Bachelor of Science in Mathematics program with Predictive Modeling Emphasis from Bellevue University

Bachelor of Science in Mathematics program with Predictive Modeling Emphasis from Bellevue University

This emphasis is designed for math majors at Bellevue University wishing to specialize in the field of predictive analytics.
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Overview

If you get excited about numbers, problem solving, and calculating figures in your head, your talent is needed in many STEM career fields. The Bachelor of Science in Mathematics degree program prepares you with the foundation of math skills needed to enter science and industry or education and to meet the growing demand for mathematicians in business. Bellevue University offers credit for Statistics.com courses applied towards this major.

Bellevue University is a private nonprofit that has served working adults since 1966 that offers flexible learning options and support designed to work with you every step of the way.

A non-profit university, Bellevue University is accredited by the Higher Learning Commission, a regional accreditation agency recognized by the U.S. Department of Education.

Who This Degree Serves

The Bachelor of Science in Mathematics program is designed to provide the foundational skills needed to enter the workforce and meet the increasing demand for mathematicians in business, education, engineering, and science fields. The program includes coverage of calculus, applied statistics, programming, discrete mathematics, linear and abstract algebra. The program emphasizes critical thinking, quantitative analysis, and problem-solving skills. Graduates from the program will have a comprehensive understanding of mathematics and be able to apply mathematical principles to conduct and support research for both scientific and business purposes. They will be able to develop mathematical and statistical models to analyze data, interpret data, report conclusions drawn from their analyses, and use data analysis to improve business decisions and solve real-world problems. Graduates will be well positioned for a variety of entry to mid-level careers in mathematics, including Predictive Modelling.

Learning Outcomes

At the completion of the Bellevue University Bachelor’s in Mathematics degree, you will:

  • Apply mathematical practices to mathematical and real-world problems.
  • Develop mathematical and statistical models to analyze data, interpret data and report conclusions drawn from their analyses.
  • Use numerical and data analysis to make informed decisions

Bellevue University offers credit for the following courses completed through Statistics.com.

Prerequisites

Required Courses

The director of this program at Bellevue University is Kimberly Brehm. Her contact information can be found here: https://www.bellevue.edu/about/leadership/faculty/brehm-kimberly

R Programming – Introduction Part 1

This course provides an easy introduction to programming in R.
Topic: Data Science, Using R | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: May 15, 2020, Sep 11, 2020

R Programming – Introduction Part 2

This course is a continuation of the introduction to R programming.
Topic: Data Science, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 10, 2020, Nov 13, 2020, Mar 12, 2021

Elective Courses

Choose one of the following:

Forecasting Analytics

This course will teach you how to choose an appropriate time series model: fit the model, conduct diagnostics, and use the model for forecasting.
Topic: Analytics, Prediction/Forecasting | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 10, 2020, Nov 13, 2020, Mar 12, 2021, Jul 9, 2021, Nov 12, 2021

Predictive Analytics 1 – Machine Learning Tools

This online course introduces the basic paradigm of predictive modeling: classification and prediction.
Topic: Analytics, Prediction/Forecasting | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: May 15, 2020, Sep 11, 2020, Jan 15, 2021

Predictive Analytics 1 – Machine Learning Tools with R

This course introduces to the basic predictive modeling paradigm: classification and prediction.
Topic: Data Science, Analytics, Machine Learning, Prediction/Forecasting, Using R | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: May 15, 2020, Sep 11, 2020

What Our Students Say​

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The TA was really helpful and very responsive to questions. Overall the course was a great experience.

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Marilyn Wheatley
Minitab
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Considering all of the material that needed to be covered, I thought the course was well written and thought provoking.

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Paul Anderson
Professor and Chair of Mathematics and Computer Science at Albion College

Tuition and Fees

Register for each course via Statistics.com, create an account with ACE and a transcript will be sent to Bellevue University.

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Frequently Asked Questions

Who is the American Council on Education (ACE)?

The American Council on Education’s College Credit Recommendation Service (ACE CREDIT) has evaluated and recommended college credit for several courses offered by The Institute for Statistics Education at Statistics.com.

ACE CREDIT’s College and University Network includes 2,200 higher education institutions that consider ACE credit recommendations for transfer to degree programs. The decision to accept specific credit recommendations is up to each institution.

Please see our knowledge center for more information.

How many courses are ACE college credit eligible?

The Institute for Statistics Education offers 34 courses that are eligible for college credit through the American Council on Education (ACE).

Please see our knowledge center for more information.

Are courses eligible for college credit?

Many of the courses at The Institute for Statistics Education have been recommended for academic credit by The American Council on Education (ACE). ACE-accredited courses can be transferred to another educational institution that accepts ACE credit.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Latest Blogs

Explain or Predict?
A casual user of machine learning methods like CART or naive Bayes is accustomed to evaluating a model by measuring how well it predicts new data.  When examining the output of statistical models, they are often flummoxed by the profusion of assessment metrics. Typical multiple linear regression output...
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Course Spotlight: Predictive Analytics
Predicting whether an internet user will click on a link or buy a product, whether an insurance claim is fraudulent, whether a home mortgage will be paid on time (or early), how much a house will sell for, what internet ad you should see next, whether a discharged...
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Predictive Modeling and Typhoon Relief
The devastation wrought by Super-Typhoon Haiyan in the Philippines is the biggest test yet for the nascent technology of "artificial intelligence disaster response," a phrase used by Patrick Meier, a pioneer in the field. When disaster strikes, a flood of social media posts and tweets ensues. There is useful...
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