What This Document Is
This is a midterm examination for Statistics 133, a course focused on Concepts in Computing With Data, offered at the University of California, Berkeley. It’s designed to assess a student’s understanding of core statistical computing principles and their ability to apply them using the R programming language. The exam tests practical skills in data manipulation, analysis, and visualization within the R environment.
Why This Document Matters
This resource is invaluable for students currently enrolled in or preparing for a similar computing with data course. It’s particularly helpful for those seeking to solidify their understanding of how to translate statistical concepts into executable R code. Reviewing a sample exam – even without the solutions – allows students to gauge the expected difficulty and scope of the assessment, identify areas where further study is needed, and practice their exam-taking strategies. It’s best utilized as part of a comprehensive study plan, alongside coursework and independent practice.
Topics Covered
* Data manipulation and cleaning techniques in R
* Working with vectors and data frames
* Statistical summaries and calculations
* Data visualization using R graphics
* Function creation and application
* Conditional logic and data subsetting
* Handling missing data
* Data import considerations
What This Document Provides
* A set of statistical computing problems mirroring the style and complexity of a university-level midterm exam.
* Questions requiring the formulation of R programs to solve specific data analysis tasks.
* Scenarios involving real-world datasets, prompting application of learned concepts.
* Problems designed to test understanding of fundamental R commands and programming structures.
* A glimpse into the types of analytical thinking and coding proficiency expected in the course.
