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Student Learning Outcomes for the Data Science Major
Evaluate arguments based on numerical evidence, construct appropriate graphics for a given data type to find patterns, and apply statistical inference methods of a given data structure and statistical hypothesis.
Evaluate arguments based on numerical evidence, construct appropriate graphics for a given data type to find patterns, and apply statistical inference methods of a given data structure and statistical hypothesis.
Know the steps to draw a random sample from a population, understand and interpret the results from sample surveys, observational studies, and experiments, and distinguish what kind of conclusions can be drawn from each study design and their limitations.
Know the steps to draw a random sample from a population, understand and interpret the results from sample surveys, observational studies, and experiments, and distinguish what kind of conclusions can be drawn from each study design and their limitations.
Import data into statistical software packages, design relational data models, and demonstrate a mastery of database terminology and use in SQL.
Import data into statistical software packages, design relational data models, and demonstrate a mastery of database terminology and use in SQL.
Apply probability properties to solve complex/real world word problems, define what a sampling distribution is and what it is used for, describe the results of the Weak Law of Large Numbers, and communicate the conditions needed to apply the Central Limit Theorem when calculating a test statistic.
Apply probability properties to solve complex/real world word problems, define what a sampling distribution is and what it is used for, describe the results of the Weak Law of Large Numbers, and communicate the conditions needed to apply the Central Limit Theorem when calculating a test statistic.
Demonstrate knowledge and growth by writing professional reports and giving presentations using a large real world dataset, craft a narrative using data visualizations to motivate an audience to action, and identify the big ideas and stakeholders for data in order to more effectively produce graphics.
Demonstrate knowledge and growth by writing professional reports and giving presentations using a large real world dataset, craft a narrative using data visualizations to motivate an audience to action, and identify the big ideas and stakeholders for data in order to more effectively produce graphics.
Demonstrate proficiency in programming in R, Python, and SQL, apply knowledge of statistical programming fundamentals in R in order to perform calculations and write functions to implement modern statistical methods/algorithms, perform data manipulations using tidyverse commands, and work collaboratively on group projects (from the planning to execution and presentation).
Demonstrate proficiency in programming in R, Python, and SQL, apply knowledge of statistical programming fundamentals in R in order to perform calculations and write functions to implement modern statistical methods/algorithms, perform data manipulations using tidyverse commands, and work collaboratively on group projects (from the planning to execution and presentation).