• Demonstrate the ability to apply appropriate statistical techniques to solve research problems. • Show improved ability to handle complex datasets, leading to more robust and credible research outcomes. • Effectively use various software and interpret statistical data and present findings in a clear and concise manner, suitable for academic and professional research dissemination.
Course Details
Explore the comprehensive course modules
• Importance of statistics in research • Types of data: Nominal, ordinal, interval, ratio • Introduction to key statistical concepts: Population, sample, variable • Measures of central tendency: Mean, median, mode • Measures of dispersion: Range, variance, standard deviation • Hands-on with real-world datasets (manual calculations and Excel basics) • Probability theory: Basic concepts, probability distributions (normal, binomial, Poisson) • Hands-on: Using Excel for probability calculations • Introduction to hypothesis testing: Null and alternative hypotheses, Type I and Type II errors • Basics of p-value and significance levels • Parametric tests: Z and T-tests (one-sample, independent, paired) • Hands-on: Conducting Z and T-tests in Excel using Data Analysis ToolPak
• Sampling methods and sample size calculation • Hands-on: Random sampling and systematic sampling using Excel • ANOVA (Analysis of Variance): One-way and two-way ANOVA concepts • Hands-on: Performing ANOVA in Excel • Correlation and regression: Understanding relationships between variables • Hands-on: Scatter plots, calculating Pearson/Spearman correlation in Excel • Multiple linear regression: Basics, interpretation of coefficients • Hands-on: Using Excel for regression analysis • Data cleaning and preprocessing in Excel: Handling missing data, identifying outliers Practical exercises
• Introduction to experimental design: Importance in research, factors, levels, and replicates • Overview of Design Expert software: Interface and key features • Full factorial design: Setting up experiments, analyzing results • Hands-on: Practicing full factorial design in Design Expert • Response Surface Methodology (RSM): Central Composite Design (CCD) and Box-Behnken Design • Hands-on: Building and interpreting RSM models • Optimization techniques in Design Expert: Multi-response optimization, desirability functions • Case studies: Application of experimental design in real-world research scenarios
• Introduction to OriginPro and SPSS: Interface, features, and importing data • Creating basic plots: Line graphs, scatter plots, histograms • Advanced visualization: Multi-panel graphs, 3D plots, and heat maps • Hands-on: Customizing and formatting publication-ready graphs • Descriptive statistics and curve fitting in OriginPro • Hands-on: Polynomial and nonlinear regression analysis • Statistical testing in OriginPro and SPSS: ANOVA, T-tests, and hypothesis testing • Hands-on: Applying statistical tools on research datasets • Combining statistical results and visualizations for research publications
• Comparative analysis: Features and applications of Excel, Design Expert, SPSS, OriginPro and python • Selecting the right software for different stages of research • Multi-software workflows: Exporting and importing data between tools • Hands-on: Analyzing the same dataset using all three tools • Experimental design in Design Expert and data visualization in OriginPro • Hands-on: Creating a full workflow for a research problem
• Introduction to the final project: Problem definition, objectives, and methodology • Statistical analysis using Excel: Applying descriptive and inferential techniques • Hands-on: Working on real-world datasets • Experimental design using Design Expert: Optimizing responses and analyzing outcomes • Hands-on: Completing experimental tasks • Data visualization and advanced graphing in OriginPro • Hands-on: Preparing research-ready visuals
Learn from leading experts in stem cell research
Dr. Imdadul Hoque Mondal is currently working as an Assistant Professor in the Department of Food Technology and Nutrition, Lovely Professional University Phagwara. He is an accomplished researcher specializing in food processing, engineering, and technology. He has done his PhD from IIT Guwahati. His PhD work focused on leafy and non-leafy vegetable based soup formulation using a matured non-linear programming based mathematical optimization techniques. Having published 25 publications in both national and international journals, he is an active participant in the food processing and optimization areas. He has already conducted 3 sessions on skill development course on statistical and software-based data analysis for research application. Dr. Mondal has presented number of research papers at various conferences, demonstrating his commitment to global knowledge exchange. He has supervised 25 master’s students and 1 PhD student and currently supervising 2 Ph.D. and 2 master's students. He is an important mentor to the future generation. His fields of study include post-harvest technologies, food processing, product development, and process optimization, demonstrating an interdisciplinary approach to the advancement of food science and technology.
Report of NIRF Data Capturing System: Management Report of NIRF Data Capturing System: Pharmacy Report of NIRF Data Capturing System: Engineering Report of NIRF Data Capturing System: Overall Report of NIRF Data Capturing System: Law Report of NIRF Data Capturing System: Architecture Report of NIRF Data Capturing System: Innovation Report of NIRF Data Capturing System: Agriculture Report of SDG Institution Report of NIRF Data Capturing System: Management Report of NIRF Data Capturing System: Pharmacy Report of NIRF Data Capturing System: Engineering Report of NIRF Data Capturing System: Overall Report of NIRF Data Capturing System: Law Report of NIRF Data Capturing System: Architecture Report of NIRF Data Capturing System: Agriculture
