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Transform your career by achieving the Doctor of Philosophy (Ph.D.) in your area of specialization | Choose from globally trending specialization areas | Get end-to-end assistance from reverend industry professionals.
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There's a reason that 95% of our alumni undertake 3+ courses as a minimum with Henry Harvin®
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The Doctor of Philosophy (Ph.D.) at Henry Harvin® is designed for researchers with advanced knowledge, practical skills and global perspectives in areas such as management, marketing, mathematics, computer science, psychology, art & design, sustainability and many more. Our specializations offer learners the opportunities to attend seminars, get end-to-end assistance from professionals with an experience of independent research and thesis writing.
Gaining the top most qualification for all streams, a milestone in education no less than a dream for learners and most individuals serving top reputed positions such as that of - CEO, Directors, Scientists, Professors, Managers in different fields.
Ph.d. Specializations offered:
Ph.D. in Management
Ph.D. in Mathematics
Ph.D. in Law
Ph.D. in Psychology
Ph.D. in Arts & Design
Ph.D. in Hospitality & Tourism
Ph.D. in Computer & Technology
Ph.D. in Sustainable Development & Environmental Sciences and many more..
Eligibility Criteria
Only those with a master's degree are qualified to apply for a Ph.D.
You must have a master's degree in a field, course, or stream that is related to the Ph.D. you want to pursue
Become a part of the Elite School of Doctorate Academy of Henry Harvin® and join the 4,60,000+ large Alumni Network Worldwide.
Know the complete offerings of our Doctor of Philosophy (Ph.D.)
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Module 1: Thesis management
a. Scope and Significance
b. Types of Research
c. Research Process
d. Characteristics of Good Research
e. Identifying Research problem
f. Meaning of Sampling Design
g. Steps in sampling
h. Criteria for good sample design
i. Types of Sample Design
j. Probability and non-probability sampling methods
k. Meaning of Measurement
l. Types of scales
a. Data Collection
b. Types of Data
c. Sources of Data Collection
d. Methods of Data collection
e. Constructing questionnaire
f. Establishing, reliability and validity
g. Data processing
h. Coding, Editing and tabulation of data
i. Meaning of Report writing
j. Types of Report
k. Steps of report writing
i. Precautions for writing report
m. Norms for using Tables
n. Charts and diagram
o. Appendix: - Index, Bibliography
Module 2: General Research Methodology
Module 3: Quantitative Research Methods
a. Session Overview
b. RQ Hypothesis Course Context Video
c. What is Quantitative Research?
d. Ethics of Quantitative Research
e. Session Summary
f. Session Overview
g. Introduction to the Scientific Method of Research
h. Comparing Descriptive, Predictive and Prescriptive Research
i. Inductive and Deductive Approaches to Quantitative Research
j. Constructing Models
K. Session Summary
a. Session Overview
b. Fundamentals of Research Design
c. Components of a Research Design
d. Characteristics of a Research Design
e. Session Summary
f. Session Overview
g. Research Design for Experimental Research Studies
h. Research Design for Quasi Experimental Studies
i. Research Design for Non-Experimental Research Studies
j. Evaluating Quantitative Research Design
k. Session Summary
a. Session Overview
b. Defining Surveys
c. Exploring Survey Methods
d. Session Summary
e. Session Overview
f. The Process of Questionnaire Development
g. Designing a Questionnaire
h. Designing Rating Scales
i. The Art of Asking Questions
j. Session Summary
k. Session Overview
l. Tips to Conduct Effective Surveys
m. Ethics of Using Technology in Surveys
n. Session Summary
a. Session Overview
b. What is Measurement?
c. True Score Theory, Estimating Measurement Errors
d. Evaluating Validity of Measures
e. Evaluating Reliability of Measures
f. Session Summary
g. Session Overview
i. Basic Concepts of Sampling
j. Problems and Blases in Sampling
k. Probability Sampling
l. Non-Probability Sampling
m. Session Summary
n. Session Overview
o. Determining the Sample Size
p. Sampling Distribution and Statistical inference
q. Demonstrations on Sampling
r. Session Summary
a. Session Overview
b. Significance of Comparing Means for Analysis
c. What is ANOVA?
d. Types of ANOVA
e. Calculating and Interpreting One-Way ANOVA
f. Session Summary
g. Session Overview
h. Building a Statistical Model
i. Effect of Moderating and Mediating Variables
j. Demonstration on Mediation and Moderation
k. Session Summary
a. Session Overview
b. What is Factor Analysis?
