The document discusses transportation problems in operations research. It defines a transportation problem as involving minimizing transportation costs of supplying commodities from origins to destinations, with supply and demand constraints. There are two types: balanced, where total supply equals demand, and unbalanced, where supply does not equal demand and dummy origins/destinations are used. A feasible solution satisfies the constraints, while a non-degenerate solution has exactly m+n-1 allocations.
This document contains answers to assignment questions on operations research. It defines operations research and describes types of operations research models including physical and mathematical models. It also outlines the phases of operations research including the judgment, research, and action phases. Additionally, it provides explanations and examples of linear programming problems and their graphical solution method, as well as addressing how to solve degeneracies in transportation problems and explaining the MODI optimality test procedure.
Operations Research is an interdisciplinary field that uses scientific methods to make optimal decisions. It began developing in the 1930s and 1940s to help with logistics problems in World War II. Some common application areas of operations research include forecasting, production scheduling, inventory control, capital budgeting, and transportation. The document provides examples of transportation problems and assignment problems, which are types of optimization problems addressed by operations research techniques. It also discusses solution methods for transportation problems like the Northwest Corner method and MODI method.
The document provides an overview of quantitative analysis. It discusses that quantitative analysis is the systematic study of an organization's structure, characteristics, functions, and relationships to provide executives with a quantitative basis for decision making. The characteristics of quantitative analysis include a focus on decision making, applying a scientific approach, using an interdisciplinary team, and applying formal mathematical models. The quantitative analysis process involves defining the problem, developing a model, acquiring data, developing a solution, testing the solution, and validating the model. Common tools used in quantitative analysis include linear programming, statistical techniques, decision tables, decision trees, game theory, forecasting, and mathematical programming.
The document outlines the key steps in the research process, which are: 1) defining the research problem; 2) reviewing relevant literature; 3) formulating testable hypotheses; 4) developing a research design; 5) determining sample design; 6) collecting data; 7) analyzing data; 8) generalizing and interpreting results; and 9) writing a report or thesis. It also discusses different types of research designs including exploratory, descriptive, and causal designs and levels of measurement such as nominal, ordinal, interval, and ratio scales. Common sources of error in measurement are issues with respondents, situational factors, flaws in measurement instruments, and errors in data handling.
1) The document discusses Data Envelopment Analysis (DEA), a linear programming technique used to evaluate the efficiency of decision-making units like organizations. DEA can handle multiple inputs and outputs to measure efficiency relative to best practices.
2) Transportation problems, which aim to minimize costs in transporting goods from origins to destinations, can be formulated as linear programs and solved using techniques like the simplex method. Initial basic feasible solutions are found using methods like the Northwest Corner Rule.
3) The document provides an example of using DEA and transportation problem solving methods to optimize the allocation of milk transportation from dairy plants to distribution centers to minimize costs.
This document provides an overview of business research including definitions, types of research, research process and methodology. It discusses quantitative vs qualitative research, descriptive vs explanatory research, and basic vs applied research. It also outlines research applications in various business functions like marketing, finance, human resources and production. Additionally, it covers research process, data sources, questionnaire method, measurement scales, sampling techniques and criteria for good research.
Data Analysis & Interpretation and Report WritingSOMASUNDARAM T
Statistical Methods for Data Analysis (Only Theory), Meaning of Interpretation, Technique of Interpretation, Significance of Report Writing, Steps, Layout of Research Report, Types of Research Reports, Precautions while writing research reports
Research is a systematic and scientific method of finding solutions by obtaining various types of data and systematic analysis of the multiple aspects of the issues related.
The techniques or the specific procedure which helps to identify, choose, process, and analyze information about a subject is called Research Methodology
Experimental design is a statistical tool for improving product design and solving production problems.
This document contains answers to assignment questions on operations research. It defines operations research and describes types of operations research models including physical and mathematical models. It also outlines the phases of operations research including the judgment, research, and action phases. Additionally, it provides explanations and examples of linear programming problems and their graphical solution method, as well as addressing how to solve degeneracies in transportation problems and explaining the MODI optimality test procedure.
Operations Research is an interdisciplinary field that uses scientific methods to make optimal decisions. It began developing in the 1930s and 1940s to help with logistics problems in World War II. Some common application areas of operations research include forecasting, production scheduling, inventory control, capital budgeting, and transportation. The document provides examples of transportation problems and assignment problems, which are types of optimization problems addressed by operations research techniques. It also discusses solution methods for transportation problems like the Northwest Corner method and MODI method.
The document provides an overview of quantitative analysis. It discusses that quantitative analysis is the systematic study of an organization's structure, characteristics, functions, and relationships to provide executives with a quantitative basis for decision making. The characteristics of quantitative analysis include a focus on decision making, applying a scientific approach, using an interdisciplinary team, and applying formal mathematical models. The quantitative analysis process involves defining the problem, developing a model, acquiring data, developing a solution, testing the solution, and validating the model. Common tools used in quantitative analysis include linear programming, statistical techniques, decision tables, decision trees, game theory, forecasting, and mathematical programming.
The document outlines the key steps in the research process, which are: 1) defining the research problem; 2) reviewing relevant literature; 3) formulating testable hypotheses; 4) developing a research design; 5) determining sample design; 6) collecting data; 7) analyzing data; 8) generalizing and interpreting results; and 9) writing a report or thesis. It also discusses different types of research designs including exploratory, descriptive, and causal designs and levels of measurement such as nominal, ordinal, interval, and ratio scales. Common sources of error in measurement are issues with respondents, situational factors, flaws in measurement instruments, and errors in data handling.
1) The document discusses Data Envelopment Analysis (DEA), a linear programming technique used to evaluate the efficiency of decision-making units like organizations. DEA can handle multiple inputs and outputs to measure efficiency relative to best practices.
2) Transportation problems, which aim to minimize costs in transporting goods from origins to destinations, can be formulated as linear programs and solved using techniques like the simplex method. Initial basic feasible solutions are found using methods like the Northwest Corner Rule.
