Why Doctorate in Business Administration?

A Doctor of Business Administration or DBA degree is a terminal, business-focused degree that provides practical knowledge that can be directly applied in the workplace. This program will teach you about business theory and practice and will explore problems that are common in any business and in all management roles. DBA programs typically include courses on contemporary business challenges, business management, organizational leadership, business innovation, and strategic business decisions. Doctoral degree programs also include courses in research methods so that students learn to conduct and evaluate research.

Key Features

Discover essential features of MBA in Data Science by College de Paris and enhance your learning journey.

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Course curriculum

    1. Research

    2. Review of Literature

    1. Meaning and importance of Research

    2. Types of Research

    3. Selection and formulation of Research Problem

    4. Meaning of Research Design

    5. Need of Research Design

    6. Features of Research Design

    7. Inductive, Deductive and Development of models

    8. Developing a Research Plan

    9. Exploration, Description, Diagnosis, Experimentation

    10. Determining Experimental and Sample Designs

    11. Analysis of Literature Review

    12. Primary and Secondary Sources

    13. Web sources

    14. Critical Literature Review

    15. Hypothesis

    16. Different Types of Hypothesis

    17. Significance

    18. Development of Working Hypothesis

    19. Null hypothesis

    20. Research Methods: Scientific method vs Arbitrary Method

    21. Logical Scientific Methods: Deductive, Inductive, Deductive-Inductive

    22. Pattern of Deductive

    23. Inductive logical process

    24. Different types of inductive logical methods

    1. Introduction to Quantitative Research Part 1

    2. Introduction to Quantitative Research Part 2

    3. Exploring Quantitative Research Design Part 1

    4. Exploring Quantitative Research Design Part 2

    5. Data Collection for Quantitative Research Part 1

    6. Data Collection for Quantitative Research Part 2

    7. Data Collection for Quantitative Research Part 3

    8. Measurement and Sampling Part 1

    9. Measurement and Sampling Part 2

    10. Measurement and Sampling Part 3

    11. Constructing Statistical Models Part 1

    12. Constructing Statistical Models Part 2

    13. Enhancing Statistical Models Part 1

    14. Enhancing Statistical Models Part 2

    15. Multivariate Analyses Part 1

    16. Multivariate Analyses Part 2

    17. Writing a Quantitative Research Paper Part 1

    18. Writing a Quantitative Research Paper Part 2

    1. Introduction to Qualitative Research

    2. a. Key Elements of Qualitative Research

    3. b. Writing Qualitative Research Question

    4. c. Qualitative Research: Framework

    5. d. Steps to Write a Qualitative Research Paper

    6. e. Ethics for Qualitative Research and IRB

    7. f. Introduction to Design Strategies

    8. g. Data-Collection and Analysis Strategies

    9. h. Introduction to research design

    10. i. Major aspects of research design

    11. Data Collection in Qualitative Research

    12. a. Sources of Evidence: A Comparative

    13. b. Assessment (Forms-Strengths-Weaknesses)

    14. c. Principles of Data Collection

    15. d. Sampling

    16. e. Reliability and Validity

    17. Interviews and Focus Groups Part 1

    18. Interviews and Focus Groups Part 2

    19. Interviews and Focus Groups Part 3

    20. Interviews and Focus Groups Part 4

    21. Interviews and Focus Groups Part 5

    22. Interviews and Focus Groups Part 6

    23. Introduction to Data Analysis

    24. a. An Introduction to Data Analysis

    25. b. First Cycle Coding (Description +Demo)

    26. c. Second Cycle Coding (Description +Demo)

    27. d. Jottings and Analytic Memoing (Description +Demo)

    28. e. Assertions and Propositions (Description +Demo)

    29. f. Within Case and Cross-Case Analysis (Description +Demo)

    30. Data Display and Exploration

    31. a. Matrix and Networks

    32. b. Timing, formatting

    33. c. Extracting Inferences and Conclusions

    34. d. Exploring Fieldwork in Progress

    35. e. Exploring Variables

    36. f. Exploring Reports in Progress

    37. Data Analysis Process - Next Steps

    38. a. Describing Participants

    39. b. Describing Variability

    40. c. Describing Action

    41. d. Ordering by time

    42. e. Ordering by process

    43. f. Explaining Interrelationship-Change

    44. g. Explaining Causation

    45. h. Making Predictions

    46. Verifying Conclusions

    47. a. Tactics to achieve integration among diverse pieces of data

    48. b. Tactics to sharpen understanding by differentiation

    49. c. Tactics of seeing relationships in data abstractly

    50. d. Tactics to assemble a coherent understanding of data

    51. e. Tactics for testing or confirming findings

    52. f. Standards for quality of conclusions

    53. Writing Report and New Technologies

    54. a. Other methods in Qualitative Research

    55. b. Audiences and Effects

    56. c. Different aspects / apa

    57. d. An Introduction to Mixed Methods Research

About this course

  • $24,999.00
  • 101 lessons
  • 0 hours of video content

5-in-1 Course

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  • Certification

  • Assignments

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