MFM 106 Business Research Notes cover all four units of the GGSIPU MBA (Financial Management) Semester 2 core paper. The printed English notes include 22 labelled diagrams, 13 worked numericals, 28 solved short answers and 49 additional exam-style practice questions. Topics include research design, sampling, questionnaire construction, measurement scales, hypothesis testing, regression, factor analysis and research report writing. The notes follow the MBA (FM) scheme labelled 2021-22 onwards.
Written by Prateek Talwar, Founder, Unnati Educations · Reviewed by Prateek Talwar, Associate Company Secretary (ACS), ICSI · Checked against the MBA (Financial Management) Scheme and Syllabus, 2021-22 onwards · Updated 14 October 2026 · Editorial policy
Scheme: MBA (FM) scheme 2021-22 onwards | Applies to: batches admitted from 2021-22 onwards | Verified against: MBA (Financial Management) Scheme and Syllabus, identified in the supplied record as dated 20 May 2022
MFM 106 Business Research at a glance: GGSIPU MBA (FM) Sem 2 credits, units and exam pattern
| Code and title | MFM 106 Business Research (MFM-106 in the supplied syllabus reference) |
|---|---|
| Course and semester | MBA (Financial Management), Semester 2 |
| Category and credits | Core, 3 credits; L-T-P: 3-0-0 |
| Marks | 100: 25 internal (15-mark class test and 10 marks for other assessment activities) + 75 external |
| Pass mark | Not specified in the supplied scheme details; refer to GGSIPU Ordinance 11 for applicable examination rules |
| Applies to | Batches admitted from 2021-22 onwards under the stated scheme |
| End-term pattern | 75 marks; detailed question-paper pattern not specified in the supplied scheme details |
| Units and hours | 4 units, 42 teaching hours: Unit I 12, Unit II 8, Unit III 10 and Unit IV 12 |
| Paired lab | None |
The supplied Semester 2 plan lists nine papers carrying 28 credits in total. Unit II receives 8 teaching hours but contains the highest number of worked numericals in these notes.
MFM 106 Business Research Notes unit-wise: 22 diagrams, 13 worked numericals and 28 solved short answers across 4 units
The four units occupy pages 4 to 53. They cover research foundations, design and sampling, questionnaire and scale measurement, and statistical analysis with report writing.
MFM 106 Unit 1: Introduction
Unit 1 (pages 4 to 17), also described as Introduction to Business Research, covers research types, problem formulation, SMART objectives, the ten-step research process, nine hypothesis types, constructs, variables and literature review techniques. It contains 6 diagrams, 7 solved short answers and 12 practice questions. This theory-focused unit has no worked numericals.
| Variable | Role | Finance example |
|---|---|---|
| Independent | Presumed explanatory factor | Interest rate |
| Dependent | Measured outcome | Demand for home loans |
| Moderating | Changes the strength or direction of a relationship | Income level |
| Mediating | Helps explain the mechanism of a relationship | Lower EMI following an interest-rate reduction |
Quick look: variable types using a home-loan research example (from page 13)
- Variable
- Independent
- Role
- Presumed explanatory factor
- Finance example
- Interest rate
- Variable
- Dependent
- Role
- Measured outcome
- Finance example
- Demand for home loans
- Variable
- Moderating
- Role
- Changes the strength or direction of a relationship
- Finance example
- Income level
- Variable
- Mediating
- Role
- Helps explain the mechanism of a relationship
- Finance example
- Lower EMI following an interest-rate reduction
These roles describe a proposed research model; a statistical association alone does not establish causation.
MFM 106 Unit 2: Research Design and Sampling
Unit 2 (pages 18 to 30) covers exploratory, descriptive and causal research designs, experimental designs, population, sampling frame, sampling methods, sample size calculations, and sampling and non-sampling errors. The supplied source notes that the official Unit II has no printed title; Research Design and Sampling is the notes' descriptive title. It contains 7 worked numericals, 5 diagrams, 7 solved short answers and 12 practice questions.
Quick look: sample size for estimating an average SIP (from page 26)
- Estimate the average monthly SIP within ±₹200 at a 95% confidence level, using Z = 1.96.
- A pilot study estimates the population standard deviation as ₹1,500.
- Apply n = Z²σ² ÷ e² = (1.96² × 1,500²) ÷ 200².
- The result is n = 216.09. Round upward to a minimum sample of 217 investors.
This calculation assumes the stated confidence level, margin of error and standard deviation; it does not include a finite-population correction or adjustment for non-response.
