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Applied Research Methodology Using Python

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What I will learn?

  • এই কোর্সটি সম্পন্ন করার মাধ্যমে আপনি Python ব্যবহার করে Research Data Preparation, Analysis এবং Results Interpretation-এর practical skills অর্জন করবেন।
  • Research Data Cleaning, Preparation এবং Descriptive Statistics করতে।
  • Correlation Analysis, Correlation Matrix এবং বিভিন্ন Data Visualization তৈরি ও বিশ্লেষণ করতে।
  • Cross-sectional Data-এর ওপর Simple ও Multiple OLS Regression Analysis পরিচালনা এবং ফলাফল ব্যাখ্যা করতে।
  • Time Series Data-এর Trend, Autocorrelation ও Stationarity বিশ্লেষণ এবং Time Series Regression করতে।
  • Panel Data Preparation, Pooled OLS, Fixed Effects ও Random Effects Models নিয়ে কাজ করতে।
  • Regression Model-এর বিভিন্ন সমস্যা শনাক্ত করতে এবং উপযুক্ত Diagnostic Tests ও Corrective Methods প্রয়োগ করতে।
  • Regression Coefficients, Model Results এবং Research Findings সঠিকভাবে Interpret করতে।
  • Robustness Checks এবং Research Reporting-এর মাধ্যমে একটি Reproducible Research Analysis তৈরি করতে।

Course Curriculum

Session 01: Orientation

Session 02: Applied Research Methodology Using Python
Data cleaning, descriptive statistics, correlation matrices, histograms, box plots and scatterplots.

Session 03: Cross-sectional regression
Simple and multiple OLS; coefficient interpretation; multicollinearity, heteroskedasticity, specification and influence checks.

Session 04: Time-series exploration
Dates and frequency, trend plots, autocorrelation, stationarity tests, logarithms, growth rates and differencing.

Session 05: Time-series regression
Lagged regression, model selection, residual diagnostics, HAC standard errors and interpretation of short-run relationships. Lagged regression, model selection, residual diagnostics, HAC standard errors and interpretation of short-run relationships.

Session 06: Panel data preparation
Entity and time identifiers, balanced and unbalanced panels, within and between variation, panel plots and pooled OLS.

Session 07: Panel model selection
Fixed effects, random effects and time effects; pooled-model comparisons, Hausman and Mundlak tests; model interpretation.

Session 08: Panel diagnostics
Heteroskedasticity, serial correlation and cross-sectional dependence; clustered standard errors and suitable corrective steps.

Session 09: Panel research application
Robustness checks, interactions, coefficient plots, interpretation, research reporting and a reproducible panel-data project.

Session 10: Assessment

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৳ 3,850.00 ৳ 7,000.00
  • Level
    Intermediate
  • Certificate
    Certificate of completion

A course by

Financial Consultant, Envirocare International Limited BBA & MBA in Finance (University of Dhaka) · MEcon in Environmental Economics (Dhaka School of Economics, University of Dhaka) · Master’s in Mathematics (AUST) Professional Training: Python & Applied Machine Learning (BUET) · Data Science & Machine Learning (NACTAR) Continues in Part II — Applied Research Paper Writing | Part III — Guided Manuscript Development and Publication Suppo

Material Includes

  • Research Data Preparation ও Analysis-এর জন্য Practical Exercises
  • Python Code Examples ও Hands-on Practice
  • Descriptive Statistics ও Data Visualization Practice
  • Regression Analysis ও Model Diagnostics Practice
  • Reproducible Research Project-এর Practical Application

Requirements

  • Statistics-এর Basic Knowledge থাকতে হবে।
  • Spreadsheet (যেমন Excel) ব্যবহারের প্রাথমিক দক্ষতা থাকতে হবে।
  • Python Programming-এর পূর্ব অভিজ্ঞতা বাধ্যতামূলক নয়।
  • Practical Data Analysis-এর জন্য একটি Laptop বা Desktop প্রয়োজন।
  • Jupyter Notebook অথবা Google Colab ব্যবহারের সুযোগ থাকতে হবে।

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