This document discusses different types of research designs, specifically experiments. It covers key components of experimental designs like independent and dependent variables, experimental and control groups, pre-testing and post-testing. Various threats to internal and external validity are explained, such as history, maturation, testing, instrumentation. Different experimental designs are presented like one-group pre-test post-test, static-group comparison. Strengths and weaknesses of experiments are that they allow manipulation and control but can lack generalizability and be expensive. Validity is important to evaluate whether conclusions can be supported.
Quantitative Methods of Research-Intro to research
Once a researcher has written the research question, the next step is to determine the appropriate research methodology necessary to study the question. The three main types of research design methods are qualitative, quantitative and mixed methods.
Quantitative research involves the systematic collection and analysis of data.
Quantitative Methods of Research-Intro to research
Once a researcher has written the research question, the next step is to determine the appropriate research methodology necessary to study the question. The three main types of research design methods are qualitative, quantitative and mixed methods.
Quantitative research involves the systematic collection and analysis of data.
Research Design (Research Types, Quantitative Research Design and Qualitative...Alam Nuzhathalam
An overview of Research Design: Definition, Classification of Research Design, Experimental Research Design, Non Experimental Research Design, Qualitative Research Design, Quantitative Research Design..
Research Design (Research Types, Quantitative Research Design and Qualitative...Alam Nuzhathalam
An overview of Research Design: Definition, Classification of Research Design, Experimental Research Design, Non Experimental Research Design, Qualitative Research Design, Quantitative Research Design..
Bivariate RegressionRegression analysis is a powerful and comm.docxhartrobert670
Bivariate Regression
Regression analysis is a powerful and commonly used tool in business research. One important step in regression is to determine the dependent and independent variable(s).
In a bivariate regression, which variable is the dependent variable and which one is the independent variable?
· What does the intercept of a regression tell? What does the slope of a regression tell?
· What are some of the main uses of a regression?
Provide an example of a situation wherein a bivariate regression would be a good choice for analyzing data.
Justify your answers using examples and reasoning. Comment on the postings of at least two peers and state whether you agree or disagree with their views.
Types of Regression Analyses
There are two major types of regression analysis—simple and multiple regression analysis. Both types consist of dependent and independent variables. Simple linear regression has two variables—dependent and independent. Multiple regression consists of dependent variable and two or more independent variables.
· How does a multiple regression compare with a simple linear regression?
· What are the various ways to determine what variables should be included in a multiple regression equation?
· Compare and contrast the following processes: forward selection, backward elimination, and stepwise selection.
Justify your answers using examples and reasoning.
Critical Analysis
Critical analysis involves thinking about what you're reading and interpreting it and evaluating it.
Critical analysis of the books, papers, articles, and research that you read for your classes is an important skill. It is also an important skill in the workplace. Generally speaking, when you engage in critical analysis, you do the following things:
Critical Analysis Principles
Example Questions or Statements
Identify and challenge starting assumptions
Questions:
Did the authors base their conclusions on the appropriate facts? Did the author consider the social conditions of the appropriate time period? Did the author use the appropriate resources to adequately address the question?
Example:
The author used widely-held social beliefs in 2007 to explain social changes that occurred in 1910.
Distinguish facts from opinions, and distinguish objectivity from bias
Questions:
Has the author stated the facts from a research study, or did he just give us his opinion? Has the author explained the situation fairly? Did the author allow her personal opinion or involvement to prejudice her explanation and cloud her judgment?
Example:
This drug has been reported to be an effective treatment. However, all the reports come from the company that created and is selling the drug. There are no independent reports from uninvolved parties that support this claim.
Make inferences from the facts
Questions:
What do these findings mean? What are the implications of these findings? Do these findings impact other areas or concepts? Did the author interpret the findings in a reas ...
This lecture looks at:
- An explanation of each of the steps in the research process flowchart
- Types of data
- Generating and testing theories
- Measurement error
- Validity
- Reliability
Use the Capella library to locate two psychology research articles.docxdickonsondorris
Use the Capella library to locate two psychology research articles: a quantitative methods article and a qualitative methods article. These do not need to be on the same topic, but if you have a research topic in mind for your proposal (see Assessment 5), you may wish to pick something similar for this assessment. Read each article carefully.