MFM 106 Unit 3: Questionnaire & Scale Measurement
Unit 3 (pages 31 to 41) covers questionnaire design, improvements to poorly worded investor questions, nominal, ordinal, interval and ratio scales, scaling techniques, Churchill's scale development steps, reliability, validity and response biases. It contains 1 worked numerical, 6 diagrams, 7 solved short answers and 12 practice questions.
Quick look: Cronbach's alpha for a four-item scale (from page 38)
- The four item variances are 0.8, 0.9, 1.0 and 1.1, giving a total of 3.8.
- The variance of the combined scale score is 9.5.
- Use α = [k ÷ (k − 1)] × [1 − (sum of item variances ÷ total-score variance)].
- α = (4 ÷ 3) × (1 − 3.8 ÷ 9.5) = (4 ÷ 3) × 0.6 = 0.80.
An alpha of 0.80 meets the commonly used 0.70 screening guideline for internal consistency. The appropriate threshold depends on the research context, and alpha alone does not establish validity.
MFM 106 Unit 4: Data Analysis & Report Writing
Unit 4 (pages 42 to 53) covers descriptive statistics, Type I and Type II errors, parametric and non-parametric tests, correlation, regression, exploratory and confirmatory factor analysis, discriminant analysis and research report writing. The notes use finance examples, including fund returns and credit decisions. It contains 5 worked numericals, 5 diagrams, 7 solved short answers and 13 practice questions.
| Dependent variable | Independent variable(s) | Possible technique |
|---|---|---|
| One continuous outcome | Several explanatory variables | Multiple linear regression |
| One continuous outcome | Two groups or three or more groups | Independent-samples t-test for two groups or ANOVA for three or more groups, subject to assumptions |
| Binary outcome | Continuous or categorical predictors | Binary logistic regression |
| Categorical group membership | Continuous predictors | Discriminant analysis, subject to assumptions |
Quick look: choosing a statistical technique from variable types (from page 50)
- Dependent variable
- One continuous outcome
- Independent variable(s)
- Several explanatory variables
- Possible technique
- Multiple linear regression
- Dependent variable
- One continuous outcome
- Independent variable(s)
- Two groups or three or more groups
- Possible technique
- Independent-samples t-test for two groups or ANOVA for three or more groups, subject to assumptions
- Dependent variable
- Binary outcome
- Independent variable(s)
- Continuous or categorical predictors
- Possible technique
- Binary logistic regression
- Dependent variable
- Categorical group membership
- Independent variable(s)
- Continuous predictors
- Possible technique
- Discriminant analysis, subject to assumptions
The final technique also depends on the research design, independence of observations, distributional assumptions and measurement quality.
Probability sampling from simple random to cluster for MBA finance surveys: excerpt from page 24 of the MFM 106 notes
Excerpt from page 24
Simple random sampling (SRS)
Every population element has an equal selection probability under simple random sampling. Selection may use a lottery, random number table or computer-generated random numbers, including Excel's =RAND() function. The researcher may sample with replacement (SRSWR) or without replacement (SRSWOR).
Advantages include a straightforward selection procedure and the ability to estimate sampling error under suitable assumptions. Limitations include the need for a complete sampling frame and potentially high costs when respondents are geographically dispersed.
Systematic sampling
Systematic sampling selects units at a regular interval after a random start. With 1,000 customers and a required sample of 50, the interval is k = 1,000 ÷ 50 = 20. A random start of 7 produces positions 7, 27, 47, 67 and so on.
The method spreads selections across an ordered list, but periodic patterns in the list may distort the sample.
Stratified random sampling
The population is divided into strata using characteristics such as income, age, region or bank type. A random sample is then selected from each stratum.
For proportionate allocation, nh = (Nh ÷ N) × n. If 10,000 investors comprise 6,000 salaried people, 3,000 business owners and 1,000 professionals, a proportionate sample of 500 contains 300, 150 and 50 investors respectively.
Stratification supports subgroup representation and can improve precision when the strata are appropriately defined. Disproportionate allocation may be used when some groups need larger samples for reliable analysis.
Cluster, multi-stage and area sampling
Cluster sampling divides the population into natural groups and randomly selects some groups for study. For example, a researcher may select five colleges and survey all MBA students within those colleges, or randomly select students within the chosen colleges.
Multi-stage sampling involves selection at successive levels, such as states, districts, villages and households. Area sampling is a form of cluster sampling in which clusters are geographical areas.
Stratified sampling selects from every stratum; cluster sampling selects only some clusters. Stratification often aims to improve precision, while clustering frequently reduces fieldwork costs. The actual sampling error depends on the population structure and design.
