Semester.ly

Johns Hopkins University | EN.550.413

Applied Statistics and Data Analysis

4.0

credits

Average Course Rating

(3.72)

An introduction to basic concepts, techniques, and major computer software packages in applied statistics and data analysis. Topics include numerical descriptive statistics, observations and variables, sampling distributions, statistical inference, linear regression, multiple regression, design of experiments, nonparametric methods, and sample surveys. Real-life data sets are used in lectures and computer assignments. Intensive use of statistical packages such as S+ to analyze data.

Fall 2012

(3.76)

Fall 2013

(3.57)

Fall 2014

(3.84)

Fall 2012

Professor: Ting Yang

(3.76)

Students said the course is a good introduction to practical applications of statistics and it provides good experience doing programming with R. The professor included a lot of applied examples, but some students said that the examples were not clear. Some felt that the course was not chal enging enough and that the professor did not have a strong enough grasp of the subject matter. Suggestions for improvement included longer or more detailed lectures, and study guides to help students prepare for exams. Prior experience coding with R would be helpful for this course.

Fall 2013

Professor: Daniel Naiman, Minh Tang

(3.57)

Students liked the very practical and applicable way the materials were taught, and felt that they were able to learn a lot because of it. The lectures, textbook, and homework assignments all provided excellent information and were valuable resources when studying for the exams. Students also found the professor to be very engaging and helpful throughout the course, although they thought his lectures were a bit fast and that the lecture slides did not contain all of the information they needed. Suggestions for improvement included having shorter, more detailed lecture slides and cutting out some of the materials covered over the class so that the remaining concepts could be covered more in depth. Students also wanted a textbook that fol owed the course format more closely. Prospective students should be interested in learning how to use computer programs for statistics, particularly R programming. This course requires a solid background in statistics, and having some prior experience to programming in general is very beneficial.

Fall 2014

Professor: Minh Hai Tang

(3.84)

Students were the most enthusiastic about the relevance of the course material covered in this class. They also enjoyed the opportunity to learn about using the R programming language. Students thought the least favorable aspect of this course was the exam which they argued didn’t match the difficulty of the easier problems in homework assignments. Students believed that the course could be improved by spending more time reviewing example problems as well as more time on practical rather than theoretical aspects of the subject matter. They thought that it was valuable for people thinking about taking this class to know that some previous experience with R would be useful for this course.