How Does Credit Transfer Work
Students at Indiana University Bloomington often use our Quantitative Analysis course to complete general education or major requirements affordably while balancing others commitments.

Indiana University Bloomington
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Bloomington, IN
The Quantitative Analysis course at Indiana University Bloomington is designed for students who want to gain practical skills while saving significantly on tuition. With NCCRS accreditation, this online course can transfer up to 3–4 credits directly to Indiana University Bloomington programs, helping students finish their degree faster and at a lower cost.
Indiana University Bloomington accepts courses recommended for college credit by ACE & NCCRS

Our courses are approved by the American Council on Education (ACE) — the same body that approves AP and IB — and are accepted for credit by thousands of universities, including Indiana University Bloomington.

Our courses are approved by the National College Credit Recommendation Service (Previously known as National Ponsi) — the NYSED.GOV body that approves AP and IB — and are accepted for credit by thousands of universities, including Indiana University Bloomington.
This course costs $250 through TransferCredit.org (UPI Study), compared to an estimated $900–$1,200 or more if taken directly at Indiana University Bloomington
FAQ
How many credits will I earn for Quantitative Analysis at Indiana University Bloomington?
You will earn 3 transferable college credits, approved byACE & NCCRS, which can be applied toward your degree at Indiana University Bloomington or over 2,100 U.S. universities.
Is the course self-paced and online?
Yes, it’s 100% online and self-paced. You can start anytime and finish on your own schedule within hours or days and then transfer it back to Indiana University Bloomington for credit.
Will this course from UPI Study transfer to Indiana University Bloomington?
Yes, the Quantitative Analysis course is ACE- and NCCRS‑approved and can be submitted to Indiana University Bloomington for credit toward general education or elective requirements.
How much does the course cost as compared to Indiana University Bloomington?
The course costs $250 total, which is 5X more affordable compared to the higher tuition fees charged on campus at Indiana University Bloomington or any community college near Bloomington, IN.
Course Details For Quantitative Analysis
Learning Outcomes
Indiana University Bloomington in Bloomington, IN
In Quantitative Analysis at Indiana University Bloomington in Bloomington, IN you can learn the same topics, transfer it and save tuition fees by a mile. This course, worth 3 transferable credits and approved by NCCRS, is designed to help students at Indiana University Bloomington gain practical skills and, preparing them for success in degree programs and real-world careers. Upon successful completion of the course, students will be able to: acquire essential knowledge and skills for strategic decision-making and risk analysis in the business field, emphasizing the use of quantitative methods; develop proficiency in key quantitative tools, including decision trees, payback analysis, and simulations, for effective managerial decision-making; gain a comprehensive understanding of the quantitative approach to decision-making, focusing on its advantages, objectives, and application under conditions of certainty, risk, and uncertainty; master business risk management through in-depth analysis and the application of risk management strategies, integrating concepts like probability distributions and Monte Carlo simulation; and prepare for data-driven, strategic decision-making, equipping students to navigate the challenges of today's dynamic business environment.
Major Course Topics
Major topics include strategic decision-making and risk analysis; simulation techniques in quantitative analysis; inventory management models; waiting line models and queueing theory; decision analysis for business; project planning and management; integer linear programming; linear programming; sensitivity analysis in business; linear programming applications; and distribution and network models.

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