3) The document provides an example of using DEA and transportation problem solving methods to optimize the allocation of milk transportation from dairy plants to distribution centers to minimize costs.
This document provides an overview of business research including definitions, types of research, research process and methodology. It discusses quantitative vs qualitative research, descriptive vs explanatory research, and basic vs applied research. It also outlines research applications in various business functions like marketing, finance, human resources and production. Additionally, it covers research process, data sources, questionnaire method, measurement scales, sampling techniques and criteria for good research.
Data Analysis & Interpretation and Report WritingSOMASUNDARAM T
Statistical Methods for Data Analysis (Only Theory), Meaning of Interpretation, Technique of Interpretation, Significance of Report Writing, Steps, Layout of Research Report, Types of Research Reports, Precautions while writing research reports
Research is a systematic and scientific method of finding solutions by obtaining various types of data and systematic analysis of the multiple aspects of the issues related.
The techniques or the specific procedure which helps to identify, choose, process, and analyze information about a subject is called Research Methodology
Experimental design is a statistical tool for improving product design and solving production problems.
The document outlines key aspects of research methodology including:
1. The objectives of research such as defining problems, formulating hypotheses, collecting and evaluating data, making deductions, and testing conclusions.
2. The different types of research including descriptive, applied, quantitative, conceptual, empirical, qualitative, fundamental, and analytical research.
3. The methods of collecting data including primary methods like questionnaires, observations, interviews, and schedules and secondary methods of collecting published and unpublished data from various sources.
This document provides an outline for a course on business research methods. It covers 7 chapters that introduce key concepts in research methodology. Chapter 1 defines research and distinguishes between research methods and methodology. It also discusses research types and processes. Chapter 2 addresses selecting research topics and problems. Chapter 3 focuses on literature reviews and hypothesis formulation. Chapter 4 examines research designs, approaches, data collection and analysis. Chapter 5 is about writing research proposals. Chapter 6 discusses data analysis and interpretation. Chapter 7 is on communicating research results. The evaluation scheme includes a research proposal, article review, and final exam worth varying points totaling 100.
There are two types of data: primary and secondary. Primary data is collected directly by the researcher through methods like questionnaires, observations, interviews, and surveys. Secondary data is previously collected data from sources like government publications, journals, and reports.
Data collection methods for primary data include questionnaires, observations made without controlling the situation, interviews between a researcher and participant, and surveys administered through enumerators. Secondary data comes from published sources like government documents and unpublished sources from individuals and organizations.
After collection, data must be processed which includes editing, coding, classification, and tabulation to organize it for analysis. Different types of analysis are then used like descriptive, correlation, multivariate, and inferential analysis. Hypotheses are
Resource management techniques involve efficiently using an organization's limited resources such as employees, equipment, and finances. Some key techniques include:
1. Linear programming, which uses mathematical models to determine the optimal allocation of resources to meet objectives and constraints. An example is determining the optimal product mix.
2. Operations research, which applies scientific principles and quantitative analysis to help maximize efficiency. It has been widely used by militaries and businesses since World War II.
3. Modeling real-world problems mathematically and using algorithms to determine the best solutions while optimizing objectives under constraints. This allows organizations to best utilize their resources.
This document discusses mixed methods research. It defines mixed methods research as integrating both quantitative and qualitative data collection and analysis within a single study. The document outlines the basic characteristics, types of designs, steps, and advantages and disadvantages of mixed methods research. It discusses when mixed methods is appropriate and reasons for using it, such as to explain findings or address questions at different levels. The four main mixed methods designs are explanatory, exploratory, embedded, and triangulation designs.
This document provides information about getting fully solved assignments from an assignment help service. It lists the contact email and phone number and specifies the programs and subjects they can provide assignments for, including research methodology, management subjects for various semesters, and more. It also provides an example of a research methodology assignment question that is answered in detail.
The document discusses four major types of evaluation methods: case study, statistical analysis, field experiment, and survey research. It provides details on case study methods, including definitions, types of case studies, and steps to conducting a case study. Statistical analysis methods are also summarized, including descriptive statistics such as frequency counts and distributions, and measures of central tendency and variability. Mathematical modeling as a research method is briefly outlined.
This document provides an overview of basic statistical concepts. It discusses that statistics involves collecting, organizing, analyzing, and interpreting quantitative data. There are two main divisions of statistics: descriptive statistics, which are used to summarize and describe basic features of data, and inferential statistics, which are used to make inferences about populations based on samples. The document also covers topics such as populations and samples, levels of measurement, data collection methods, sampling techniques, and ways to present statistical data through tables, graphs, and other visual formats.
This document discusses topics related to quantitative research methods and data analytics, including simple linear regression. It outlines course assignments, with the final coursework assignment involving selecting a topic of interest, collecting related data, applying quantitative research methods learned in the course to analyze the data in RStudio, and writing a 2000-word report on the findings. The report should include sections on the introduction, data, results, and conclusion. Assessment will be based on rubrics evaluating these sections. The document also provides overviews of key concepts like bootstrapping, introduction to regression, and simple linear regression.
Here are the steps I would take to analyze this data using exploratory factor analysis:
1. Check assumptions
- Sample size of 300 is adequate
- Most correlations are between .3 and .8
2. Extract initial factors using principal axis factoring
- Kaiser's criterion suggests 4 factors with eigenvalues > 1
3. Rotate factors orthogonally using varimax rotation
- This will make the factor structure more interpretable
4. Interpret the factors based on which items have strong loadings
- Factor 1 relates to anxiety about learning SPSS
- Factor 2 relates to anxiety about using computers
- Factors 3 and 4 may reflect other aspects of statistics anxiety
5. Compute factor scores if desired to use in further
This document provides an overview of research methodology. It discusses the meaning and objectives of research, as well as types of research including descriptive, applied, quantitative, conceptual, empirical, qualitative, fundamental, and analytical research. It also distinguishes between research methods and research methodology. The document outlines various sampling methods, data collection methods, data analysis techniques, hypothesis testing, and the steps involved in interpreting and presenting research findings in a report.