Then, in a 2–3-page assessment, address the following elements:
1 Summarize the research question and hypothesis, the research methods, and the overall findings.
2 Compare the research methodologies used in each study. In what ways are the methodologies similar? In what ways are they different? (Be sure to use the technical psychological terms we are studying.)
3 Describe the sample and sample size for each study. Which one used a larger sample and why? How were participants selected?
4 Describe the data collection process for each study. What methods were used to collect the data? Surveys? Observations? Interviews? Be specific and discuss the instruments or measures fully—what do they measure? How is the test designed?
5 Summarize the data analysis process for each study. How was the data analyzed? Were statistics used? Were interviews coded?
6 In conclusion, craft 1–2 paragraphs explaining how these two articles illustrate the main differences between quantitative and qualitative research.
Additional Requirements
· Written communication: Written communication should be free of errors that detract from the overall message.
· APA formatting: Your assessment should be formatted according to APA (6th ed.) style and formatting.
· Length: A typical response will be 2–3 typed and double-spaced pages.
Font and font size: Times New Roman, 12 point.
Research Methods
There are many different types of research studies, and the type of study that is done depends very much on the research question. Some studies demand strictly numerical data, such as a comparison of GPA among different college majors or weight loss among different types of eating programs. Others require more in-depth data, like interview responses. Such studies might include the lived experience of people that have been through a terrorist attack or understanding the experience of being physically disabled on a college campus. While there are a number of different types of studies that can be done, all of them fall under two basic categories: quantitative and qualitative.
Quantitative Research
Quantitative research deals with numerical data. This means that any topic you study in a quantitative study must be quantifiable—grades, weight, height, depression, and intelligence are all things that can be quantified on some scale of measurement. Quantitative data is often considered hard data—numbers are seen as concrete, irrefutable evidence, but we have to take into account a number of factors that could impact such data. Errors in measurement and recording of such data, as well as the influence of other factors outside those in the study, make for ...
Experimental and Quasi-Experimental DesignsChapter 5.docxelbanglis
Experimental and Quasi-Experimental Designs
Chapter 5
*
Introduction
Experiments are best suited for explanation and evaluation research
Experiments involve:
Taking action
Observing the consequences of that action
Especially suited for hypothesis testing
Often occur in the field
The Classical Experiment Classical experiment: a specific way of structuring researchInvolves three major components:
Independent variable and dependent variable
Pretesting and posttesting
Experimental group and control group
Independent and Dependent Variables
The independent variable takes the form of a dichotomous stimulus that is either present or absent
It varies (i.e., is independent) in our experimental process
The dependent variable is the outcome, the effect we expect to see
Might be physical conditions, social behavior, attitudes, feelings, or beliefs
Pretesting and Posttesting
Subjects are initially measured in terms of the DV prior to association with the IV (pretested)
Then, they are exposed to the IV
Then, they are remeasured in terms of the DV (posttested)
Differences noted between the measurements on the DV are attributed to influence of IV
Experimental and Control Groups
Experimental group: exposed to whatever treatment, policy, initiative we are testing
Control group: very similar to experimental group, except that they are NOT exposed
Can involve more than one experimental or control group
If we see a difference, we want to make sure it is due to the IV, and not to a difference between the two groups
Placebo
We often don’t want people to know if they are receiving treatment or not
We expose our control group to a “dummy” independent variable just so we are treating everyone the same
Medical research: participants don’t know what they are taking
Ensures that changes in DV actually result from IV and are not psychologically based
Double-Blind Experiment
Experimenters may be more likely to “observe” improvements among those who received drug
In a double-blind experiment, neither the subjects nor the experimenters know which is the experimental group and which is the control group
Selecting Subjects
First, must decide on target population – the group to which the results of your experiment will apply
Second, must decide how to select particular members from that group for your experiment
Cardinal rule – ensure that experimental and control groups are as similar as possible
RandomizationRandomization: produces an experimental and control group that are statistically equivalentEssential feature of experimentsEliminates systematic bias
Experiments and Causal Inference
Experimental design ensures:
Cause precedes effect via taking posttest
Empirical correlation exists via comparing pretest to posttest
No spurious 3rd variable influencing correlation via posttest comparison between experimental and control groups, and via randomization
Example of Research Using an Experimental Design
Researchers at the University of Marylan ...
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
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
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Why are attacks on smart factories rising?
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Download the full report from here:
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Welocme to ViralQR, your best QR code generator.ViralQR
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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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
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The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
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Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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.
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