Assignment Set – 1

Q1. (a) Describe Data wrangling. Name the package used for Data wrangling in R and describe some of its features.

(b) Interpret vectors. Explain the creation of vectors with examples. Also, describe how to identify and handle missing values. 5+5   

Ans 1.

(a) Description of Data Wrangling and Package in R

Data wrangling refers to the systematic process of transforming raw, unstructured, or semi-structured data into a clean and organized format suitable for analysis. Real-world datasets often contain missing values, inconsistencies, incorrect formats, and redundant information. Data wrangling involves tasks such as filtering, selecting variables, renaming columns, reshaping data, handling outliers, and merging multiple datasets. In R, data wrangling is central to any data science workflow because the quality of analysis depends heavily on how

MUJ

Its Half solved only

Buy Complete assignment from us

Price – 190/  assignment

MUJ Manipal University Complete SolvedAssignments  JULY-AUGUST  2025

buy cheap assignment help online from us easily

we are here to help you with the best and cheap help

Contact No – 8791514139 (WhatsApp)

OR

Mail us-  bestassignment247@gmail.com

Our website – https://muj.assignmentsupport.in/

Q2. (a) Explain the chaining operator with an example.

(b) Articulate the summary () method with an example in R. 5+5           

Ans 2.

(a) Explanation of the Chaining Operator

The chaining operator, often referred to as the pipe operator, is used in R to create readable and intuitive sequences of data transformations. The most widely used chaining operator is %>%, provided by the magrittr package and commonly used through the tidyverse. It passes the output of one function directly as the input to the next, reducing nested function calls and improving code clarity. Instead of writing deeply nested expressions, the programmer can express operations as a logical sequence. For example, without the chaining operator, a user

Q3. (a) Criticize with an example the syntax of various looping constructs in R – For, While and Repeat statements.

(b) Discuss continuous random variable. How can that be created using R? 5+5          

Ans 3.

(a) Syntax and Use of Looping Constructs with Example

R provides three primary looping constructs: for, while, and repeat. These control structures allow repetitive execution of statements, although many operations in R are better handled through vectorization or apply-family functions. The for loop iterates over elements of a sequence. For example:

sum_val <- 0

for (i in 1:5) {

sum_val <- sum_val + i

Assignment Set – 2

Q4. (a) Explain with examples – Set, List and Tuples. What are the similarities and differences between the same.

(b) Illustrate how strings are converted into iterables in Python? Give a suitable example. 5+5

Ans 4.

(a) Sets, Lists and Tuples – Meaning, Examples, Similarities and Differences

In Python, lists, tuples and sets are fundamental collection data types used to store multiple values in a single variable, but they differ in structure, mutability and behaviour. A list is an ordered, mutable collection that can store heterogeneous elements. For example, marks = [80, 75, 90] defines a list, and elements can be updated as marks[1] = 78. Lists preserve insertion order and support operations like appending, slicing and iteration, which makes them ideal

Q5. (a) Summarize “waffle charts”. When is it used? Explain with an example in python.

(b) Discuss how simple and complex pattern searches can be performed on lists.          5+5

Ans 5.

(a) Waffle Charts – Meaning, Usage and Example in Python

A waffle chart is a visual representation used to display parts-of-a-whole relationships in a grid of small squares. Each square represents a fixed proportion, such as one percent of the total, and coloured squares indicate the contribution of a category. Unlike a pie chart, a waffle chart uses a rectangular grid, which many viewers find easier to interpret and compare. It is commonly used to show composition, such as the share of customer segments, product categories, or survey responses.

In Python, waffle charts can be built using libraries such as pywaffle in combination with

Q6. (a) Contrast the difference between loc and iloc attributes with example.

(b) When is agg() method used. Explain with example.     5+5     

Ans 6.

 (a) Difference Between loc and iloc with Example

In the pandas library, loc and iloc are two powerful indexers used to access subsets of rows and columns in a DataFrame. The loc attribute is label-based, meaning it selects rows and columns using explicit index and column names. For instance:

import pandas as pd

df = pd.DataFrame({

“name”: [“Asha”, “Ravi”, “Meera”],

“marks”: [85, 90, 88]

Assignment Set – 1

Q1. What is Data Science? Discuss the role of Data Science in various Domains. 10    

Ans 1.