This document provides an overview and template for conducting independent research. It discusses key aspects of the research process such as defining the research problem, identifying independent and dependent variables, developing hypotheses, choosing an appropriate research methodology, collecting and analyzing data, and presenting conclusions. Sample topics are provided to illustrate each step, such as examining factors that could contribute to an university's internet server crashing each July. The document concludes by listing references that were consulted in creating the research overview and template.
Introduction to Quantitative Research MethodsIman Ardekani
This document provides an introduction to quantitative research methods. It discusses key concepts like research methodology, variables, hypotheses, experimental design, and statistical analysis. Specifically, it covers:
- The difference between research methodology and methods, and examples of methodology scopes.
- Key terms like variables, hypotheses, and types of errors in hypothesis testing.
- How to plan, conduct, and analyze experiments, including best-guess experiments and one-factor-at-a-time experiments.
- Basic statistical concepts like mean, variance, normal distribution, and the t-distribution.
- Types of experimental designs like factorial experiments and comparative experiments.
pratik meshram-Unit 4 contemporary marketing research full notes pune univers...Pratik Meshram
Unit 4 discusses data analysis and hypothesis testing. It covers topics such as data analysis, hypothesis, conjoint analysis, and factor analysis. Data analysis involves collecting, processing, analyzing, and interpreting data. A hypothesis is a proposition that can be tested. The key steps in hypothesis testing are to formulate hypotheses, select a significance level, choose a test criterion, and make a decision to accept or reject the null hypothesis. Common hypothesis tests include z-tests, t-tests, F-tests, chi-square tests, and ANOVA.
This document outlines the key aspects of research including: defining research as a systematic process of investigating a problem through collecting data to answer a question; describing the main types of research such as fundamental, quantitative, applied, and qualitative; and explaining the common steps of research such as formulating the problem, developing hypotheses, collecting and analyzing data, and reporting results. The overall goal of research is to increase knowledge and understanding of a topic.
This document discusses the analysis of quantitative and qualitative data in research. It describes the key steps in analyzing quantitative data, including data preparation, compilation, editing, coding, classification, tabulation, descriptive statistics, inferential statistics, and interpreting results. For qualitative data analysis, it outlines ordering and reducing data, summarizing data using various techniques, drawing conclusions, reporting findings, and establishing validity.
The document discusses various steps involved in processing and analyzing qualitative and quantitative data. It describes processes like editing, classification, tabulation, content analysis and quantitative data analysis either manually or using computer software. Classification can be done based on attributes or class intervals. Tabulation involves arranging data in tables for further analysis. Content analysis involves identifying themes and coding responses. Quantitative data can be analyzed manually for small samples or using software like SPSS.
Advanced Research Methodology Session-4.pptxHarariMki1
This document outlines the key steps in deductive and inductive research processes. It discusses:
- The deductive process works from general theories to specific facts in a top-down manner, while the inductive process works bottom-up from specific facts to broader generalizations.
- The main steps of research include developing hypotheses, designing the study, collecting and analyzing data, testing hypotheses, generalizing results, and reporting findings.
- Research design considerations include variables, sampling, data collection methods, and analysis techniques. Both qualitative and quantitative approaches are discussed.
- Managing biases, organizing analysis, and clearly reporting results are important aspects of the research process.
Abhay Bhutada, the Managing Director of Poonawalla Fincorp Limited, is an accomplished leader with over 15 years of experience in commercial and retail lending. A Qualified Chartered Accountant, he has been pivotal in leveraging technology to enhance financial services. Starting his career at Bank of India, he later founded TAB Capital Limited and co-founded Poonawalla Finance Private Limited, emphasizing digital lending. Under his leadership, Poonawalla Fincorp achieved a 'AAA' credit rating, integrating acquisitions and emphasizing corporate governance. Actively involved in industry forums and CSR initiatives, Abhay has been recognized with awards like "Young Entrepreneur of India 2017" and "40 under 40 Most Influential Leader for 2020-21." Personally, he values mindfulness, enjoys gardening, yoga, and sees every day as an opportunity for growth and improvement.
The document outlines key aspects of research methodology including:
1. The objectives of research such as defining problems, formulating hypotheses, collecting and evaluating data, making deductions, and testing conclusions.
2. The different types of research including descriptive, applied, quantitative, conceptual, empirical, qualitative, fundamental, and analytical research.
3. The methods of collecting data including primary methods like questionnaires, observations, interviews, and schedules and secondary methods of collecting published and unpublished data from various sources.
This document provides an outline for a course on business research methods. It covers 7 chapters that introduce key concepts in research methodology. Chapter 1 defines research and distinguishes between research methods and methodology. It also discusses research types and processes. Chapter 2 addresses selecting research topics and problems. Chapter 3 focuses on literature reviews and hypothesis formulation. Chapter 4 examines research designs, approaches, data collection and analysis. Chapter 5 is about writing research proposals. Chapter 6 discusses data analysis and interpretation. Chapter 7 is on communicating research results. The evaluation scheme includes a research proposal, article review, and final exam worth varying points totaling 100.
There are two types of data: primary and secondary. Primary data is collected directly by the researcher through methods like questionnaires, observations, interviews, and surveys. Secondary data is previously collected data from sources like government publications, journals, and reports.
Data collection methods for primary data include questionnaires, observations made without controlling the situation, interviews between a researcher and participant, and surveys administered through enumerators. Secondary data comes from published sources like government documents and unpublished sources from individuals and organizations.
After collection, data must be processed which includes editing, coding, classification, and tabulation to organize it for analysis. Different types of analysis are then used like descriptive, correlation, multivariate, and inferential analysis. Hypotheses are
Resource management techniques involve efficiently using an organization's limited resources such as employees, equipment, and finances. Some key techniques include:
1. Linear programming, which uses mathematical models to determine the optimal allocation of resources to meet objectives and constraints. An example is determining the optimal product mix.
