1610 
3 Credits

Fundamentals of Statistics

An introduction to statistical reasoning
Ying Deng 邓莹
Course Introduction
Ying Deng 邓莹
Ying Deng 邓莹PhD, Syracuse University

Ying Deng is an associate professor in the School of International Trade and Economics (SITE) at University of International Business and Economics (UIBE). She has been working at UIBE since graduated with a PhD in Economics from Maxwell School at Syracuse University in 2013. Her primary research focuses on Spatial Econometrics and Applied Econometrics. She has taught courses for students at different levels, including Introduction to Econometrics for undergraduates, Financial Econometrics, Econometric Methods and Applications Using Stata for masters and Spatial Econometrics for PhDs.

Interests
  • Playing Badminton
  • Skiing
  • Traveling
  • Home Organizing

Fundamentals of Statistics

UIBE serves as our School of Record
3 Credits
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Course Description

An introduction to statistical reasoning. Students learn how statistics has helped to solve major problems in economics, education, genetics, medicine, physics, political science, and psychology. Topics include: design of experiments, descriptive statistics, mean and standard deviation, the normal distribution, the binomial distribution, correlation and regression, sampling, estimation, and testing of hypothesis.

Courses Outcomes

Statistics can be defined as the science of reasoning from data. Data and statistical thinking abound in everyday life and in almost all academic disciplines, so the ability to reason with data is essential to educated citizenship. This course will focus on understanding statistical concepts and reasoning; organizing, interpreting and producing data; analyzing statistical arguments and communicating findings clearly; and appreciating the relevance of statistics to contemporary society. After successful completion of this course, students will be able to:

  • Construct and interpret graphical and numerical summaries of data;
  • Describe many of the fundamental ideas of statistics, such as variability, distribution,association, sampling;
  • Describe how the nature of data collection methods affects the scope of the conclusionsthat can be drawn from statistical studies (especially cause and effect) the role ofprobability in sampling and experiments;
  • Apply the normal distribution and the Central Limit Theorem;
  • Comprehend the basics of statistical inference: estimation, assessing statisticalsignificance, statistical reasoning, and apply and interpret the results of a variety of statistical techniques;
  • Analyze and assess statistical arguments, such as those found in the popular press and scholarly publications;
  • Communicate knowledge of statistical ideas effectively.