This document discusses key elements of research design including the purpose of a study, type of investigation, study setting, population, time horizon, and importance of considering research design early. It describes exploratory, descriptive and hypothesis testing purposes. Correlational and causal studies are covered as well as field, lab and contrived settings. Individuals, groups, organizations can be units of analysis. Cross-sectional and longitudinal time horizons are presented. Reliability including stability over time and internal consistency are also summarized.
Inductive and Deductive Approach to Research. Difference between Inductive an...Rohan Byanjankar
What is inductive and Deductive Approach to Research? The difference between Inductive and Deductive Reasoning to Research with clear example, figure and some major differences between them.
A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research with economy in procedure.
It is a conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data.
I’m a young Pakistani Blogger, Academic Writer, Freelancer, Quaidian & MPhil Scholar, Quote Lover, Co-Founder at Essar Student Fund & Blueprism Academia, belonging from Mehdiabad, Skardu, Gilgit Baltistan, Pakistan.
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Exploratory research - Research Methodology - Manu Melwin Joymanumelwin
Exploratory research is research conducted for a problem that has not been clearly defined. It often occurs before we know enough to make conceptual distinctions or posit an explanatory relationship. Exploratory research helps determine the best research design, data collection method and selection of subjects.
Exploratory Research Design - Meaning and MethodsSundar B N
This ppt contains Exploratory Research Design which covers Introduction to Exploratory Research, Meaning of Exploratory Research, Techniques of Exploratory Research, Examples of Exploratory Research, Methods of Designing Exploratory Research
Inductive and Deductive Approach to Research. Difference between Inductive an...Rohan Byanjankar
What is inductive and Deductive Approach to Research? The difference between Inductive and Deductive Reasoning to Research with clear example, figure and some major differences between them.
A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research with economy in procedure.
It is a conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data.
I’m a young Pakistani Blogger, Academic Writer, Freelancer, Quaidian & MPhil Scholar, Quote Lover, Co-Founder at Essar Student Fund & Blueprism Academia, belonging from Mehdiabad, Skardu, Gilgit Baltistan, Pakistan.
I am an academic writer & freelancer! I can work on Research Paper, Thesis Writing, Academic Research, Research Project, Proposals, Assignments, Business Plans, and Case study research.
Expertise:
Management Sciences, Business Management, Marketing, HRM, Banking, Business Marketing, Corporate Finance, International Business Management
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Exploratory research - Research Methodology - Manu Melwin Joymanumelwin
Exploratory research is research conducted for a problem that has not been clearly defined. It often occurs before we know enough to make conceptual distinctions or posit an explanatory relationship. Exploratory research helps determine the best research design, data collection method and selection of subjects.
Exploratory Research Design - Meaning and MethodsSundar B N
This ppt contains Exploratory Research Design which covers Introduction to Exploratory Research, Meaning of Exploratory Research, Techniques of Exploratory Research, Examples of Exploratory Research, Methods of Designing Exploratory Research
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Running Head: WORKPLACE ISSUES
WORKPLACE ISSUES 2
English Homework
Student’s Name
Institutional Affiliation
Professor’s Name
Description of the problems
The two major workplace issues to be discussed in this paper include discrimination and safety within the workplace. Discrimination refers to a situation in which some employees within an organization are highly favoured in comparison to others. For instance, some organizations may favour particular group of people for each and every kind of leadership position at the extent of depriving others this chance even though they may be qualified for the position. Discrimination comes in various ways; in some scenarios it may be viewed from the point of using the organization’s resources whereby some employees may not be allowed to use some resources as a result of discrimination. The issue of discrimination needs to be addressed from the fact that an organization may end up losing potential employees as a result of discrimination. Discrimination is normally brought as a result of having a diversity of employees within a workplace. Currently, researches conducted in different organizations have shown that organizations with a higher diversity of employees will always have great ideas for creativity and also innovation. From the fact that discrimination results into loss of potential employees, this clearly shows that the level of creativity and innovation with as well decrease and therefore making this issue very sensitive and thus needs to be addressed (Acocella, 2007).
