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Statistics: QR:Stat Computing&Data Anlysis

STAT 201 OL1 (CRN: 61731)

3 Credit Hours

Fundamental data processing, code development, graphing and analysis using statistical software packages, including SAS and R. Analysis of data and interpretation of results. Prerequisite: STAT 111 with Instructor permission, or STAT 141 or STAT 211.

Notes

Dates: May 22 - July 14, 2017; Prereqs: STAT 111 with instructor permission OR STAT 141; OR STAT 211

Section Description

The goal of STAT201 is to teach students how to conduct data analyses using the statistical programs R and SAS. We discuss practical issues of using real data with an emphasis on data management, data manipulation, basic statistical procedures, data visualization, and interpretation of findings. This is a “STAT” class and we will review some basic statistical methods learned, however, the class is more about using statistical programs and not a course in statistical theory. It is therefore important for students to have a foundational statistical knowledge before taking STAT201– something at the level of UVM's Stat141 is appropriate.

Section Expectation

The below content areas will be covered for both R and SAS. Getting started - Program basics and working environment Getting data in and out of the program - Entering data directly into the program - Using program datasets - Reading in external data files - Generating data using simulation - Saving and exporting data files Data management & manipulation - Understanding data types - Data cleaning: missing values, typos - Renaming variables and using variable labels - Changing variable types and using value labels - Working with special data types: date and time - Formatting variables - Creating new variables - Using conditional logic: if-then-else - Grouping observations - Sort, subset, merge and append data - Explore tools to simplify programs: loops, functions (macros) Descriptive statistics - Calculate measures of center, spread, position, and association - Calculate frequencies and relative frequencies - Create basic graphs: histogram, scatterplot, box and whisker, pie, bar, and segmented bar Inferential statistics - Calculate confidence intervals - Conduct hypothesis tests (t-test, chi-square, anova, regression, and basic non-parametric approaches) - Evaluate test assumptions Data visualization & Reporting - Enhance graphs for improved communication - Create clean, effective reports for communicating results of analyses - Support accurate interpretation of findings Reproducible research - Write and annotate scripts for consistency, transparency, and reproducibility

Evaluation

This course has 24 learning modules, across 3 units. Unit 1 focuses on R: 8 modules, 2 HW, 1 Test Unit 2 focuses on R: 8 modules, 2 HW, 1 Test Unit 3 focuses on SAS: 8 modules, 2 HW, 1 Test Course grades are assigned with the below criteria: 1) Participation/timely completion of modules: 10% 2) Homework: 30% 3) Tests: 60%

Meetings

May 22, 2017 to July 14, 2017

Location

Online Course (View Campus Map)

Important Dates

Note: These dates may change before registration begins.

Last Day to Add May 24, 2017 May 29, 2017 May 31, 2017 June 5, 2017 June 27, 2017

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