2. Operations research, which applies scientific principles and quantitative analysis to help maximize efficiency. It has been widely used by militaries and businesses since World War II.
3. Modeling real-world problems mathematically and using algorithms to determine the best solutions while optimizing objectives under constraints. This allows organizations to best utilize their resources.
This document discusses mixed methods research. It defines mixed methods research as integrating both quantitative and qualitative data collection and analysis within a single study. The document outlines the basic characteristics, types of designs, steps, and advantages and disadvantages of mixed methods research. It discusses when mixed methods is appropriate and reasons for using it, such as to explain findings or address questions at different levels. The four main mixed methods designs are explanatory, exploratory, embedded, and triangulation designs.
This document provides information about getting fully solved assignments from an assignment help service. It lists the contact email and phone number and specifies the programs and subjects they can provide assignments for, including research methodology, management subjects for various semesters, and more. It also provides an example of a research methodology assignment question that is answered in detail.
The document discusses four major types of evaluation methods: case study, statistical analysis, field experiment, and survey research. It provides details on case study methods, including definitions, types of case studies, and steps to conducting a case study. Statistical analysis methods are also summarized, including descriptive statistics such as frequency counts and distributions, and measures of central tendency and variability. Mathematical modeling as a research method is briefly outlined.
This document provides an overview of basic statistical concepts. It discusses that statistics involves collecting, organizing, analyzing, and interpreting quantitative data. There are two main divisions of statistics: descriptive statistics, which are used to summarize and describe basic features of data, and inferential statistics, which are used to make inferences about populations based on samples. The document also covers topics such as populations and samples, levels of measurement, data collection methods, sampling techniques, and ways to present statistical data through tables, graphs, and other visual formats.
This document discusses topics related to quantitative research methods and data analytics, including simple linear regression. It outlines course assignments, with the final coursework assignment involving selecting a topic of interest, collecting related data, applying quantitative research methods learned in the course to analyze the data in RStudio, and writing a 2000-word report on the findings. The report should include sections on the introduction, data, results, and conclusion. Assessment will be based on rubrics evaluating these sections. The document also provides overviews of key concepts like bootstrapping, introduction to regression, and simple linear regression.
Here are the steps I would take to analyze this data using exploratory factor analysis:
1. Check assumptions
- Sample size of 300 is adequate
- Most correlations are between .3 and .8
2. Extract initial factors using principal axis factoring
- Kaiser's criterion suggests 4 factors with eigenvalues > 1
3. Rotate factors orthogonally using varimax rotation
- This will make the factor structure more interpretable
4. Interpret the factors based on which items have strong loadings
- Factor 1 relates to anxiety about learning SPSS
- Factor 2 relates to anxiety about using computers
- Factors 3 and 4 may reflect other aspects of statistics anxiety
5. Compute factor scores if desired to use in further
This document provides an overview of research methodology. It discusses the meaning and objectives of research, as well as types of research including descriptive, applied, quantitative, conceptual, empirical, qualitative, fundamental, and analytical research. It also distinguishes between research methods and research methodology. The document outlines various sampling methods, data collection methods, data analysis techniques, hypothesis testing, and the steps involved in interpreting and presenting research findings in a report.
This document provides an overview and template for conducting independent research. It discusses key aspects of the research process such as defining the research problem, identifying independent and dependent variables, developing hypotheses, choosing an appropriate research methodology, collecting and analyzing data, and presenting conclusions. Sample topics are provided to illustrate each step, such as examining factors that could contribute to an university's internet server crashing each July. The document concludes by listing references that were consulted in creating the research overview and template.
Introduction to Quantitative Research MethodsIman Ardekani
This document provides an introduction to quantitative research methods. It discusses key concepts like research methodology, variables, hypotheses, experimental design, and statistical analysis. Specifically, it covers:
- The difference between research methodology and methods, and examples of methodology scopes.
- Key terms like variables, hypotheses, and types of errors in hypothesis testing.
- How to plan, conduct, and analyze experiments, including best-guess experiments and one-factor-at-a-time experiments.
- Basic statistical concepts like mean, variance, normal distribution, and the t-distribution.
- Types of experimental designs like factorial experiments and comparative experiments.
pratik meshram-Unit 4 contemporary marketing research full notes pune univers...Pratik Meshram
Unit 4 discusses data analysis and hypothesis testing. It covers topics such as data analysis, hypothesis, conjoint analysis, and factor analysis. Data analysis involves collecting, processing, analyzing, and interpreting data. A hypothesis is a proposition that can be tested. The key steps in hypothesis testing are to formulate hypotheses, select a significance level, choose a test criterion, and make a decision to accept or reject the null hypothesis. Common hypothesis tests include z-tests, t-tests, F-tests, chi-square tests, and ANOVA.
This document outlines the key aspects of research including: defining research as a systematic process of investigating a problem through collecting data to answer a question; describing the main types of research such as fundamental, quantitative, applied, and qualitative; and explaining the common steps of research such as formulating the problem, developing hypotheses, collecting and analyzing data, and reporting results. The overall goal of research is to increase knowledge and understanding of a topic.
This document discusses the analysis of quantitative and qualitative data in research. It describes the key steps in analyzing quantitative data, including data preparation, compilation, editing, coding, classification, tabulation, descriptive statistics, inferential statistics, and interpreting results. For qualitative data analysis, it outlines ordering and reducing data, summarizing data using various techniques, drawing conclusions, reporting findings, and establishing validity.
The document discusses various steps involved in processing and analyzing qualitative and quantitative data. It describes processes like editing, classification, tabulation, content analysis and quantitative data analysis either manually or using computer software. Classification can be done based on attributes or class intervals. Tabulation involves arranging data in tables for further analysis. Content analysis involves identifying themes and coding responses. Quantitative data can be analyzed manually for small samples or using software like SPSS.
