Research For Everyone
Organized By
National University Research Hub & Scholarship Abroad 

Course Syllabus-2025

Lecture No. Topics
Lecture 01 ● Introduction to Research
o Definition, scope, and significance of business research
o Types of business research (exploratory, descriptive, causal)
o Business research vs. academic research
o The Research Process: Steps in Conducting Research.
Lecture 02 ● Writing a Research Proposal
● Ethics in research
Lecture 03 ● Research Problem Identification
o Defining the Research Problem.
o Literature Review: Importance and Process.
o How to formulate research questions
o Setting Research Objectives.
Lecture 04 ● How to conduct literature review
Lecture 05 ● Referencing Discussion (Citation, Bibliography, Referencing style)
o Referencing Software ‘Zotero’
Lecture 06 ● Hypothesis development
Lecture 07 ● Research Design
● Types of Research
o Explanatory, and Evaluative Research
o Qualitative, Quantitative, and Mixed Methods,
o Cross-Sectional and Longitudinal Research,
o Deductive, Inductive, and Abductive Research
Lecture 08 ● Measurement Concepts
o Measurement and Scaling Concepts
o Questionnaire Design
Lecture 09 ● Sampling
o Sampling Designs and Sampling Procedures
o Determination of Sample Size: A Review of Statistical Theory
Lecture 10 ● Data Collection
o Qualitative (FGD, IDI, observation)
o Quantitative (Survey & secondary data)
Lecture 11 ● Data Analysis
o Introduction to Data Analysis.
o Coding, categorizing, and managing data
o Handling missing data and outliers
o Quantitative Data Analysis: Descriptive and Inferential Statistics.
o Qualitative Data Analysis: Thematic Analysis, Content Analysis.
o Using Statistical Software: SPSS, Excel
Lecture 12 ● Introduction to SPSS
o Overview of SPSS: Purpose and Application.
o Installing SPSS and Navigating the Interface.
o Understanding the SPSS Windows (Data View, Variable View).
o Basic File Operations (Opening, Saving, Importing Data).
Lecture 13 ● Data Entry and Management
o Defining Variables: Variable Types and Properties.
o Data Entry in SPSS: Manual Entry and Importing Data.
o Data Cleaning: Identifying Missing Data and Outliers.
o Recoding Variables and Creating New Variables.
o Sorting and Filtering Data.
Lecture 14 ● Descriptive Statistics and Data Summarization using SPSS
o Introduction to Descriptive Statistics.
o Calculating Measures of Central Tendency (Mean, Median, Mode).
o Calculating Measures of Dispersion (Variance, Standard Deviation, Range).
o Frequency Tables, Cross-tabulation, and Descriptive Output.
Lecture 15 ● Data Visualization in SPSS
o Creating Charts and Graphs (Bar Charts, Pie Charts, Histograms).
o Generating Scatterplots and Boxplots.
o Customizing Graphs (Labels, Titles, Colours).
o Exporting Charts for Reports.
Lecture 16 ● Inferential Statistics: Hypothesis Testing
o Performing t-tests (One-sample, Independent Samples, Paired Samples).
o Conducting Chi-Square Tests for Independence.
o Analyzing Results and P-Values.
o Conducting Correlation Analysis (Pearson’s, Spearman’s).
o Introduction to Linear Regression.
o Interpreting Regression Output (Coefficients, R-Square, P-values).
Lecture 17 ● Research Report Writing and Presentation
o Structure of a Research Report.
o Writing an Executive Summary.
o Presenting Research Findings: Graphs, Charts, and Tables.
o Writing Recommendations Based on Research.
Lecture 18 ● How to publish in a High Impart Factor Journal

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