Do the MFM 106 notes cover the full GGSIPU syllabus?
The supplied editorial mapping identifies coverage of the listed topics in all four official units. One limitation is explicitly recorded: Course Outcome 3 mentions preparing a research proposal, but the notes do not contain a dedicated research proposal writing section or template.
| Official unit | Official topics | In the notes | Status |
|---|---|---|---|
| I: Introduction | Meaning, purpose and nature of research; problem formulation; objectives and questions; research process; hypotheses; constructs; variables; literature review | Sections 1–11, pages 4–15 | Mapped |
| II: No official title printed | Research design; target population, frame and units; sampling methods; sample size; sample design; sampling and non-sampling errors | Sections 1–8, pages 18–29 | Mapped |
| III: Questionnaire & Scale Measurement | Questionnaire purpose and design; structured and unstructured questions; scale types; scale formulation; reliability; validity; errors | Sections 1–9, pages 31–40 | Mapped |
| IV: Data Analysis & Report Writing | Descriptive statistics; hypothesis testing; parametric and non-parametric tests; ANOVA; correlation; multiple and logistic regression; EFA and CFA; discriminant analysis; report writing | Sections 1–8, pages 42–52 | Mapped |
MFM 106 official syllabus topics mapped to the notes
- Official unit
- I: Introduction
- Official topics
- Meaning, purpose and nature of research; problem formulation; objectives and questions; research process; hypotheses; constructs; variables; literature review
- In the notes
- Sections 1–11, pages 4–15
- Status
- Mapped
- Official unit
- II: No official title printed
- Official topics
- Research design; target population, frame and units; sampling methods; sample size; sample design; sampling and non-sampling errors
- In the notes
- Sections 1–8, pages 18–29
- Status
- Mapped
- Official unit
- III: Questionnaire & Scale Measurement
- Official topics
- Questionnaire purpose and design; structured and unstructured questions; scale types; scale formulation; reliability; validity; errors
- In the notes
- Sections 1–9, pages 31–40
- Status
- Mapped
- Official unit
- IV: Data Analysis & Report Writing
- Official topics
- Descriptive statistics; hypothesis testing; parametric and non-parametric tests; ANOVA; correlation; multiple and logistic regression; EFA and CFA; discriminant analysis; report writing
- In the notes
- Sections 1–8, pages 42–52
- Status
- Mapped
Official reference: MBA (Financial Management) Scheme and Syllabus, 2021-22 onwards. The supplied source locates MFM-106 on PDF pages 32–33 and the marks scheme on page 3.
Students preparing a research proposal should also follow the proposal requirements supplied by their faculty or project supervisor.
How to write MFM 106 answers: H0 and H1 notation, comparison tables and step-by-step test workings
For hypothesis-testing questions, clearly state the null hypothesis (H0) and alternative hypothesis (H1). Explain the chosen significance level, test statistic, decision rule and interpretation. Use the terms reject H0 or fail to reject H0; a statistical test does not prove a hypothesis with certainty.
For Unit 1 and Unit 2 long answers, the notes recommend a definition, classification diagram, comparison table and a relevant Indian business example. For literature review answers, explain how earlier research leads to a specific research gap. A literature matrix can organise author, year, objective, sample, findings and gap.
For logistic regression, factor analysis and discriminant analysis, explain the purpose, suitable variable types, model or equation, interpretation of major outputs and a finance application. Useful comparisons include independent-samples t-test versus Mann-Whitney U, paired t-test versus Wilcoxon signed-rank, one-way ANOVA versus Kruskal-Wallis, and Pearson versus Spearman correlation.
For reliability and validity, draw the target diagram and explain why consistent measurements can still fail to measure the intended construct. Use Cronbach's alpha to discuss internal consistency, while recognising that its commonly quoted 0.70 threshold is a guideline rather than a universal rule.
Worked example: One-way ANOVA for three sales schemes (page 45)
- Observations: Scheme A: 5, 6, 7; Scheme B: 8, 9, 10; Scheme C: 11, 12, 13.
- Hypotheses: H0 states that all three population means are equal; H1 states that at least one mean differs.
- Group means: A = 6, B = 9, C = 12. Grand mean = 9.
- Between-group sum of squares: SSB = 3[(6 − 9)² + (9 − 9)² + (12 − 9)²] = 54.
- Within-group sum of squares: SSW = 6.
- Degrees of freedom: Between groups = 2; within groups = 6.