Data Science

Data Science is an interdisciplinary field that focuses on extracting meaningful insights from structured and unstructured data using scientific methods, algorithms, processes, and computational tools. It integrates principles from statistics, computer science, artificial intelligence, and domain expertise to transform raw data into actionable knowledge. With digitalization increasing across industries, organizations generate massive volumes of data, and Data Science helps convert this data into valuable business intelligence. In modern

MUJ

Its Half solved only

Buy Complete assignment from us

Price – 190/  assignment

MUJ Manipal University Complete SolvedAssignments  JULY-AUGUST  2025

buy cheap assignment help online from us easily

we are here to help you with the best and cheap help

Contact No – 8791514139 (WhatsApp)

OR

Mail us-  bestassignment247@gmail.com

Our website – https://muj.assignmentsupport.in/

Q2. Explain various measures of dispersion in detail using specific examples. 10         

Ans 2.

Dispersion

Measures of dispersion describe the extent to which data values in a dataset vary from one another. While measures of central tendency such as mean, median, and mode indicate the typical value, dispersion measures describe how spread out the data is around the central value. Understanding dispersion is essential in Exploratory Data Analysis (EDA) because it reveals variability, consistency, and reliability in datasets. A dataset with high dispersion

Q3. Discuss various techniques used for Data Visualization. 10  

Ans 3.

Data Visualization

Data visualization refers to the graphical representation of information and data using charts, graphs, and visual elements. It transforms complex datasets into clear and understandable visuals, allowing users to identify patterns, trends, and relationships quickly. In Exploratory Data Analysis (EDA), visualization plays a critical role because it helps simplify large amounts of data and supports faster decision-making. Effective visualizations enable analysts

Assignment Set – 2

Q4. What is feature selection? Discuss any two feature selection techniques used to get optimal feature combinations. 10       

Ans 4.

Feature Selection and Two Major Techniques

Feature selection refers to the systematic process of identifying the most relevant variables from a dataset that contribute meaningfully to predictive modelling or pattern recognition. Modern datasets often contain dozens or even hundreds of attributes, many of which may be redundant, noisy, or irrelevant. Including such features can reduce model accuracy, increase computational cost, and lead to overfitting. Feature selection improves model performance by reducing dimensionality, simplifying interpretation, and ensuring that only the most

performance is a priority and when the dataset is of manageable size.

Q5. Discuss in detail the concept of Factor Analysis 10    

Ans 5.

Concept of Factor Analysis

Factor Analysis is a multivariate statistical technique used to identify underlying structures or latent variables within large datasets. When researchers work with many correlated variables, it becomes difficult to interpret relationships meaningfully. Factor Analysis simplifies this complexity by grouping related variables into smaller sets called factors. Each factor represents a hidden dimension underlying observable variables. This method is widely used in psychology, social sciences, marketing research, finance, and any domain where complex

Q6. Differentiate between Principal Component Analysis and Linear Discriminant Analysis 10

Ans 6.

Difference Between Principal Component Analysis and Linear Discriminant Analysis

PCA and LDA

Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are two widely used dimensionality reduction techniques, but they serve fundamentally different purposes. Both methods transform high-dimensional datasets into lower-dimensional representations, helping analysts visualize patterns, improve computational efficiency, and reduce noise. However, PCA focuses on capturing maximum variance in the data, while LDA aims to maximize class separability. Understanding the distinction between these techniques

Assignment Set – 1

Q1. What do you mean by Machine Learning? Discuss the concept of Supervised, Unsupervised and Reinforcement learning. 10 

Ans 1.

Machine Learning

Machine Learning refers to a branch of artificial intelligence that enables computer systems to learn patterns from data and make predictions or decisions without being explicitly programmed for every scenario. Instead of following a rigid set of instructions, a machine learning model improves its performance over time as it is exposed to additional data. The core principle behind machine learning is the ability to identify relationships, extract meaningful insights, and generate accurate predictions in dynamic environments. As organizations collect massive volumes of data, machine learning has become a fundamental

MUJ

Its Half solved only

Buy Complete assignment from us

Price – 190/  assignment

MUJ Manipal University Complete SolvedAssignments  JULY-AUGUST  2025

buy cheap assignment help online from us easily

we are here to help you with the best and cheap help

Contact No – 8791514139 (WhatsApp)

OR

Mail us-  bestassignment247@gmail.com

Our website – https://muj.assignmentsupport.in/

Q2. What is Support Vector Machine? What are the various steps in using Support Vector Machine? 10   

Ans 2.

