1 point)
How much corn should be plante ...
Experiments
A Quick History of Design of Experiments
Why We Use Experimental Designs
What is Design of Experiment
How Design of Experiment contributes
Terminology
Analysis Of Variation (ANOVA)
Basic Principle of Design of Experiments
Some Experimental Designs
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Stats I Syllabus (Hph 7300)Ransdell Winter2010
1. Nova Southeastern University
HPH 7300—CRN 35894
BIOSTATISTICS I
Winter 2010
SYLLABUS
I. DESCRIPTION: First of a two-course sequence focusing on inferential statistics
for students interested in understanding quantitative research in
the health sciences. It is designed to enable students to apply
experimental-design models toward solving practical problems
and improving the efficiency of formulating and providing
healthcare services.
II. GOAL: Educate students to generate, interpret, and evaluate clinical,
biomedical, and healthcare-services research.
III. PREREQUISITE: Introductory-level statistics course.
IV. OBJECTIVES: After successful completion, students will be able to:
1. match empirical research questions to statistical methods.
2. apply hypothesis-testing models to experimental and
quasi-experimental research questions.
3. use appropriate probability distributions, including z, t,
and F.
4. estimate parameters with adequate confidence intervals.
5. test hypotheses using a wide variety of statistical models.
6. use different versions of analysis of variance as applied to
the health sciences.
V. INSTRUCTOR: Sarah Ransdell, PhD
Office Tel. (954)262-1208, (800)356-0026, ext. 21208.
e-mail: ransdell@nova.edu If you want to talk by phone,
set this up first by email. I will be online at least once every 6-
10 hours, especially around assignment due dates.
VI. MEETINGS: Presentation and discussion of course material will be held
within WebCT. Students are responsible for all posted
materials. Discussion is to everyone, email is one to one, use
discretion. There will also be Tegrity video recordings and a
posting when they are available.
1. Course material presentations will focus on purpose,
nature, composition, and application of different statistical
models.
2. Homework will be devoted to working out statistical
problems using SPSS, your textbook, and your other
course materials.
VII. HOMEWORK: Six problem sets will be assigned. They are due about one
week later, see syllabus schedule. In addition, students will be
expected to complete textbook and course material reading
prior to homework submission.
VIII. CREDIT: Three credit hours.
2. IX. TEXTBOOK and SOFTWARE: Wayne W. Daniel, Biostatistics: A Foundation
for Analysis in the Health Sciences, New York: John Wiley & Sons, Inc., 9th edition,
2009, ISBN: 978-0-470-10581-8. You will also need access to SPSS 17.0 for Win or
Mac. Please order these ASAP so that you have it for the first week. You may also purchase
Green and Salkind, Using SPSS for Windows and Macintosh, 5th edition (NJ: Pearson), ISBN:
9780131890251.
X. POLICIES: 1.
Policies related to attendance, civility, and grades will be
in accord with HPD student policies, see Student Manual.
2. A grade of incomplete is available at the instructor’s
discretion. Students are expected to remove the
incomplete within two semesters or by the end of the next
semester in which the course is offered again.
3. No credit will be given for assignments that are not sent to
the Assignment dropbox by Sundays at 9pm the week they
are assigned. Each problem set is worth 5 pts.
4. All assignments are cumulative.
5. Academic dishonesty in the form of cheating, plagiarism,
etc. constitute transgressions against the honor code and
may bring penalties ranging from severe reprimand to
recommendation for expulsion from the program,
including failing the entire course or part of it.
XI. GRADING: Mid-term exam (15pts) Problem sets (30pts)
Final exam (15pts)
HPD Numeric Grading – Equivalent Alpha Grade
90 – 100% of out 60pts A
80 – 89 B
00 – 79 F
XII. SCHEDULE:
Week Date Weekly Topic Assignment
begins Reading
(8th ed.)
(9th ed.)
1 1/4 1/all Course organization / WebCT / Tegrity/ SPSS WebCT
2/15-34 Statistics in perspective tutorial,
3/all Probability load SPSS
2/19-37
2 1/11 2/35-51 Measures of location or central tendency
2/38-54 Measures of dispersion
Relationship between both types of measures
3 1/19 4/all Normal vs. skewed distributions Problem Set
4/93-134 The z distribution 1 Due 1/17,
Estimation of percentiles 9pmEastern
3. 4 6/156-186 The t distribution
1/25 7/211-218 Confidence intervals
6/62-189, Hypothesis testing
7/215-222
5 2/1 5/129-140 One-population tests: Means Problem Set
6/196-201 One-population tests: Proportions 2 Due 1/31,
7/218-234 The F distribution 9pmEastern
7/258-260
7/270-278
5/135-146
6/199-203
7/223-237
6 2/8 5/140-152 Two-population tests: Paired observations
7/235-257 Two-population tests: Unpaired observations
7/260-270 Equal-size vs. unequal-size data sets
7/258-201
7/273-280
none
2/15 Mid-term Exam due 2/14, Sunday 9pm Eastern
7
Happy Valentines Day!
Problem Set
8 2/22 8/303-321 Multiple population comparisons
3 Due 2/28
8/305-322 The CRD(Completely Randomized Design) model
9pmE
One-way analysis of variance
9 3/1 8/322-352 Post-hoc tests Problem Set
8/322-353 The RCBD (Randomized Complete Block Design) 4 Due 3/7,
model without replications 9pmE
Two-way analysis of variance (without replicat.)
10 3/8 Comparison of CRD and RCBD models
The RCBD model with replications
Two-way analysis of variance (with replications)
11 3/15 The NHC model
Multiway analysis of variance
Multiple hierarchies of sources of variation
12 3/22 8/352- Factorial experiments Problem Set
368 Analysis of variance for factorial experiments 5 Due 3/28
8/353-36 Integration of ANOVA models 9pmEastern
8
4. 13 3/29 12/593-6 The chi-square distribution
46
12/593-6
48
14 4/5 13/680-7 Non-parametric statistical comparisons Problem Set
29 6 Due 4/11
13/683-7 9pmE
30
15 4/12 Review for Final exam
Final Exam due 4/18 Sunday 9pm Eastern
