skilldevelopment.cpe@lpu.co.in

What you'll learn

The course "Statistical and Software-Based Data Analysis for Research Applications" is designed to equip researchers, students, and professionals with the essential skills to analyze and interpret data effectively. It offers a blend of statistical concepts and hands-on training with industry-standard software tools such as Excel, Design Expert, SPSS and OriginPro. The curriculum emphasizes the application of descriptive and inferential statistics, experimental design, data visualization, and optimization techniques in real-world research scenarios. Participants will gain proficiency in managing datasets, conducting hypothesis testing, regression analysis, and creating publication-ready visuals. By integrating statistical knowledge with software-based solutions, the course aims to enhance participants' ability to derive meaningful insights and make data-driven decisions. Ideal for those in science, engineering, and social sciences, this six-week program provides a comprehensive learning experience to bridge the gap between theoretical knowledge and practical application in data analysis. Learning Outcome of Course: By the end of this course, participants will be able to: 1. Demonstrate the ability to apply appropriate statistical techniques to solve research problems. 2. Show improved ability to handle complex datasets, leading to more robust and credible research outcomes. 3. Effectively use various software and interpret statistical data and present findings in a clear and concise manner, suitable for academic and professional research dissemination.

  • • 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 and OriginPro • 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
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Dr. Imdadul Hoque Mondal
Assistant Professor

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 13 publications in both national and international journals, he is an active participant in the food processing and optimization areas. He has already conducted two 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 7 master’s students and currently supervising two Ph.D. and six 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.