- Mean squares: MSB = 54 ÷ 2 = 27; MSW = 6 ÷ 6 = 1.
- Test statistic: F = 27 ÷ 1 = 27.
- Decision: At the 5% significance level, F-critical for (2, 6) degrees of freedom is approximately 5.14. Since 27 exceeds 5.14, reject H0. The data provide evidence that at least one scheme has a different population mean, subject to ANOVA assumptions.
For 15-mark answers, organise the response with clear headings, relevant formulas, assumptions, an illustration and an interpretation rather than presenting calculations alone.
MFM 106 exam corner: 28 solved short answers and 49 fifteen-mark and five-mark practice questions by unit
| Unit | Solved short answers | Long-answer practice (15 marks) | Short-answer practice (5 marks) | Worked numericals |
|---|---|---|---|---|
| Unit 1 | 7 | 6 | 6 | 0 |
| Unit 2 | 7 | 6 | 6 | 7 |
| Unit 3 | 7 | 6 | 6 | 1 |
| Unit 4 | 7 | 7 | 6 | 5 |
| Total | 28 | 25 | 24 | 13 |
MFM 106 notes: solved answers, practice questions and numericals per unit
- Unit
- Unit 1
- Solved short answers
- 7
- Long-answer practice (15 marks)
- 6
- Short-answer practice (5 marks)
- 6
- Worked numericals
- 0
- Unit
- Unit 2
- Solved short answers
- 7
- Long-answer practice (15 marks)
- 6
- Short-answer practice (5 marks)
- 6
- Worked numericals
- 7
- Unit
- Unit 3
- Solved short answers
- 7
- Long-answer practice (15 marks)
- 6
- Short-answer practice (5 marks)
- 6
- Worked numericals
- 1
- Unit
- Unit 4
- Solved short answers
- 7
- Long-answer practice (15 marks)
- 7
- Short-answer practice (5 marks)
- 6
- Worked numericals
- 5
- Unit
- Total
- Solved short answers
- 28
- Long-answer practice (15 marks)
- 25
- Short-answer practice (5 marks)
- 24
- Worked numericals
- 13
Total: 28 solved short answers + 49 additional practice questions (25 long-answer and 24 short-answer) = 77 questions, plus 13 worked numericals. The 5-mark and 15-mark labels describe the notes' practice format, not a confirmed official end-term question-paper pattern.
One question per unit, with answer pointers:
- Unit 1: What is a hypothesis? Explain its types and the process of hypothesis formulation with examples. Pointer: Explain the hypothesis types table on page 11, then outline the formulation process.
- Unit 2: Distinguish between sampling and non-sampling errors. How can they be minimised? Pointer: Explain standard error for the sample mean as σ ÷ √n under appropriate assumptions. Non-sampling errors may occur even in a census.
- Unit 3: What is a measurement scale? Explain nominal, ordinal, interval and ratio scales with examples. Pointer: Give a business example for each scale and identify suitable descriptive statistics.
- Unit 4: Explain discriminant analysis and its applications in finance. Pointer: Discuss classification, Wilks' lambda and classification accuracy. For Altman's original public manufacturing-firm Z-score model, values below 1.81 and above 2.99 are commonly labelled distress and safe zones respectively; thresholds differ for other model variants.
Who writes and checks the MFM 106 Business Research notes?
- Prateek Talwar, author: Founder, Unnati Educations; Associate Company Secretary (ACS), ICSI, membership no. 58704, since 15 May 2019; B.Com, University of Delhi (School of Open Learning), 2012. Author profile
Prateek Talwar is also identified as the subject reviewer. The supplied editorial record maps the four units against the MBA (FM) scheme for batches admitted from 2021-22 onwards. Its sample literature matrix is illustrative rather than a record of actual research studies.
Last updated 14 October 2026. Read the editorial policy for information about review and corrections.
MFM 106 and the GGSIPU MBA (FM) Sem 2 papers it connects to
Paired lab: None. MFM 106 is a core theory paper with 3 credits.
- MFM 114 Minor Project (4 credits): Research problem formulation, sampling, questionnaires, analysis and report writing are relevant to project work.
