Name: Thakur Business Analytics for Decision Making MBA 2nd Sem PTU
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Thakur Business Analytics for Decision Making MBA 2nd Sem PTU

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Business Analytics for Decision Making – MBA 2nd Sem PTU by Dr. Sanjiv Kumar Tiwary (Thakur Publications) is a comprehensive guide tailored for MBA Semester II students of Punjab Technical University. Covering key topics like statistics, sampling, hypothesis testing, regression analysis, and time series forecasting, this book provides a strong foundation in business analytics. With clear explanations, practical examples, and a 2019 question paper for exam practice, it ensures effective learning and exam readiness. Ideal for students and professionals, this book is a must-have for mastering data-driven decision-making in business.

Business Analytics for Decision Making is an essential book for MBA Semester II students of Punjab Technical University (PTU). This book is meticulously crafted to help management students develop a strong foundation in business analytics, statistical methods, and data-driven decision-making. It covers all critical topics as per the PTU syllabus, making it an indispensable resource for both learning and exam preparation.

Key Features:

1. Comprehensive Coverage for MBA Semester II: Specifically designed for Punjab Technical University (PTU) MBA 2nd Semester students, this book aligns perfectly with the prescribed syllabus.

2. Practical Approach to Business Analytics: Provides a clear understanding of statistical and analytical techniques essential for data-driven decision-making in business.

3. Structured Learning: Well-organized units with detailed explanations, examples, and case studies to reinforce key concepts.

4. Exam-Oriented Content: Includes a previous year’s question paper (2019) to help students prepare effectively for exams.

5. Authoritative Content: Written by Dr. Sanjiv Kumar Tiwary, an expert in the field, ensuring academic rigor and practical relevance.

Why Choose This Book?

1. Syllabus-Aligned: Perfectly matches the PTU MBA Semester II curriculum.

2. Concept Clarity: Simplified explanations with real-world business applications.

3. Exam Ready: Chapter-wise summaries and previous year’s papers for thorough revision.

4. Trusted Author: Authored by Dr. Sanjiv Kumar Tiwary, ensuring high-quality, reliable content.

Ideal For:

MBA Semester II students of PTU

Business professionals seeking to enhance analytical skills

Professors and tutors looking for a structured teaching resource

Conclusion

In summary, Dr. Sanjiv Kumar Tiwary's "Business Analytics for Decision Making" is a must-have resource for MBA Semester II students looking to enhance their analytical skills for effective business decision-making. With its comprehensive coverage of essential topics, practical applications, and guided learning, this book equips you to thrive in a data-driven world. Invest in your future and empower yourself with the knowledge and skills this book offers. Add "Business Analytics for Decision Making" to your cart today, and take the first step towards becoming a data-savvy business leader.

Have Doubts Regarding This Product ? Ask Your Question

Q1

Is this book strictly aligned with the PTU MBA Semester II syllabus?

A1

Yes, the book is meticulously designed to cover all topics as per Punjab Technical University’s MBA 2nd-semester syllabus (2021 onwards).
Q2

Does this book include practical examples or case studies?

A2

Yes, it features real-world business applications, examples, and case studies to reinforce analytical concepts.
Q3

Does the book include solved numerical problems for practice?

A3

Yes, it provides step-by-step solved problems, especially in regression analysis, hypothesis testing, and time series analysis.
Q4

Are there chapter-wise summaries or revision notes?

A4

Yes, each unit includes concise summaries and key takeaways for quick revision before exams.
Q5

Is the 2019 question paper included with solutions?

A5

The book includes the 2019 PTU question paper for reference, but solutions may not be provided (check the latest edition).
Q6

Are there MCQs or self-assessment questions at the end of chapters?

A6

The book includes conceptual questions and problem sets, but MCQs may be limited (check the "Question Paper" section for exam patterns).
Q7

Who is the author of the book, and what are his qualifications?

A7

The book is authored by Dr. Sanjiv Kumar Tiwary, a recognized expert in the field of business analytics and decision-making, ensuring that the content is academically rigorous and practically relevant.
Q8

What key topics does the book cover?

A8

The book covers essential topics such as statistics, sampling, hypothesis testing, correlation and regression analysis, index numbers, and time series analysis.
Q9

Is this book suitable for self-study?

A9

Yes, the structured learning approach with organized units, summaries, and case studies makes it an excellent resource for self-study, allowing students to learn at their own pace.
Q10

How are complex concepts explained in the book?

A10

Complex concepts are broken down into simplified explanations, accompanied by diagrams, examples, and case studies to facilitate better understanding.

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Unit 1 : Introduction to Statistics and Sampling

Unit 2 : Sampling Distribution and Hypothesis Testing

Unit 3 : Business Analysis and Correlation & Regression Analysis

Unit 4 : Index Number and Time Series Analysis

Question Paper (2019)

Punjab Technical University

MBA Batch 2021 onwards (MBA 201-18)

Business Analytics for Decision Making

Course Objective: The course aims at equipping students with an understanding of the research process, tools and techniques in order to facilitate managerial decision making.

Course Outcomes: At the end of the course, the student will be able to:

CO1: To have a deeper and rigorous understanding of fundamental concepts in business decision making under subjective conditions

CO2: To enhance knowledge in probability theory and normality and its distribution concepts

CO3: To conduct research surveys through multiple regression and multiple correlation

CO4: To design a good quantitative purpose statement and good quantitative research questions and hypotheses

CO5: To know the various types of quantitative sampling techniques and conditions to use.

CO6: To utilize the time series method to predict the future of sales in a concern.

Unit I

Introduction to Statistics: Meaning, Importance, Applications of inferential statistics in managerial decision making. Collection of Data: concept of primary data and secondary data, sources of primary data and secondary data, Classification and Tabulation of Data: Concept and types of classification, construction of frequency distributions, tabulation of data: role of tabulation, parts of table, rules of tabulation, review of table, types of table.

Sampling: Concept, definitions, census and sampling, probability and non probability methods of sampling, relationship between sample size and errors.

Unit II

Sampling Distributions: Concept and standard error.

Hypothesis Testing: Formulation of hypothesis, procedure of hypothesis testing, errors in testing of hypothesis, tests of significance for large samples, tests of significance for small samples, application of t-test, Z-test, F-test and Chi-square test and Goodness of fit, ANOVA.

Techniques of association of attributes.

Unit III

Business Forecasting: Introduction, Role of forecasting in business, Steps in forecasting and methods of forecasting.

Correlation: Partial and Multiple correlation.

Regression Analysis: Multiple regression analysis, Testing the assumptions of regression: multicollinearity, heteroscedasticity and autocorrelation.

Unit IV

Index Number: Definition, importance of index number in managerial decision making, methods of construction, tests of consistency, base shifting, splicing and deflation, problems in construction.

Time Series Analysis: Meaning, component and, methods of time series analysis. Trend analysis: Least square method, linear and non linear equations, applications of time series in business decision making