Business Data Analysis and Interpretation

Spring 2022 BUS 320 Syllabus

Subject to revision (last updated Dec 31, 2021)

Contact information

Course description

This is an applied course that builds upon knowledge acquired from lower-division statistics coursework. It exposes students to the research and data analysis practices executed in the business world. A focus of this course is on generating reproducible analyses using the R programming language.

Prerequisites

Learning objectives

Course materials

Schedule

Date Topic
Feb 1 1: Introduction/R/RStudio due at 5 PM
Feb 8 2: Install R/RStudio and create a blog due at 5 PM
Feb 15 3: Data manipulation / descriptive analysis I due at 5 PM
Feb 22 4: Reading and writing data due at 5 PM
Mar 1 5: Data manipulation / descriptive analysis II due at 5 PM
Mar 8 6: Data manipulation / joining data due at 5 PM
Mar 15 7: Exploratory analysis / data visualization I due at 5 PM
Mar 29 8: Exploratory analysis / data visualization II due at 5 PM
Apr 5 9: Data visualization / storytelling due at 5 PM
Apr 12 10: Machine learning due at 5 PM
Apr 19 11: Inference / sampling due at 5 PM
Apr 26 12: Inference / bootstrapping due at 5 PM
May 3 13: Inference / hypothesis testing due at 5 PM
May 10 14: Assignment due at 5 PM
May 17 15: Assignment due at 5 PM

Grading

There are 1050 possible points in the course (50 are extra credit points). Your grade will be determined by your total points:

Grade Points
A 950
A- 900
B+ 870
B 830
B- 800
C+ 770
C 730
C- 700
D+ 670
D 600

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