Correlational research investigates relationships between two variables without manipulating either variable. It can be used for explanatory purposes to help explain behaviors, or for prediction purposes to predict outcomes. Common correlational techniques include scatter plots, regression analysis, multiple regression, and factor analysis. Threats to internal validity like subject characteristics, location, instrumentation, and mortality must be evaluated. The basic steps in correlational research are problem selection, sampling, instrumentation, design, data collection, and evaluating threats to validity.
Topic: What is Reliability and its Types?
Student Name: Kanwal Naz
Class: B.Ed 1.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
Topic: What is Reliability and its Types?
Student Name: Kanwal Naz
Class: B.Ed 1.5
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
It talks about the different types of validity in assessment.
* Face Validity
* Content Validity
* Predictive Validity
* Concurrent Validity
* Construct Validity
Interview Method for Qualitative ResearchPun Yanut
Interview is the verbal conversation between two people with the objective of collecting relevant information for the purpose of research.
Interviewing, a method for conducting research, is a technique used to understand the experiences of others.
McNamra (1999), the interviewer can pursue in-depth information around the topic.
Interview may be useful as follow-up to certain respondent
Topic: Principles of Assessment
Student Name: Syed Faizan Ali
Class: B.Ed. Hons Elementary Part (II)
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
Characteristics Of A Good Test, Measuring Instrument (Test)
Validity, Nature/Characteristics Of Validity
Types/Approaches To Test Validation
Validity: Advantages And Disadvantages
Reliability, Nature/Characteristics
Types Of Reliability
Methods Of Estimating Reliability
Practicality/Usability
Objectivity
Norms
this is about the different theories related to planning in management practices. useful for freshers to mgmt. studies and also may be for Entrepreneur
It talks about the different types of validity in assessment.
* Face Validity
* Content Validity
* Predictive Validity
* Concurrent Validity
* Construct Validity
Interview Method for Qualitative ResearchPun Yanut
Interview is the verbal conversation between two people with the objective of collecting relevant information for the purpose of research.
Interviewing, a method for conducting research, is a technique used to understand the experiences of others.
McNamra (1999), the interviewer can pursue in-depth information around the topic.
Interview may be useful as follow-up to certain respondent
Topic: Principles of Assessment
Student Name: Syed Faizan Ali
Class: B.Ed. Hons Elementary Part (II)
Project Name: “Young Teachers' Professional Development (TPD)"
"Project Founder: Prof. Dr. Amjad Ali Arain
Faculty of Education, University of Sindh, Pakistan
Characteristics Of A Good Test, Measuring Instrument (Test)
Validity, Nature/Characteristics Of Validity
Types/Approaches To Test Validation
Validity: Advantages And Disadvantages
Reliability, Nature/Characteristics
Types Of Reliability
Methods Of Estimating Reliability
Practicality/Usability
Objectivity
Norms
this is about the different theories related to planning in management practices. useful for freshers to mgmt. studies and also may be for Entrepreneur
Causal Comparative Research At least two different groups are compared on a dependent variable or measure of performance (called the “effect”) because the independent variable (called the “cause”) has already occurred or cannot be manipulated. Dependent variable-the change or difference occurring as a result of the independent variable. Independent variable- an activity of characteristic believed to make a difference with respect to some behavior.
Systematic review and meta analysis is considered as the highest body of evidence in research evidence hierarchy. Often misunderstood or skipped over, this powerful tool can broaden our understanding on a specific topic and form basis of practicing evidence based medicine for us.
I presented systematic review and meta analysis as part of my PG seminar and got a good feedback. Now I wanted to share the presentation for a broader audience.
Any kind of constructive feedback is welcome.
Dr. Anik Chakraborty
JR3, Dept. Of Community Medicine
Pt. B. D. Sharma PGIMS, Rohtak
Tribhuvan University, Nepal
Masters in Arts
Population Studies
Research method in Population analysis
Validity and Threats to validity
If any mistakes, feel free to suggest me for the improvement.
Hope its useful for reference
thank You :)
All the concepts related to research design are covered in this PPT Presentation.Research Design being an integral and crucial part of Research majorly deals with Parametric and non-parametric test, Type 1 and type 2 error, level of significance etc.It helps in ascertaining which research technique is used in which situation.
Research is a systematic and scientific method of finding solutions by obtaining various types of data and systematic analysis of the multiple aspects of the issues related.