Advanced Research Methodology Session-4.pptxHarariMki1
This document outlines the key steps in deductive and inductive research processes. It discusses:
- The deductive process works from general theories to specific facts in a top-down manner, while the inductive process works bottom-up from specific facts to broader generalizations.
- The main steps of research include developing hypotheses, designing the study, collecting and analyzing data, testing hypotheses, generalizing results, and reporting findings.
- Research design considerations include variables, sampling, data collection methods, and analysis techniques. Both qualitative and quantitative approaches are discussed.
- Managing biases, organizing analysis, and clearly reporting results are important aspects of the research process.
Abhay Bhutada, the Managing Director of Poonawalla Fincorp Limited, is an accomplished leader with over 15 years of experience in commercial and retail lending. A Qualified Chartered Accountant, he has been pivotal in leveraging technology to enhance financial services. Starting his career at Bank of India, he later founded TAB Capital Limited and co-founded Poonawalla Finance Private Limited, emphasizing digital lending. Under his leadership, Poonawalla Fincorp achieved a 'AAA' credit rating, integrating acquisitions and emphasizing corporate governance. Actively involved in industry forums and CSR initiatives, Abhay has been recognized with awards like "Young Entrepreneur of India 2017" and "40 under 40 Most Influential Leader for 2020-21." Personally, he values mindfulness, enjoys gardening, yoga, and sees every day as an opportunity for growth and improvement.
Lecture slide titled Fraud Risk Mitigation, Webinar Lecture Delivered at the Society for West African Internal Audit Practitioners (SWAIAP) on Wednesday, November 8, 2023.
1. Elemental Economics - Introduction to mining.pdfNeal Brewster
After this first you should: Understand the nature of mining; have an awareness of the industry’s boundaries, corporate structure and size; appreciation the complex motivations and objectives of the industries’ various participants; know how mineral reserves are defined and estimated, and how they evolve over time.
Vicinity Jobs’ data includes more than three million 2023 OJPs and thousands of skills. Most skills appear in less than 0.02% of job postings, so most postings rely on a small subset of commonly used terms, like teamwork.
Laura Adkins-Hackett, Economist, LMIC, and Sukriti Trehan, Data Scientist, LMIC, presented their research exploring trends in the skills listed in OJPs to develop a deeper understanding of in-demand skills. This research project uses pointwise mutual information and other methods to extract more information about common skills from the relationships between skills, occupations and regions.
Understanding how timely GST payments influence a lender's decision to approve loans, this topic explores the correlation between GST compliance and creditworthiness. It highlights how consistent GST payments can enhance a business's financial credibility, potentially leading to higher chances of loan approval.
2. Elemental Economics - Mineral demand.pdfNeal Brewster
After this second you should be able to: Explain the main determinants of demand for any mineral product, and their relative importance; recognise and explain how demand for any product is likely to change with economic activity; recognise and explain the roles of technology and relative prices in influencing demand; be able to explain the differences between the rates of growth of demand for different products.
"Does Foreign Direct Investment Negatively Affect Preservation of Culture in the Global South? Case Studies in Thailand and Cambodia."
Do elements of globalization, such as Foreign Direct Investment (FDI), negatively affect the ability of countries in the Global South to preserve their culture? This research aims to answer this question by employing a cross-sectional comparative case study analysis utilizing methods of difference. Thailand and Cambodia are compared as they are in the same region and have a similar culture. The metric of difference between Thailand and Cambodia is their ability to preserve their culture. This ability is operationalized by their respective attitudes towards FDI; Thailand imposes stringent regulations and limitations on FDI while Cambodia does not hesitate to accept most FDI and imposes fewer limitations. The evidence from this study suggests that FDI from globally influential countries with high gross domestic products (GDPs) (e.g. China, U.S.) challenges the ability of countries with lower GDPs (e.g. Cambodia) to protect their culture. Furthermore, the ability, or lack thereof, of the receiving countries to protect their culture is amplified by the existence and implementation of restrictive FDI policies imposed by their governments.
My study abroad in Bali, Indonesia, inspired this research topic as I noticed how globalization is changing the culture of its people. I learned their language and way of life which helped me understand the beauty and importance of cultural preservation. I believe we could all benefit from learning new perspectives as they could help us ideate solutions to contemporary issues and empathize with others.
How Does CRISIL Evaluate Lenders in India for Credit RatingsShaheen Kumar
CRISIL evaluates lenders in India by analyzing financial performance, loan portfolio quality, risk management practices, capital adequacy, market position, and adherence to regulatory requirements. This comprehensive assessment ensures a thorough evaluation of creditworthiness and financial strength. Each criterion is meticulously examined to provide credible and reliable ratings.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
How Non-Banking Financial Companies Empower Startups With Venture Debt Financing
Semester IV Exam Notes.pdf
1. 1.
1.
2.
3.
Semester IV Exam Notes
Theory OR
What is transportation problem?
The transportation problem is a special type of linear programming problem where the objective
consists in minimizing transportation cost of a given commodity from a number of sources or
origins (e.g. factory, manufacturing facility) to a number of destinations (e.g. warehouse,
store). Each source has a limited supply (i.e. maximum number of products that can be sent
from it) while each destination has a demand to be satisfied (i.e. minimum number of products
that need to be shipped to it). The cost of shipping from a source to a destination is directly
proportional to the number of units shipped.
B. Types of Transportation Problems
There are two different types of transportation problems based on the initial given information:
Balanced Transportation Problems: cases where the total supply is equal to the total demand.
Unbalanced Transportation Problems: cases where the total supply is not equal to the total
demand. When the supply is higher than the demand, a dummy destination is introduced in the
equation to make it equal to the supply (with shipping costs of $0); the excess supply is
assumed to go to inventory. On the other hand, when the demand is higher than the supply, a
dummy source is introduced in the equation to make it equal to the demand (in these cases
there is usually a penalty cost associated for not fulfilling the demand).
