Tuck | Mr. Social To Tech
GMAT 700, GPA 2.7
NYU Stern | Ms. Legal Officer
GMAT 700, GPA 4
Wharton | Mr. Mobility Entrepreneur
GMAT 760, GPA 1st Division
HEC Paris | Mr. Business Man
GMAT 720, GPA 3.89
Harvard | Mr. Football Author
GMAT 760, GPA 3.4
Harvard | Mr. Deferred Admission
GRE 329, GPA 3.99
Harvard | Mr. Tech Start-Up
GMAT 720, GPA 3.52
Chicago Booth | Mr. Plantain & Salami
GMAT 580, GPA 4.0
Stanford GSB | Ms. Education Non-profit
GRE 330, GPA 3.0
Tuck | Mr. Running To The Future
GMAT 720, GPA 3.5
Kellogg | Mr. Digital Finance
GRE 327, GPA 3.47
Stanford GSB | Mr. Filling In The Gaps
GRE 330, GPA 3.21
Tuck | Mr. Tech PM
GMAT 710, GPA 3.3
Wharton | Mr. Data Dude
GMAT 750, GPA 4.0
Harvard | Ms. Tech Impact
GMAT 730, GPA 3.8
Columbia | Mr. MD/MBA
GMAT 670, GPA 3.77
Chicago Booth | Mr. Community Uplift
GMAT 780, GPA 2.6
Rice Jones | Mr. Simple Manufacturer
GRE 320, GPA 3.95
London Business School | Ms. Social Impact Consulting
GRE 330, GPA 3.28
Ross | Ms. Business Development
GMAT Targetting 740, GPA 4.0
UCLA Anderson | Ms. Triathlete
GMAT 720, GPA 2.8
Columbia | Mr. Oil & Gas
GMAT 710, GPA 3.37
Chicago Booth | Ms. IB Hopeful
GMAT 710, GPA 2.77
Kellogg | Mr. Digital Finance Strategy
GRE 327, GPA 3.47
Wharton | Mr. Market Analyst
GMAT 770, GPA 7.2/10
Harvard | Mr. Banking & Finance
GMAT 700, GPA 3.8
Berkeley Haas | Mr. Hanging By A Thread
GMAT 710, GPA 3.8

November’s Essential Business MOOCs

Foundations of Data Analysis

 

School: University of Texas-Austin

Platform: EdX

Registration Link: Foundations of Data Analysis

Start Date: November 4, 2014 (13 Weeks)

Workload: 3-6 Hours Per Week

Instructor: Michael J. Mahometa, Ph.D

Credentials: Mahometa is a statistical consultant and manager of consulting services at the University of Texas, where he manages a team responsible for supporting faculty and graduate students with statistical analysis. He is also a lecturer in the school’s Department of Statistics and Data Sciences. He holds a Ph.D. in experiential psychology.

Graded: EdX makes numerous certifications available. Although students can simply audit the course, they can also earn honor code certificates (confirms you completed the course without verifying your name), verified certificates of achievement (includes your name and picture), and XSeries certificates (available when you complete a series of courses on a particular topic). The latter two certificates require a small fee.

Description: This hands-on course is equivalent to an undergraduate statistics course, with the added benefit of a modeling section. Each week begins with a question, with data and an analytical framework provided to help students to help them interpret and summarize their findings. The course is divided into three sections: descriptive and visualization statistics (distributions, contingencies, variables, regression); modeling data (exponential and logistic); and inferential statistical tests (t-tests, chi-square, ANOVA). Aside from a unifying question, each weekly session includes instructional and tutorial videos followed by lab exercises.

Review: No reviews.

Additional Note: Students will need to install R and RStudio software on their PC.