DTSA 5704 Managing, Describing, and Analyzing Data
Same as DTSA 5900-1
- Specialization: Data Science Methods for Quality Improvement
- Instructor: Wendy Martin, Instructor, W. Edwards Deming Professor of Management
- Prior knowledge needed: R programming, Statistics, Math, Algebra II
Learning Outcomes
- Calculate descriptive statistics and create graphical representations using R software
- Solve problems and make decisions using probability distributions
- Explore the basics of sampling and sampling distributions with respect to statistical inference
- Classify types of data with scales of measurement
Course Content
Upon completion of this module, students will be able to use R and R Studio to work with data and classify types of data using measurement scales.
Upon completion of this module, students will be able to use R and RStudio to create visual representations of data, and calculate descriptive statistics to describe location, spread and shape of data.
Upon completion of this module, students will be able to apply the rules and conditions of probability and probability distributions to make decisions and solve problems using R and R Studio.
Upon completion of this module, students will be able to use R and RStudio to characterize sampling and sampling distributions, error and estimation with respect to statistical inference.
Upon completion of this module, students will be able to use R and RStudio to perform statistical tests for two groups with independent and dependent data.
You will complete a multiple choice exam worth 20% of your grade. You must attempt the final in order to earn a grade in the course. If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.
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