Master Course in Statistics and Econometrics (101 level)

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Master Course in Statistics and Econometrics (101 level)​

Statistics, Econometrics, Regression Analysis , Time Series Analysis, Hypothesis Testing, Research Methodology, SPSS

What you'll learn​

• Define and explain key concepts in statistics, such as measures of central tendency, variability, and probability.
• Demonstrate the ability to organize, summarize, and visualize data using appropriate statistical techniques.
• Apply the principles of probability to solve practical problems and make informed predictions.
• Interpret the results of probability distributions and understand their relevance in statistical analysis.
• Formulate hypotheses and conduct hypothesis tests for population parameters.
• Interpret p-values and confidence intervals to make informed decisions about statistical significance.
• Construct confidence intervals for population parameters and understand the precision of estimates.
• Evaluate the impact of sample size and variability on the width of confidence intervals.
• Develop skills in building and interpreting simple and multiple regression models.
• Understand how to identify and interpret the coefficients, including assessing their statistical significance.
• Apply diagnostic techniques to assess the assumptions of regression models.
• Address issues like multicollinearity and heteroscedasticity to enhance the reliability of regression analysis.
• Apply various time series forecasting methods, such as moving averages and exponential smoothing.
• Evaluate the accuracy and reliability of time series forecasts in different contexts.
• Apply regression analysis techniques to estimate parameters and test economic hypotheses.
• Critically assess the implications, limitations, and policy relevance of econometric results in economic applications.

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