Econometrics Tutor in GK1- The tutor will assist in understanding key econometric concepts, statistical methods, and data analysis techniques used in economics. The ideal candidate should have a strong background in economics, statistics, and mathematics, along with experience using econometric software such as Stats, R, Python, or E Views.

IF you want to take a free demo class contact now – 7669520555

econometrics tutor in gk1

Econometrics Tutor In gk1 delhi

Responsibilities

  • Provide one-on-one or group tutoring sessions to students in econometrics.
  • Explain complex statistical and economic concepts in an accessible manner.
  • Assist with assignments, research projects, and exam preparation.
  • Teach statistical techniques such as regression analysis, hypothesis testing, and time series analysis.
  • Guide students in using econometric software for data analysis.
  • Assess students’ progress and adjust tutoring methods accordingly.
  • Develop study materials, practice problems, and real-world examples.
  • Stay updated on advancements in econometrics and statistical software

Introduction to Econometrics Tutor in gk1 delhi

  • Definition and Scope of Econometrics
  • Relationship Between Economic Theory, Mathematics, and Statistics
  • Types of Data: Cross-Sectional, Time Series, and Panel Data
  • Steps in Empirical Economic Research

Statistical Foundations for Econometrics

  • Probability and Random Variables
  • Sampling and Estimation Theory
  • Hypothesis Testing and Confidence Intervals
  • Review of Matrix Algebra (for Advanced Courses)

Econometrics Tutor In gk1

The Classical Linear Regression Model (CLRM)

  • Simple Linear Regression Model
  • Assumptions of the Classical Model
  • Ordinary Least Squares (OLS) Estimation
  • Properties of OLS Estimators (BLUE)
  • Goodness of Fit: R² and Adjusted R²

Multiple Regression Analysis

  • Extension to Multiple Explanatory Variables
  • Interpretation of Coefficients
  • Multicollinearity: Causes, Consequences, and Remedies
  • Functional Form and Model Specification

Violations of Classical Assumptions

  • Heteroskedasticity: Causes, Detection (White Test, Breusch-Pagan Test), and Remedies
  • Autocorrelation: Causes, Detection (Durbin-Watson Test, Breusch-Godfrey Test), and Remedies
  • Endogeneity and Simultaneity Bias
  • Instrumental Variables (IV) Estimation

Dummy Variables and Categorical Data Econometrics Tutor in gk1

  • Use of Dummy Variables in Regression
  • Interaction Effects
  • Testing for Structural Change (Chow Test)

Time Series Econometrics

  • Stationarity and Unit Root Testing (ADF Test, KPSS Test)
  • Autoregressive (AR) and Moving Average (MA) Models
  • ARMA and ARIMA Models
  • Cointegration and Error Correction Models (Engle-Granger, Johansen Test)
  • Vector Autoregressions (VAR) and Granger Causality

Econometrics Tutor In GK1

Panel Data Econometrics

  • Pooled OLS vs. Fixed and Random Effects Models
  • Hausman Test for Model Selection
  • Dynamic Panel Data Models (GMM Estimation)

Advanced Topics (Optional/Graduate Level)

  • Maximum Likelihood Estimation (MLE)
  • Generalized Method of Moments (GMM)
  • Limited Dependent Variable Models (Probit, Logit, Tobit)
  • Bayesian Econometrics
  • Machine Learning Applications in Econometrics

Econometrics Tutor In GK1



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