Statistical Computing
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Overview
Description
Computational statistics is a fundamental part of modern data analysis. This course provides an understanding of the principles and concepts of using modern statistical programing languages for data analysis. Students will learn a programming language, such as R, to handle the manipulation of large data sets, as well as to simulate data, and to import and export data. As an introductory course in statistically oriented programming, no extensive programming background is assumed. Students will gain experience in analyzing both quantitative and qualitative data. They will learn important ideas of programming data structures, functions, iteration, input and output, debugging, logical design, and abstraction. They will learn how to fit basic statistical models and to assess and present the results. Students will also learn how to comment and organize code.
Career
Undergraduate
Credits
Value
3
Max
3
Min
3
Course Count
1
Number Of Credits
3
Number Of Repeats
1
Repeatable
No
Contact Use
Yes
Generate Attendance
No
Left Use
Yes
Present Use
Yes
Reason Use
Yes
Tardy Use
Yes
Template Override
No
Time Use
Yes
Attendance Type
Class Meeting
Auto Create
No
Code
LEC
Instructor Contact Hours
3
Default Section Size
30
Final Exam Type
Yes
Include in Dynamic Date Calc
No
Instruction Mode
In Person
LMS File Type
Blackboard CourseInfo 4
Name
Lecture
OEE Workload Hours
0
Optional Component
No
Preferred Room Features
Academic Scheduling
Workload Hours
3