In order to proceed with the solution of any given transportation problem, the first step consists
in verifying if it is balanced. If it is not, it must be balanced accordingly.
what is feasible solution and non degenerate solution in transportation problem?
Feasible Solution: A feasible solution to a transportation problem is a set of non-negative values
x, (i = 1, 2,
... m, j= 1,2, ... n) that satisfies the constraints.
Non-degenerate basic feasible solution: If a basic feasible solution to a transportation problem
contains
exactly m + n - 1 allocations in independent positions, it is called a Non-degenerate basic
feasible solution.
Here m is the number of rows and n is the number of columns in a transportation problem.
A. What do you mean by balanced transportation problem
2. 3.
4.
5.
Ans - balanced transportation problem is a transportation problem where the total availability at
the origins is equal to the total requirements at the destinations.
B. Methods of solving Transportation method
There are three ways for determining the initial basic feasible solution. They are
1. NorthWest Corner Cell Method.
2. Vogel’s Approximation Method (VAM).
3. Least Call Cell Method.
What is the Assignment problem?
The assignment problem is a special case of linear programming problem; it is one of the
fundamental combinational optimization problems in the branch of optimization or operations
research in mathematics. Its goal consists in assigning m resources (usually workers) to n tasks
(usually jobs) one a one to one basis while minimizing assignment costs. As a general rule, all
jobs must be performed by exactly one worker and every worker must be assigned exclusively
to one job. Any worker can be assigned to perform any job, incurring in some cost that may vary
depending on the work-job assignment.
Give mathematical form of assignment problem.
Mathematical Formulation:
Any basic feasible solution of an Assignment problem consists (2n – 1) variables of which the (n
– 1) variables are zero, n is number of jobs or number of facilities. Due to this high degeneracy,
if we solve the problem by usual transportation method, it will be a complex and time consuming
work. Thus a separate technique is derived for it. Before going to the absolute method it is very
important to formulate the problem.
Suppose xjj is a variable which is defined as
1 if the ith job is assigned to jth machine or facility
3. .
.
What is the difference between Assignment Problem and Transportation Problem?
Explain the steps of graphical methods for the solution of LPP and explain its limitation
We can solve the LPP with the graphical
method by following these steps
Step 1 : First of all, formulate the LP problem.
Step 2 : Then, make a graph and plot the constraint lines over there.
Step 3 : Determine the valid part of each constraint line.
Step 4 : Recognize the possible solution area.
Step 5: Place the objective function in the graph.
4. Step 5: Place the objective function in the graph.
Step 6 : Finally, find out the optimum point.
Limitations are
The graphical method is one of the easiest way to solve a small LP problem. However this is
useful only when the decision variables are not
more than two.
It is not possible to plot the solution on a two-dimensional graph when there are more than two
variables and we must turn to more complex methods.
Another limitation of graphical method is that, an incorrect or inconsistent graph will produce
inaccurate answers, so one need to be very careful while drawing and plotting the graph.
Theory Research Methodology
M1 Nature and scope of RM
Q 1 - What are the types of research?
•Quantitative research
Quantitative refers to the number where the data is collected based on numbers (numeric form)
Example - car manufacturers can compare no of sales of red sedans to white.
•Qualitative research
Qualitative refers to the non numerical form of data in research. It helps to form a better
summary in terms of theories in data.
Example -
•Fundamental research
It is a research which is generally conducted to develop new theorie. It is also known as basic
research. It mainly focuses on generalization and formulation of theory
Example- Research studies that are concerned with human behavior, its conducted by devoting
in generating knowledge in a particular area of interest.
•Applied research
Its a research which is usually conducted to solve the problem of the organization. It is also
5. Its a research which is usually conducted to solve the problem of the organization. It is also
called action research. It is deductive in nature whcih means it keeps same theories as its base
while conducting research so as to generate solution.
Example - it can be used to find out conclusion/ solution to business problem.
•Descriptive research
It is a type of research which describes a population, situation or phenomenon that is being
studied. It focuses on answering the how what when and where questions in a research problem
than just why. It is important to have a paper understanding of what a research problem is
about, before investigating why it exists at the first place.
Example-
•Analytic research
It is a type of research where the researcher uses facts or information that is already available
and analyze them ti make a critical evaluation of the material.
•Exploratory research
It is defined as a research used to investigate a problem which is not clearly defined. It is
conducted to have better understanding at the existing problem but usually doesn’t lead to a
conclusive result.
Example- a study into the implications of covid-19 pandemic into the global economy.
•Conclusive research
It is used to obtain information that can be used to reach conclusions to make decisions. The
data collected in this research is generally quantitative in nature and therefore it takes
numerical values. The information needed must be clearly defined.
•Casual research
It is a type of conclusive research which attempts to establish a cause and effect relationship
between two or more variables.
•Conceptual research
It is a type of research which is related to same abstract idea or theory. It is generally used by
philosophers and thinkers to develop new concepts kr to reinspect existing ones.
•Empirical research
It is a type of study where the conclusion of the study is strictly drawn from observation or
experiments.
6. Q 2 - What is research design and its types
It is a structural framework of various research methods as well as techniques that are chosen
by a researcher. It refers to a he overall strategy utilized to carry out research that defines a suc
and logical plan to tackle established research questions through collection, interpretation
analysis and discussion of data.
Types
•Explanatory
•Descriptive
•Experimental - Experimental research is a scientific method of conducting research using two
variables: independent and dependent
Q 3 - Name the steps in research process
•Selection of research problem
•Reviewing literature
•Making hypothesis
•Preparing for research design
•Deciding on the sample design
•Data collection
•Processing and analyzing data
•Preparing of the report
Q 4 - What are the types of approaches in research
•Deductive
This approach tests the validity of assumptions ie theories of hypothesis. If there is no theory
one cant conduct deductive research.
•Inductive
It contributes yo the emergence of new theory and generalization. Data collection is used to
explore a phenomenon, identify themes and patterns and create a conceptual framework.
