EC124 Statistical Techniques B Notes | Assignment Help | Syllabus
Country: United Kingdom
University: The University Of Warwick
Students will acquire a comprehensive grasp of probability theory, computing moments of univariate and multivariate distributions (including several frequently used special distributions), hypothesis testing, and confidence intervals in this session. You will learn data analysis skills and methods.
Students will get a comprehensive grasp of the fundamental concepts of statistics in this subject. Probability theory, computing moments of univariate and multivariate distributions (including several frequently used special distributions), hypothesis testing, and confidence intervals will all be covered. You’ll get a better grasp of
how to program inside the statistical package, allowing for the display of statistical data in a graphical format
How to construct hypothesis tests from data in a relevant manner (tables, graphs).
The Most Important Learning Outcomes
Students will learn how to use quantitative techniques to study core and elective first and second year economics courses.
Students will improve their statistical skills and statistical modeling approaches.
Students will develop data awareness and analysis, as well as data management skills.
having learned the statistical skills required to study economics’ core and elective first and second year courses;
expand your understanding of statistical techniques and statistical modeling
Through the use of statistical tools, they have acquired a better understanding of data and how to handle it.
The following subjects are usually covered in the module:
Probability; Discrete random variables; Binomial and Poisson distributions; Bivariate distributions; covariance and correlation; Descriptive statistics; Probability; Discrete random variables; Binomial and Poisson distributions; Bivariate distributions; covariance and correlation; Uniform and normal distributions; continuous random variables; Theorems of limitation; Sampling and distributions of samples; Confidence intervals and hypothesis testing Non-parametric testing is a kind of statistical analysis that does not use a standard
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