The techniques or the specific procedure which helps to identify, choose, process, and analyze information about a subject is called Research Methodology
Experimental design is a statistical tool for improving product design and solving production problems.
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/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
2. THE NATURE OF
CORRELATIONAL RESEARCH
• Sometimes called associational research
• It investigates the possibility of relationships
between only two variables
• Also sometimes referred to as a form of
descriptive research
• Describes the degree to which two or more
quantitative variables are related
3. PURPOSES OF CORRELATIONAL
RESEARCH
• Two basic purposes
1. Help explain important human behaviors
(Explanatory Studies)
2. Predict likely outcomes
(Prediction Studies)
4. EXPLANOTARY STUDIES
• Researchers often investigate a number of
variables they believe are related to a more
complex variable.
• Unrelated variables dropped from further
consideration
• Most researchers most probably trying to
gain some ideas about cause and effect
• However it does not establish cause and
effect
5. PREDICTION STUDIES
• Predict a score on one variable if a score on
the other variable is known
• Determine the predictive validity of
measuring instruments
• Predictor Variable; variable that is used to
make the prediction
• Criterion Variable; variable about which the
prediction is made
6. Using Scatter plots to Predict a Score
• We can use the scatter plots to find a
correlation between the variables
• correlational research.pptx
7. A simple Prediction Equation
• Used to express the regression line
• We gain confidence in using the
Y'
prediction equation to make future
predictions if there is a close similarity
between two results
8. MORE COMPLEX
CORRELATIONAL TECHNIQUES
1. Multiple Regressions; technique that
enables researchers to determine a
correlation between a criterion variable
• The best combination of two or more
predictor variables
9. 2. The Coefficient of Multiple Correlation
• Symbolized by R; indicates the strength of
the correlation between the combination of
the predictor variables and the criterion
variables.
• multiple correlation.jpg
• The higher R is, the more reliable a
prediction will be
10. 3. The Coefficient of Determination
• The square of the correlation between a
predictor and a criterion variable
• Indicates the percentage of the variability
among the criterion scores that can be
attributed to differences in the scores on
the predictor variable
11. 4. Discriminant Function Analysis
• Technique used when the technique of
multiple regression cannot be used when
the criterion variable is categorical
5. Factor Analysis
• Technique that allows a researcher to
determine if many variables can be
described by a few factors.
12. BASIC STEPS IN
CORRELATIONAL RESEARCH
1. Problem Selection
• Three major types of problems;
a. is variable X related to variable Y?
b. how well does variable P predict variable C?
c. What are the relationship among a large
number of variables and what predictions can
be made?
13. 2. Sample
• Should be selected carefully, and if
possible, randomly.
• Not less than 30.
3. Instruments
• Most correlational studies involve the
administration of some types of
instruments (tests, questionnaire, and so
on).
14. 4. Design and Procedures
• Design used quite straightforward.
5. Data Collection
• Data on both variables will usually be
collected in a short time.
• Instruments used are administered in a
single session or two sessions
15. THREATS TO INTERNAL
VALIDITY
• There are some threats identified in
conducting correlational research
1. Subject Characteristics
• Individuals or groups have two or more
characteristics; might be a cause of
variation in the other two variables.
16. 2. Location
• Location is different for different subject
• One location may be more comfortable
compared to others
3. Instrumentation
• Instrument decay; care must be taken to ensure
the observers don’t become tired, bored or
inattentive
• Data collector characteristics; different
gender, age or ethnicity may affect specific
response
17. 4. Testing
• Experience of responding to the first
instrument may influence subject responses
to the second instrument
5. Mortality
• Loss of subjects may make a relationship
more (or less) likely in the remaining data
18. EVALUATING THREATS TO
INTERNAL VALIDITY
• Follows a procedure similar to the
experimental research.
1. Subject Characteristics
• Four of many possible characteristics
a. Severity of disability
b. Socioeconomic level of parents
c. Physical strength and coordination
d. Physical appearance
19. 2. Mortality
• Loss of subjects can be expected to reduce
magnitude of correlation
3. Location
• Threats could be controlled by
independently assessing the job-site
environments.
20. 4. Instrumentation
• Instrument decay; observations should
scheduled
• Data collector characteristics; interaction of
data collectors and supervisors is a
necessary parts
• Data collector bias; observers should have
no knowledge of job ratings