Home : Book details : Book description

Description of  Master Course In Statistics And Econometrics (101 Level)

Published 12/2023 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 319.41 MB | Duration: 0h 58m 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. Requirements Basic skills and Ideas of Statistics and Econometrics ! Description Overview Section 1: Master Course in Statistics and Econometrics - Lectures Lecture 1 Foundations of Statistics Lecture 2 Statistical Inference Lecture 3 Regression Analysis Lecture 4 Time Series Analysis Lecture 5 Econometric Modeling and Applications Lecture 6 Business and Academic Success: The Power of Statistics and Econometrics