DMBA214 BUSINESS RESEARCH METHODS (RPYTHON) JULY-AUGUST 2025

Description

SESSION	JULY-AUGUST 2025
PROGRAM	MASTER OF BUSINESS ADMINISTRATION (MBA)
SEMESTER	II
COURSE CODE & NAME	DMBA214 BUSINESS RESEARCH METHODS (R/PYTHON)

 

 

Assignment Set – 1

 

 

Q1. What are the different types of research designs? Provide examples of how each type is applied in business research. 4+6

Ans 1.

Research design refers to the overall plan, structure, and strategy used to conduct research in a logical and systematic manner. It serves as a blueprint that guides data collection, measurement, and analysis. In business research, an appropriate research design ensures that the study objectives are met accurately and efficiently. The types of research designs broadly fall under three categories — exploratory, descriptive, and causal designs. Each serves a

 

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Q2. What are the key features of RStudio, and how does it enhance the functionality of base R? Describe the purpose of each pane in the RStudio interface. 3+3+4     

Ans 2.

RStudio is an integrated development environment (IDE) for R programming, designed to simplify the process of writing, running, and managing R code. While base R provides the statistical and computational core, RStudio enhances its usability through an intuitive interface, organized workspace, and productivity tools that support data analysis and visualization.

Key Features of Rstudio

RStudio offers several features that make it superior to working in the base R console.

1. User-Friendly Interface: It organizes scripts, output, plots, and packages within a

 

 

Q3. Explain the differences between structured, semi-structured, and unstructured data collection methods. 10           

Ans 3.

In business research, data collection is the foundation for generating insights that guide decisions and strategies. Depending on the nature of information and research objectives, data can be categorized as structured, semi-structured, or unstructured. These categories differ in terms of format, organization, and analytical approach. Understanding their distinctions helps researchers select appropriate tools and techniques for efficient data handling and analysis.

Structured Data Collection Methods

Structured data refers to information organized in a predefined format that fits neatly into

 

 

Assignment Set – 2

 

 

Q4. Discuss how to implement simple linear regression and perform its visualization in R (provide codes). 5+5           

Ans 4.

Implementing Simple Linear Regression and Visualization in R

Concept and Assumptions

Simple linear regression models the relationship between a numeric outcome Y and a single predictor X using Y=β0+β1X+ε. Before fitting, check core assumptions: linearity between X and Y, independence of errors, constant variance (homoscedasticity), and approximate normality of residuals. In practice, visual scans and basic diagnostics go a long way; if relationships curve, a transformation or a different model may be better.

Data Preparation and Exploratory Glance

Begin by loading data and inspecting structure, missing values, and outliers. A quick

 

 

 

Q5. Discuss the structure and various components of research report. 4+6       

Ans 5.

Structure and Components of a Research Report

A research report is a coherent narrative that documents why a study was undertaken, how it was executed, what was found, and why those findings matter. Its structure balances readability with methodological transparency, enabling peers to evaluate rigor and replicate results.

Front Matter

Begin with the title page, abstract, and keywords. The title should be precise and informative, the abstract a compact 150–250-word snapshot covering background, methods, key results,

 

 

Q6. A random sample of 395 people in a country were surveyed to find out if gender is independent of education level. Each person was asked to report the highest education level they had obtained. The data that resulted from the survey is summarized in the following table:

Gender	High School	Bachelors	Masters	Ph.D.	Total
Female	60	54	46	41	201
Male	40	44	53	57	194
Total	100	98	99	98	395

 

Formulate the hypothesis and test that are gender and education level dependent at 5% level of statistical significance?   2+8

Ans 6.

The Chi-square test of independence is a non-parametric statistical method used to determine whether two categorical variables are related or independent of each other. It compares the observed frequencies in each category with the expected frequencies calculated under the assumption of independence. If the difference between observed and expected frequencies is large enough, it indicates a significant association between the variables. The test is based on the Chi-square (χ²) distribution and is widely used in surveys, social sciences, and marketing research. In this problem, it helps evaluate whether gender and education level are