•Quantitative
It emphasizes the objective measures and the statistical mathematical or numeric analysis of
data. It focuses on gathering numerical data in order to explain a particular phenomenon.
7. –
–
–
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•Qualitative
It emphasizes on the subjective assessments of attitudes opinions and behavior. Such an
approach in research is generates results in non quantitative form. Focus groups, questions,
interviews etc are the technique used.
M2 Research methods and data collection techniques
Q 1 - What is data collection methods? And its types
•Data collection method
The task of data collection begins after the research problem has been defined and the
research design plan has been called out.
The researcher has to keep in mind about the two types of data ie primary and secondary.
Primary data is a type of data that is collected by researching directly from main sources
through interviews, surveys, etc and it happens to be original in character.
Few methods of collecting primary data are
observation methods
Interviews
Questionnaire
Survey
The secondary data is a data that has been already collected through primary sources and
made readily available for researches to use for their research. Its basically the data has been
collected in the past.
•Observation method
•Questionnaire method
•Surveys
•Publications
Q 2 - Explain the six steps to good questionnaire design
8. •Identity your research aim and the goal of your questionnaire
•Define target respondents
•Develop questions
•Choose your question type
•Design question sequence and overall layout
•Piloting the questionnaire
Q 3 - Explain the types of questions
•Close ended questions
•Open ended questions
•Multiple choice question
•Rating survey questions
•Likest scale questions
•Drop down questions
Q 4 - What is attitude measurement survey?
An attitude measurement survey is a study, on a properly drawn sample, of a specified
population to find out what people in that population feel about a specified issue.
explanatory context. Attitude surveys usually use carefully constructed, standardised
questionnaires.
Q 5 - What is scaling techniques and what are its types
Definition: Scaling technique is a method of placing respondents in continuation of
gradual change in the pre-assigned values, symbols or numbers based on the
features of a particular object as per the defined rules.
Types of scale
Qualitative research mostly uses descriptive statements to seek answers to the
research questions, whereas in quantitative research these answers are usually sough
on one of the measurement scales (nominal, ordinal, interval or ratio).
> Those scales which have a unit of measurement (interval and ratio) are considered to be more
refined, objective and accurate. On the other hand, nominal and ordinal scale (used for rankings
etc) are considered subjective and hence not as accurate as they do not have a unit of
9. measurement per se.
> The greater the refinement in the unit of measurement of a variable, the better.
> Steve classified the different types of scale into four categories
•Nominal scale
A nominal scale is a scale of measurement used to assign events or objects into
discrete categories. This form of scale does not require the use of numeric values or
categories ranked by class, but simply unique identifiers to label each distinct category.
•Ordinal scale
The Ordinal scale includes statistical data type where variables are in order or rank
but without a degree of difference between categories. The ordinal scale contains
qualitative data; "ordinal' meaning 'order.
Example - movie ratings
•Interval scale
Example - celsius, Fahrenheit
•Ratio scale
Example - measuring income, age etc
Q 6 - What is sampling frame ?
•Its a list of all the items in the research. Its a complete list of everyone or everything a
researcher wants to study.
•It is a source material from which a sample is drawn. It is also a list of all these within a
population who can be sampled and may include individuals, households or institutes etc.
Q 7 - What is sample design ? Name its types.
A sample design is a definite plan for obtaining a sample from a given population. It refers to
the technique or the procedure the researcher would adopt in selecting items for the sample.
•Probability sampling
•Non- Probability sampling
10. Types of probability sampling
•Simple random sampling
•Systematic sampling
•Stratified sampling
•Clustered sampling
Types of non probability sampling
•Judgement
•Quota
•Snowball
•Convenience
Q 8 - what is sampling and not sampling errors ?
Sampling error - Its a statistical error that occurs when an analyst does not select a sample that
represents the entire population and data. As a result, the result found in the sample don’t
represent the result that would be obtained from the entire population.
Non sampling errors - Its a term used in statistics that refers to an error that occurs during data
collection, causing the data to differ from the true value. It refers to either random or systematic
errors and these errors can be challenging to spot in surveys, samples etc.
Q 9 - What is editing tabulating and validating of data?
•Editing data
•Coding of data
•Clarification of data
•Tabulation of data
Editing is the procedure that improves the quality of the data for coding. With coding the
stage is ready for tabulation. Tabulation is a part of the technical procedure wherein the
classified data are put in the form of tables.
M3 Data analysis techniques
Q 1 - What is multivariate? State its characteristic, applications and advantages, disadvantages
and limitations
11. Multivariate is having or involving a number of independent mathematical or statisti
multivariate calculus multivariate data analysis.
M4 field project and report writing
Q 1 what are the common problems that arise while preparing the research report
Random question ans
Q 1 - Essentials of good questionnaire
1. The length of questionnaire should be proper one.
2. The language used should be easy and simple.
3. The term used are explained properly.
4. The questions should be arranged in a proper way.
5. The questions shouts be in logical manner
6. The questions should be in analytical form.
7. Complex questions should be broken into filter questions
8. The questions should be described precisely and correctly.
9. The questionnaire should be constructed for a specific period of time.
10. The questions should be moving around the theme of the investigator.
11. The answers should be short and simple.
12. These answers should be accurate.
13. The answers should be direct one.
14. The answers should be relevant to the problem.
15. The answers should be understand able to everyone of respondents.
Q 2 - What is Hypothesis?
A hypothesis is an assumption that is made based on some evidence. This is the initial point of
any
investigation that translates the research questions into predictions. It includes components
like variable, population and the relation between the variables. A research hypothesis is a
hypothesis that is used to test
12. the relationship between two or more variables.
Characteristics of Hypothesis
Following are the characteristics of hypothesis:
The hypothesis should be clear and precise to consider it to be reliable.
• If the hypothesis is a relational hypothesis, then it should be stating the relationship between
varia
• The hypothesis must be specific and should have scope for conducting more tests.
• The way of explanation of the hypothesis must be very simple and it should also be
understood tha
simplicity of the hypothesis is not related to its significance.