- MFM 110 Investment Analysis and Portfolio Management: Regression concepts from Unit 4 help explain the estimation of a security's beta.
| Group | Papers |
|---|---|
| Governance and finance | MFM 102 Corporate Social Responsibility and Corporate Governance; MFM 104 Financial Management |
| Operations and people management | MFM 108 Sustainable Operations Management; MFM 112 Human Resource Management |
| Professional skills and electives | MFM 116 Professional Skill Development (NUES); MFM 118 MOOC/Open Elective |
Other MBA (Financial Management) Semester 2 papers in the supplied scheme
- Group
- Governance and finance
- Papers
- MFM 102 Corporate Social Responsibility and Corporate Governance; MFM 104 Financial Management
- Group
- Operations and people management
- Papers
- MFM 108 Sustainable Operations Management; MFM 112 Human Resource Management
- Group
- Professional skills and electives
- Papers
- MFM 116 Professional Skill Development (NUES); MFM 118 MOOC/Open Elective
MFM 106 Business Research notes FAQs
How do I get the full MFM 106 notes?
Use the WhatsApp ordering button below. The complete MFM 106 notes are supplied as a printed English book, not as a downloadable full-book PDF. A separate sample PDF is planned for preview. Delivery usually takes up to 5 to 7 days, depending on location.
Is MFM 106 Business Research a Semester 1 or Semester 2 paper?
MFM 106 is listed in Semester 2 of the MBA (Financial Management) scheme for 2021-22 onwards. It is a 3-credit core paper with three lecture hours per week.
What is the passing mark for MFM 106?
The subject carries 100 marks: 25 internal and 75 external. The supplied scheme details do not state a passing percentage. Consult GGSIPU Ordinance 11 for the applicable examination and result rules.
Which MFM 106 unit has the most worked numericals?
Unit 2 has 7 of the 13 worked numericals, covering sampling methods and sample size calculations. Unit 4 has 5, Unit 3 has 1 and Unit 1 has none.
Do the MFM 106 notes explain common SPSS and AMOS output cut-offs?
Yes. The notes list common screening guidelines such as Cronbach's alpha of 0.70, KMO of 0.60, factor loadings of 0.50, CFI and TLI of 0.90, RMSEA of 0.08, composite reliability of 0.70 and AVE of 0.50. They also discuss eigenvalues above 1 and VIF values above 10 as a multicollinearity warning. These are context-dependent guidelines, not universal acceptance rules. The notes mention SPSS, AMOS, SmartPLS and R but do not provide software tutorials or screenshots.
Will the MFM 106 notes help with the MFM 114 Minor Project?
They cover research problem formulation, hypotheses, sample size, questionnaire construction, reliability and report structure. They are study notes rather than a completed project report, and they do not contain a dedicated research proposal template. Follow the project supervisor's requirements for the final format.
Get the full MFM 106 Business Research Notes on WhatsApp
The printed English notes book is listed as 54 pages. The supplied page ranges document pages 1 to 53, leaving one page to confirm. The notes include 22 diagrams, 13 worked numericals, 28 solved short answers and 49 additional practice questions.
| Part | Pages | Diagrams | Worked numericals |
|---|---|---|---|
| Cover and index | 1–3 (3) | — | — |
| Unit 1: Introduction | 4–17 (14) | 6 | 0 |
| Unit 2: Research Design and Sampling | 18–30 (13) | 5 | 7 |
| Unit 3: Questionnaire & Scale Measurement | 31–41 (11) | 6 | 1 |
| Unit 4: Data Analysis & Report Writing | 42–53 (12) | 5 | 5 |
| Unidentified page | 54 (1; content pending confirmation) | — | — |
| Listed book total | 54 | 22 | 13 |
MFM 106 printed notes book: documented pages and content per unit
- Part
- Cover and index
- Pages
- 1–3 (3)
- Diagrams
- —
- Worked numericals
- —
- Pages
- 4–17 (14)
- Diagrams
- 6
- Worked numericals
- 0
- Pages
- 18–30 (13)
- Diagrams
- 5
- Worked numericals
- 7
- Pages
- 31–41 (11)
- Diagrams
- 6
- Worked numericals
- 1
- Pages
- 42–53 (12)
- Diagrams
- 5
- Worked numericals
- 5
- Part
- Unidentified page
- Pages
- 54 (1; content pending confirmation)
- Diagrams
- —
- Worked numericals
- —
- Part
- Listed book total
- Pages
- 54
- Diagrams
- 22
- Worked numericals
- 13
Delivery: within 5 to 7 days at most; the exact time may vary with your location.
Order the MFM 106 notes book on WhatsApp (4 units, 54 pages)
Unnati Educations is an independent education provider based in Vikaspuri, Delhi. We are not affiliated with, authorised by, or endorsed by Guru Gobind Singh Indraprastha University (GGSIPU). 'GGSIPU' and 'IPU' are used only to describe the syllabus our notes follow. For official information, visit ipu.ac.in.
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