The second major problem that needs to be addressed is safety from the fact that organizations deal with various tools and equipment which may result into harmful implications on the employees. Safety may also be looked into in different angles; for instance there is the physical safety in which the employer should ensure each employee is protected against any risk that may end up resulting into harmful effects. Emotional safety is also important and the employee should ensure this by providing a stress free environment for working. Safety is a very important issue to be addressed from the fact that human life is very important. A human life once lost can never be retrieved since no one has the capability of giving another life. This makes this problem very necessary to be addressed.
Solution
s for the problems to be implemented
Strategies need to be implemented to address the issues above. For the case of discrimination, various steps need to be applied to make sure the problem is addressed. The employers needs to sit and discuss deeply with an experienced business attorney who will help in the formulation of discrimination policies for the workplace. The policies should be in line with the discrimination laws for best results. It is from th.
Between Black and White Population1. Comparing annual percent .docxjasoninnes20
Between Black and White Population
1. Comparing annual percent of Medicare enrollees having at least one ambulatory visit between B and W
2. Comparing average annual percent of diabetic Medicare enrollees age 65-75 having hemoglobin A1c between B and W
3. Comparing average annual percent of diabetic Medicare enrollees age 65-75 having eye examination between B and W
4. Comparing average annual percent of diabetic Medicare enrollees age 65-75 having
Students will develop an analysis report, in five main sections, including introduction, research method (research questions/objective, data set, research method, and analysis), results, conclusion and health policy recommendations. This is a 5-6 page individual project report.
Here are the main steps for this assignment.
Step 1: Students require to submit the topic using topic selection discussion forum by the end of week 1 and wait for instructor approval.
Step 2: Develop the research question and
Step 3: Run the analysis using EXCEL (RStudio for BONUS points) and report the findings using the assignment instruction.
The Report Structure:
Start with the
1.Cover page (1 page, including running head).
Please look at the example http://www.apastyle.org/manual/related/sample-experiment-paper-1.pdf (you can download the file from the class) and http://www.umuc.edu/library/libhow/apa_tutorial.cfm to learn more about the APA style.
In the title page include:
· Title, this is the approved topic by your instructor.
· Student name
· Class name
· Instructor name
· Date
2.Introduction
Introduce the problem or topic being investigated. Include relevant background information, for example;
· Indicates why this is an issue or topic worth researching;
· Highlight how others have researched this topic or issue (whether quantitatively or qualitatively), and
· Specify how others have operationalized this concept and measured these phenomena
Note: Introduction should not be more than one or two paragraphs.
Literature Review
There is no need for a literature review in this assignment
3.Research Question or Research Hypothesis
What is the Research Question or Research Hypothesis?
***Just in time information: Here are a few points for Research Question or Research Hypothesis
There are basically two kinds of research questions: testable and non-testable. Neither is better than the other, and both have a place in applied research.
Examples of non-testable questions are:
How do managers feel about the reorganization?
What do residents feel are the most important problems facing the community?
Respondents' answers to these questions could be summarized in descriptive tables and the results might be extremely valuable to administrators and planners. Business and social science researchers often ask non-testable research questions. The shortcoming with these types of questions is that they do not provide objective cut-off points for decision-makers.
In order to overcome this problem, researchers often seek to answer o ...
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While many firms are part of supply chain not all are managed in any truly coordinated fashion.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
9. Study Setting
Field Study
Correlational studies done in organizations are called
Field study
Field Experiment
Studies conducted to establish cause and effect
relationships using the same natural environment in
which employees normally function are called Field
experiment
Lab Experiment
The environment is controlled to study the cause and
effect relationships
12. The importance of research
Design
Why is it important to consider basic research
design issues before conducting the study and
even as early as at the time of formulating the
research question?
Ensures that the purpose for which a study is conducted is
effectively addressed.
Some studies are focused on finding, others might be
interested in “getting some idea” of what is going on, rather
than wanting to know the “absolute truth”.