Q 3 - Correlation and regression
Q 4 - What is cluster analysis and state its business application
13. .
.
Cluster analysis is an exploratory data analysis tool which aims at sorting different objects
into groups in a way that the degree of association between two objects is maximal if they
belong to the same group and minimal otherwise.
Business application of clustering.
•Market segmentation
•Analyzing and understanding buyers behavior
•Anomaly detection
•Identification of new product opportunities
•Data reduction
Theory Export management
M1 Introduction to export management
Q 1 - what is export management ?
•Export management means conducting the export activity in an orderly, efficient and profitable
manner.
• Since the heart of each business is marketing, export management can be termed as export
marketing management.
•Because it needs to be managed efficiently so that the export should increase and exporter
should get more profit and importer should get more satisfaction.
• Export management means managing export marketing activity efficiently, smoothly and in an
orderly manner
Q 2 - Two levels of EM? And their need
National level
Business level
National level
•Earning foreign Exchange
•International Relations
•Balance of payments
•Economic Growth
•Reputation in the World
•Employment
14. •Research and Development
•Standard of Living
Business level
•Export obligation
•Higher profits
•Reputation and goodwill
•Imports being liberalized
•Government incentives and schemes
Q 3 - Explain the EM Process
•Identifying export product
•Market selection
•Swot analysis
•Export license
•Export pricing and costing
•Understanding of foreign exchange rates
•Export risk management
•Packing and labelling of goods
Q 4 - Give successful exported business models
•E bay
•Starbucks
•Ikea
•McDonalds
•7-eleven
Q 5 - Who is an export manager and explain his functions and list requirements to be a em.
•An export manager serves as intermediary between foreign buyers and domestic sellers.
Unlike trading companies who buy the products before selling directly to foreign buyers, export
managers find buyers internationally for a domestic manufacturer that employ them.
• A export manager plans and coordinates the international shipment of goods. During the
course of the day, he/she may negotiate with a variety of people, such as shippers, agents and
vendors, and are expected to have excellent customer service skills in dealing with customers.
•Export managers are also often responsible for personnel management, which often includes
15. the hiring, training and supervision of the international department staff
• In their accounting function, export managers may keep track of invoices and prepare
reports to expedite the billing process. They may also have to ensure that shipments are
in compliance with the laws and regulations governing the export industry.
• They have also to negotiate Exporttt Contracts.
• While there are no specific requirements for entry into this profession, most employers
(mainly new exporters) require that candidates have at least a high school education, and many
prefer an university degree mainly in marketing or business administration. However,
experience in the industry may often substitute for the lack of a degree. Extensive knowledge of
languages (Spanish, French, German and Chinese) is also appreciated
Q 6 Explain the organizational structure of export firm and its types
•Initial division structure
Initial division structures are common in subsidiaries, export firms, and on-site
manufacturers. Subsidiaries that follow this kind of organization structure include firms where
the main export is expertise, for example, consultants and financial firms. Export firms include
those having technologically advanced products and manufacturing units. Companies
having on-site manufacturing operations follow this structure to cut down their costs
•International division structure
This structure is built to handle all international operations by a division created for control. It is
often adopted by firms that are still in the development stages of international business
operations.
•Global product division
Global product divisions include domestic divisions that are allowed to take global responsibility
for product groups. These divisions operate as profit centers.
•Global Area division
Global area division structure is used for operations that are controlled on a geographic rather
than a product basis. Firms in mature businesses with select product lines use it.
•Global functional division
16. This structure is to primarily organize global operations based on function; product orientation
is secondary for firms using global function division structure
•Mixed matrix
This structure combines global product, area, and functional arrangements and it has a cross-
cutting committee structure.
Q 7 - State the export prospects for small firms
• Increase your overall sales and profits.
•Increase the scope of your business making you more competitive domestically.
•Take advantage of relatively lower costs of transportation.
•Take advantage of the ongoing reduction in trade barriers thanks to recent trade agreements.
•Reduce your total reliance on a single domestic market.
•Extend and broaden your customer base.
•Add sustainable life into your line of current products.
•Flatten out seasonal product use and market fluctuations to achieve a more even production
schedule and sales performance.
• Take advantage of current favorable exchange rates that make U.S. goods and services even
more of a bargain to foreign buyers.
•Reduce available excess inventory or excess production capacity and staffing due to the
struggling domestic economy.
•Take advantage of improvements in trade finance, the internet, and trade agreements that have
dramatically increased access to worldwide markets.
•Exporting can be lucrative for businesses of all sizes. On average, sales grow faster, more jobs
are created, and employees earn more than in non-exporting firms.
Q 8 - If exporting is beneficial to the growth and profit of a company, then why don't more small
companies actually export?
The pretext for not exporting most often involves three explanations.
•First, companies say they do not know how to get started.
•Second, companies claim that they do not have the staff with adequate export knowledge
about how to go about entering the export arena and how to follow through once orders are
received.
•Third, companies say they would export if they had a level playing field.
17. M2 Setting up Export Firm and Product Planning
Q 1 - Explain the nature of export firm
•Their products and/or services are successful domestically
•They have a solid domestic business plan with proven effectiveness
•They have specific advantages over the competition
•Their products and/or services are unique in one or more ways
•Their products and/or services are competitively priced
•They are willing to invest resources of time, people and capital without return for a period of
time.
•Entry into new markets may require two or three years of effort before showing a profit
•They are sensitive to and aware of the cultural differences of doing business in other countries
Q 2 - What are the registration formalities for setting up an export firm ?
• Selection of name of the firm
•Approval to name of the firm
•Registration of organization
•Opening of bank account
•Obtaining permanent account number (PAN)
•Registration with sales tax authorities
•Importer-Exporter Code number (IEC number)
•Registration cum membership certificate
•Registration with Export credit guarantee corporation (ECGC)
•Registration under central excise law
•Registration with with other authorities
•Registration for Business Identification number (BIN)
•Export licensing