Support Vector Machine

Support Vector Machine (SVM) is a powerful supervised learning algorithm used primarily for classification and, to some extent, regression problems. The central idea of SVM is to identify an optimal separating boundary, known as a hyperplane, that best differentiates between different classes in the dataset. SVM works by maximizing the margin, which refers to the distance between the hyperplane and the nearest data points from each class. These nearest points are called support vectors. By maximizing this margin, the algorithm aims to

Q3. Discuss Decision Tree in detail for classification. How we can make a balance model taking decision tree. 10       

Ans 3.

Decision Tree Classification and Creating a Balanced Decision Tree Model

Decision Tree Classification

A Decision Tree is a supervised learning method used for classification and prediction by dividing a dataset into branches based on decision rules. It resembles a tree-like structure with a root node, internal decision nodes, and leaf nodes representing outcomes. Decision Trees are intuitive because they mimic human decision-making by splitting data according to conditions. They are widely used in risk analysis, medical diagnosis, marketing segmentation, operational planning, and various prediction tasks. The core objective of a decision tree is to

Assignment Set – 2

4. Explain the K-Means Clustering algorithm 10

Ans 4.

K-Means Clustering

K-Means is one of the most widely used unsupervised learning algorithms for clustering data into groups based on similarity. The algorithm aims to partition data points into a predefined number of clusters, represented by the variable K. Each cluster has a centroid, which serves as the central point around which similar data points are grouped. K-Means is effective because it is computationally efficient and works well when the structure of data exhibits

5. Discuss various validation measures used for Machine Learning in detail. 10

Ans 5.

Validation Measures in Machine Learning

Validation measures play an essential role in evaluating the performance and reliability of machine learning models. They assess how well a model generalizes to unseen data and help prevent issues such as overfitting or underfitting. Validation ensures that model predictions are credible, stable, and suitable for real-world deployment. Since machine learning solutions often guide critical decisions in finance, healthcare, marketing, and security, selecting the

6. What is a recommendation system. Discuss various types of recommendation systems. 10

Ans 6.

Meaning of Recommendation Systems and Types of Recommendation Systems

Recommendation Systems

A recommendation system is an intelligent information filtering tool used to suggest relevant products, services, or content to users based on their preferences and behavior. These systems play a central role in modern digital platforms, shaping user experience on e-commerce sites, streaming services, social media, and online learning environments. The core purpose of recommendation systems is to personalize content, increase engagement, boost satisfaction, and enhance business outcomes such as sales or retention.

Concept and Working of Recommendation Systems

The system analyzes user data such as browsing history, ratings, purchases, search patterns,

Assignment Set – 1

Q1. Compare and contrast bar charts and Pie charts in terms of their use cases, strengths, and limitations. 10           

Ans 1.

Comparison Between Bar Charts and Pie Charts

Bar and Pie Charts

Bar charts and pie charts are among the most widely used visualization tools for summarizing and presenting categorical data. Although both serve the purpose of comparing categories, they differ significantly in structure, interpretability, and the type of insights they can convey. Understanding their similarities and differences helps analysts choose the appropriate visualization method depending on dataset characteristics and communication needs.

Use Cases of Bar Charts

A bar chart displays category names on one axis and their corresponding values on the other.

MUJ

Its Half solved only

Buy Complete assignment from us

Price – 190/  assignment

MUJ Manipal University Complete SolvedAssignments  JULY-AUGUST  2025

buy cheap assignment help online from us easily

we are here to help you with the best and cheap help

Contact No – 8791514139 (WhatsApp)

OR

Mail us-  bestassignment247@gmail.com

Our website – https://muj.assignmentsupport.in/

Q2. Describe the role of user interface (UI) and server function in an R-Shiny app.     10

Ans 2.

Role of User Interface (UI) and Server Function in an R-Shiny App

R-Shiny App Structure

R-Shiny is an interactive web application framework that allows analysts to build dashboards and data-driven tools directly from R. A Shiny app operates through two core components: the user interface (UI) and the server function. These components work together to create dynamic and responsive applications that enable users to interact with datasets, models, and visualizations in real time.

Role of the User Interface (UI)

The UI defines how the application appears visually to the user. It includes layout, input

Q3. Define a dashboard in the context of data visualization. Discuss its importance with suitable example. 10           

Ans 3.