If the rigor needed can be achieved at only high cost and if
this cost is considered too much, then the goals of
research might have to be revised or even completely
changed.
Thus, thinking through the research design issues at the
early stages helps in averting several problematic issues
later.
13. The importance of research Design
(cont.)
Why is the unit of analysis an integral part
of the research design?
Sampling 30 individuals in an organization when the
unit of analysis is individuals, is not as problematic as
sampling 30 organizations when the unit of analysis is
organizations, or sampling 30 countries when the unit
of analysis is countries. Thus, the unit of analysis
influences other decisions such as the sampling
design, the sample size, data collection methods, etc.
Eg. If you plan to do a research on two countries
stock market behaviour. You would look at National
stock markets not individual stock markets in those
two countries.
14. Exercise
Below are three scenarios. For each, indicate how the
researcher should proceed with the following, giving
reasons:
The purpose of the study
The type of investigation
The extent of researcher interference
The study setting
The time horizon for the study
The unit of analysis.
Scenario A
Ms. Joyce Lynn, the owner of a small business (a woman’s dress boutique), has
invited a consultant to tell her how she is different from similar small businesses
within a 60-mile radius, in regard to her usage of the most modern computer
technology, sales volume, profit margin, and staff training.
15. Exercise Answer (cont.)
This will be a descriptive study (describing how she
compares with the others).
Data will be collected from small businesses on the
use of computers, sales volume, profit margin, and
training programs and comparisons made.
Some of these descriptions might be qualitative, as for
example, in describing training methods.
This will be a field study (using many similar small
businesses), and researcher interference will be
minimal.
It will be a one-shot study, and the unit of analysis will
be small business systems.
17. Nominal Scale
A nominal scale is one that allows the researcher
to assign subjects to certain categories or groups.
What is your department?
O Marketing O Maintenance O Finance
O Production O Servicing O
Personnel
O Sales O Public Relations O
Accounting
What is your gender?
O Male
O Female
19. Ordinal Scale
Not only categorizes variables in such a way as to denote
differences among various categories, it also rank-orders
categories in some meaningful way.
The ordinal scale helps the researcher to determine the
percentage of respondents who consider interaction with
others as most important.
Provide information on how respondents distinguish them by
rank-ordering them
Eg. What is the highest level of education you have
completed?
O Less than High School
O High School/GED Equivalent
O College Degree
O Masters Degree
O Doctoral Degree
21. Interval Scale
Whereas the nominal scale allows us only to
qualitatively distinguish groups by categorizing
them into mutually exclusive and collectively
exhaustive sets, and the ordinal scale to rank-
order the preferences, the interval scale lets
us measure the distance between any two
points on the scale.
It measures the magnitude of the differences
in the preferences among the individual.
22. Interval Scale
Circle the number that represents your feelings at this
particular moment best. There are no right or wrong answers.
Please answer every question.
1. I invest more in my work than I get out of it
disagree completely 1 2 3 4 5 agree completely
2. I exert myself too much considering what I get back in return
disagree completely 1 2 3 4 5 agree completely
3. For the efforts I put into the organization, I get much in return
disagree completely 1 2 3 4 5 agree completely
24. Ratio Scale
Overcomes the disadvantage of the arbitrary
origin point of the interval scale, in that it has
an absolute (in contrast to an arbitrary) zero
point, which is a meaningful measurement
point.
Most powerful of the four scales because it
has a unique zero origin and subsumes all the
properties of the other three scales.
Eg. What is your weight
27. Rating Scale
Dichotomous scale
Is used to elicit a Yes or No answer.
Category scale
Uses multiple items to elicit a single response
Semantic Differential scale
Use to assess respondents’ attitudes toward a particular brand,
advertisement, object or individual.
Numerical Scale
Similar to semantic differential scale but with the numbers on a five or
seven point scale are provided
Itemized rating scale
A five or seven points scale with anchors as needed is provided for each
item and the respondent states the appropriate number on the side of
each item
Likert scale
Designed to examine how strongly subjects agree or disagree with
statements on a five-point scale.