The Diagnostic Assessment and Achievement of College Skills (DAACS) is a formative assessment designed to provide you with information about key college skills. DAACS includes assessments in self-regulated learning, mathematics, reading, and writing. YOU ARE ONLY REQUIRED TO COMPLETE THE SELF-REGULATED LEARNING ASSESSMENT. This should take about 10 minutes to complete the assessment and there is no passing or failing. Once you are done, I encourage you to review the resources recommended to you.
You are responsible for presenting one practice homework problem during the semester. Please sign up as-soon-as possible as there are limited slots per week. Try to keep each presentation to five minutes or less. Sign-up on this Google Spreadsheet: https://docs.google.com/spreadsheets/d/14OFGJZFkiI6JM_wn8bl-_BsKlbLybdgR5IDVrsk5HfE/edit?usp=sharing Choose a problem from the following list: Chapter 1 - Introduction to Data Practice: Any odd numbered question. Chapter 2 - Summarizing Data Practice: Any odd numbered question.
The solutions to the practice problems are at the end of the book and do not need to be handed in. Graded assignments should use the provided R markdown templates provided below. Data for the homework assignments, and for within the chapters too, can be downloaded here. Or alternatively all the data is included in the openintro R packge (use the data(package = 'openintro') command to list all the datasets available in that package).
These mini projects will have you explore statistical topics using R. You can use the startLab function in the DATA606 package to get started, or copy the templates from the links below. Please submit a PDF (preferred) or HTML file along with your Rmarkdown file. Be sure to answer all questions in lab, not just the on your own section. Labs should be submitted on Blackboard. Introduction to R and RStudio (Template) Introduction to Data (Template) Probability (Template) Distributions of Random Variables (Template) Foundations for Statistical Inference Sampling Distributions (Template) Confidence Levels (Template) Inference for Categorical Data (Template) Inference for Numerical Data (Template) Introduction to Linear Regression (Template) Multiple Linear Regerssion (Template)
Download project proposal template Download project template The purpose of the data project is for you to conduct a reproducible analysis with a data set of your choosing. There are two components to the project, the proposal, which will be graded on a pass/fail basis, and the final report. The outline for each of these are provided in the templates. When submitting the assignments, include the R Markdown file (change the name to include your last name, for example Bryer-Proposal.
The final exam will be posted on Blackboard during the time indicated on the course schedule.