Dashboards

A dashboard in data visualization refers to a consolidated visual display that compiles multiple charts, indicators, and analytical components into a single interface. Dashboards provide real-time insights by summarizing key metrics and trends associated with business operations, performance, customer behavior, or system status. They are widely used in decision-making environments because they present complex data in a structured and easily

Assignment Set – 2

Q4. What are the benefits of grouping data in Tableau when analyzing large datasets? 10    

Ans 4.

Benefits of Grouping Data in Tableau When Analyzing Large Datasets

Grouping in Tableau

Grouping in Tableau is a feature that allows users to combine related members of a dimension into a single higher-level category. When exploring large datasets with many unique values, grouping becomes an effective way to simplify the visualization, uncover hidden relationships, and provide a clearer analytical view. The process helps analysts convert granular information into meaningful segments, enabling more strategic

Q5. Explain how LOD expressions allow aggregations at different levels of granularity beyond the visualization’s view. 10         

Ans 5.

LOD Expressions

Level of Detail (LOD) expressions in Tableau are advanced analytical constructs that enable users to perform aggregations at different levels of granularity, independent of the visualization’s current view. LOD expressions allow analysts to define exactly how data should be grouped and aggregated, overcoming the limitations of traditional row-level or view-level computations. This results in highly flexible and precise analysis, especially when

Q6. Define data cleansing and explain why it is essential in Power BI.    10

Ans 6.

Data Cleansing in Power BI

Data cleansing in Power BI refers to the process of identifying, correcting, or removing inaccurate, inconsistent, incomplete, or irrelevant data before analysis. Since Power BI integrates data from multiple sources—such as Excel files, SQL databases, APIs, and cloud platforms—data quality issues are common. Clean data ensures the accuracy of dashboards, reports, and business decisions. Power Query, the data preparation engine in Power BI,

Assignment Set – 1

1. Evaluate the significance of each essential element in ensuring the enforceability of a contract under the Indian Contract Act, 1872. 2+8

Ans 1.

A contract is a legally enforceable agreement that creates obligations between two or more parties. The Indian Contract Act, 1872, lays down the legal framework for contracts in India, ensuring that agreements made between parties are valid and binding. For an agreement to become a contract, it must include specific essential elements. Without these, the agreement is void, voidable, or unenforceable.

Essential Elements of a Valid Contract

1. Lawful Offer and Acceptance

One of the most fundamental elements is a lawful offer and acceptance. A contract begins

MUJ

Its Half solved only

Buy Complete assignment from us

Price – 190/  assignment

MUJ Manipal University Complete SolvedAssignments  JULY-AUGUST  2025

buy cheap assignment help online from us easily

we are here to help you with the best and cheap help

Contact No – 8791514139 (WhatsApp)

OR

Mail us-  bestassignment247@gmail.com

Our website – www.assignmentsupport.in

2. Discuss the different modes of dissolution of a partnership firm under the Indian Partnership Act, 1932. 10

Ans 2.

The dissolution of a partnership firm refers to the termination of the relationship between partners and the end of business activities carried on jointly. When a firm is dissolved, all assets are realized, liabilities are paid, and any remaining surplus is distributed among the partners. The Indian Partnership Act, 1932, provides a comprehensive framework under Sections 39 to 55 for various modes of dissolution to ensure fairness and transparency in

3. Assess the importance of each essential element in determining the validity of a contract of sale under the Sale of Goods Act, 1930. 10

Ans 3.

The Sale of Goods Act, 1930 governs contracts related to the sale and purchase of goods in India. It defines a contract of sale as an agreement whereby the seller transfers or agrees to transfer the ownership of goods to the buyer for a price. However, not every agreement to sell goods qualifies as a valid contract. Certain essential elements must be present to ensure that

Assignment Set – 2

4. Illustrate how companies in India implement CSR activities in compliance with the provisions of the Companies Act, 2013. 10

Ans 4.

Corporate Social Responsibility (CSR) refers to a company’s ethical obligation to contribute positively to society, beyond profit-making objectives. It involves initiatives for social development, environmental protection, and community welfare. The concept was formally introduced into Indian corporate law under Section 135 of the Companies Act, 2013, which made CSR a legal requirement for eligible companies.