c. Conducting Factor Analysis
d. Demonstration on R: Factor Analysis
e. Interpreting Factor Scores
f. Session Summary
g. Session Overview
h. What is Factorial ANOVA?
i. Dealing with Interaction Effects in Factorial ANOVA
j. Calculating and Interpreting Factorial ANOVA
k. Session Summary
a. Session Overview
b. Multivariate regression
c. MANOVA
d. Logistic Regression
e. Structural Equation Modeling
f. Tree Structured Methods
g. Conjoint Analysis
h. Session Summary
i. Session Overview
j. Time Series
k. Cluster Analysis
l. Session Summary
a. Session Overview
b. Introduction to Formatting the Research Project for Quantitative Research
c. Components of a Quantitative Research Paper
d. Writing the Summary, Background and Purpose of Quantitative Research
e. Writing the Literature Review
f. Detailing your Research Design/Methodology
g. Curating your Results, Analysis and Supplimentary Findings
h. Outlining your Conclusions and Reccomendations
i. Making Appendices
j. Session Summary
k. Session Overview
l. Writing Different Types of Quant Papers
m. Guidelines for Fine Tuning your Research Presentation
n. Session Summary
Module 4: Qualitative Research Methods
a .Key Elements of Qualitative Research
b. Writing Qualitative Research Question
c. Qualitative Research: Framework
d. Steps to Write a Qualitative Research Paper
e. Ethics for Qualitative Research and IRB
f. Introduction to Design Strategies
g. Data-Collection and Analysis Strategies
h. Introduction to research design
i. Major aspects of research design
a. Sources of Evidence: A Comparative
b. Assessment (Forms-Strengths-Weaknesses)
c. Principles of Data Collection
d. Sampling
e. Reliability and Validity
a. An Introduction to Data Analysis
b. First Cycle Coding (Description +Demo)
c. Second Cycle Coding (Description +Demo)
d. Jottings and Analytic Memoing (Description +Demo)
e. Assertions and Propositions (Description +Demo)
f. Within Case and Cross-Case Analysis (Description +Demo)
a. Matrix and Networks
b. Timing, formatting
c. Extracting Inferences and Conclusions
d. Exploring Fieldwork in Progress
e. Exploring Variables
f. Exploring Reports in Progress
a. Describing Participants
b. Describing Variability
c. Describing Action
d. Ordering by time
e. Ordering by process
f. Explaining Interrelationship-Change
g. Explaining Causation
h. Making Predictions
a. Tactics to achieve integration among diverse pieces of data
b. Tactics to sharpen understanding by differentiation
c. Tactics of seeing relationships in data abstractly
d. Tactics to assemble a coherent understanding of data
e. Tactics for testing or confirming findings
f. Standards for quality of conclusions
a. Other methods in Qualitative Research
b. Audiences and Effects
c. Different aspects / apa
d. An Introduction to Mixed Methods Research
Know the complete offerings of our Doctor of Philosophy (Ph.D.)
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Research
Writing
Editing
PowerPoint present
Data Analysis
Critical thinking
Technical Skills
Project management
Teaching & Mentorship
English, German
30+ Years
Bussiness Management
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PhD is the short form of Doctor of Philosophy and to be eligible, the students are required to have completed their Master’s degree. Aspirants need to possess a valid master’s degree to be eligible to pursue a PhD programme. Candidates can pursue a PhD programme in any stream. In a PhD course, aspirants need to select a topic or a subject and do in-depth research on it and answer any queries related to the topic/ subject.
A PhD (Doctor of Philosophy) degree is considered a terminal degree. It has been recognized as a valuable form of degree and can be your highest achievement.
It gives you the satisfaction of knowing that you have completed all those years of study with dedication and hard work, which makes it worth taking up this challenge in the first place.
You will also learn new skills along the way (such as writing). If your aim is to become an academic in any field, then this would be ideal for you because it teaches students how they should conduct themselves while working on projects at their workplace or institution where they teach others who may not have gone through similar experiences before!
A PhD (Doctor of Philosophy) is a research-based degree. It is awarded after the successful completion of a research project, which must be submitted to an evaluator for peer review.
The PhD Admissions are awarded on the basis of the quality of research and not on how many papers you write or how many times your papers are cited in other work done by other people.
In other words, you don’t get credit for writing papers; instead, your dissertation will be evaluated based on its quality as well as whether it makes sense or not within various fields within which it was written
There are few options if you miss a class. You get free access to LMS where you can find course content in an organized form. You view recorded class sessions.
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