CSR Provisions under the Companies Act, 2013

According to Section 135, CSR provisions apply to companies that meet any of the following

5. Discuss the rights of consumers under the Consumer Protection Act, 2019. 10

Ans 5.

The Consumer Protection Act, 2019 was enacted to safeguard consumer interests and ensure fair trade practices in India. It replaced the 1986 Act to address modern market challenges such as e-commerce, online fraud, and misleading advertisements. According to the Act, a consumer is any individual who purchases things or makes use of services for consideration. Additionally, the Act establishes various rights that are designed to protect customers from

6. Explain the concept of a patent and describe the procedure for obtaining one under the Indian Patent Act, 1970. 3+7

Ans 6.

A patent is an exclusive legal right granted to an inventor for a new invention or process that offers a novel way of doing something or provides a technical solution to a problem. The Indian Patent Act, 1970, governs patent registration in India and provides protection to inventors by preventing others from making, using, or selling their invention without permission for a specific period—usually 20 years.

Concept and Importance of a Patent

Patents encourage innovation by rewarding inventors with exclusive rights while promoting

Assignment Set – 1

Q.1. Discuss the types of strategies with suitable examples. Explain PESTEL analysis.

Ans 1.

Types of Strategies

Strategies are a longer-term course for action to meet a specific goal or set goals in an environment of competition. The different kinds of organizations employ strategies based on their situation, available resources, and competitive pressures they face. The majority of strategies are categorized as three levels: corporate operational, business, and. Each level is designed to serve a particular objective and has a distinct area within the structure.

Corporate-level strategies establish the overall direction and scope of the organization as a

MUJ

Its Half solved only

Buy Complete assignment from us

Price – 190/  assignment

MUJ Manipal University Complete SolvedAssignments  JAN- FEB  2026

buy cheap assignment help online from us easily

we are here to help you with the best and cheap help

Contact No – 8791514139 (WhatsApp)

OR

Mail us-  bestassignment247@gmail.com

Our website – https://muj.assignmentsupport.in/

JAN-FEB 2026

Q.2. How does Porter’s Five Forces model aid in analysing competitive dynamics within an industry? Provide a detailed examination of each force, supported by examples from a specific industry or company.

Ans 2.

Porter’s Five Forces Model

Porter’s Five Forces model, developed by Michael Porter of Harvard Business School can be a highly effective analytical tool to understand how competitive intensity affects profitability potential of any sector. It examines the five major forces which, together, influence competitive behavior and define the overall attractiveness of an industry as a place to invest.

Threat of New Entrants

This measure measures the ease with which it is for new competitors to enter into the business

Q.3. What is strategic control, and how does it differ from operational control in terms of its scope, focus, and objectives? Discuss. Discuss BCG Matrix.

Ans 3.

Strategic Control vs Operational Control

Strategic Control is the way by which top management monitors whether a business’s strategies are executed as designed and producing the expected outcomes. It is focused on the overall strategy of the business over longer periods of time that typically spans several years. Strategic control evaluates whether certain assumptions regarding the external environment that were made during the plan process still hold and whether the chosen strategy keeps generating

Assignment Set – 2

Q.4. Discuss the steps involved in business continuity plan. What are the three major types of strategic alliances organizations form for the purpose of developing a competitive advantage? Describe in detail.

Ans 4.

Business Continuity Plan

An Business Continuity Plan (BCP) is a written plan which defines the manner in which a company will carry on essential business operations or following a sudden disruption like a natural catastrophe or cyberattack, pandemic or a failure in the supply chain. A well-formulated BCP can reduce financial losses as well as protects reputation of the organization and helps

Q.5. Examine the key business strategies employed by multinational corporations (MNCs) to succeed in global markets?

Ans 5.

Global Strategies of Multinational Corporations

Multinational corporations (MNCs) have operations across a range of countries, and must face the task of improving efficiency across the globe in response to a variety of local market requirements. In order to thrive in the globalized and competitive conditions, MNCs adopt a range of strategic business models that align with their market position, the resources they have

Q.6. Write notes on the following: Business Ethics  Corporate Social Responsibility (CSR)

Ans 6.

Business Ethics

Business ethics is the application of moral principles and ethical standards to commercial activities, choices, and relationships within organizations. It defines the boundaries of proper and improper conduct in business contexts and guides how companies interact with customers, employees, suppliers, competitors, investors, and other members of the community. Ethics-based business conduct builds credibility and trust, both of which are essential foundations for long-