Cheapest Online Masters in Mathematics and Statistics

The Master of Arts in Mathematics (M.A.) degree is for students who take most of their courses online. The time taken to complete this degree depends on the number of courses taken in any particular semester. Every summer a large selection of 5000 level courses is available.

The primary purpose of the program is to prepare students to teach mathematics at the secondary school and junior/community college levels. The program also provides advanced degree credentials for teachers who wish to take on supervisory positions in mathematics or in mathematics administration.

To obtain this degree, a student needs to pass 11 courses with a GPA of 3.0 or better. One of these courses is the tutorial course Math 6315. At least seven of the other courses are online mathematics courses at the 5000 level. The other three courses may be online mathematics courses at the 5000 level or other elective courses such as those in the mathematics education graduate program.

All of the courses in the program are offered online, and the entire program can be completed in that format. It is also be possible to take approved on-campus courses as alternatives to online courses. There is a regular schedule of online classes each semester, including the summer sessions. As a result, there is little difficulty in combining a full-time teaching position with the program’s course work.

The program requires 33 semester hours of course work.

Master of Science (MS) degree in Statistics offers a state-of-the art curriculum with the aim of serving the growing demand for professionals with knowledge and training in data science and quantitative analysis.

A classified graduate student must maintain a 3.0 grade point average in all coursework to remain in good standing. A total of 30 units are required for the degree.

Program features include:

(1) Convenient class times for both full-time and part-time students. Classes are offered in late afternoon and evenings.

(2) Your choice to attend classes in person, or remotely via live stream. The program is unique nationally in that it is the first master’s degree in statistics that broadcasts all its courses live via online two-way stream. Students can choose to attend courses remotely, via a two-way live stream, or in person at the CSUF campus.

(3) Fully online program to accommodate non-local students. All students can complete the program by attending courses online, submitting and presenting projects and homework online, and taking exams online.

(4) Prepare to join a Ph.D. program or the workforce. The courses are designed to serve students interested in continuing their graduate education by attaining their Ph.D., as well as those who plan to immediately join the workforce upon graduation.

(5) Teaching Associate opportunities for qualified students. The university offer interested masters students, depending on availability, part-time instructor positions where they teach one or more of our elementary mathematics courses. Applications for the Teaching Associate (TA) position will be accepted beginning in March of each year to teach the following fall semester.

(6) Non-resident fee waivers. A limited number of non-resident fee waivers are available on a competitive basis for highly qualified non-resident students.

An online Master’s Degree in Applied Statistics from Michigan Technological University will prepare students for high-demand, high-paying positions in statistics and data science. The accelerated, 100% online program will teach students to analyze and interpret data in a variety of professional settings and industries.

The coursework delivers insight into a broad spectrum of statistical science and methods that can be used to make predictions, devise experiments, and draw accurate conclusions. As a student, you’ll work with industry-standard statistical and data analysis software and conduct a thorough analysis of real datasets to solve real-world problems.

30 credit hours; 10 courses; Accelerated format – 7-week courses; Three start dates per year; 100 percent online; ideal for busy professionals.

Columbia University offers an online Master's Degree in Applied Mathematics. The program provides high-performance computation, and applied mathematics has transcended its typical analytical style to acquire even greater importance and vitality in the field of simulation. The core courses give students a solid foundation in the principles of Applied Mathematics. The core courses count for 15 graduate credit hours toward the degree. Students must complete at least five of the thirteen classes.

Master Degrees STEM Education Mathematics and Statistics.

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The Master of Education (M.Ed.) in STEM Education degree program has three areas of concentration: Mathematics and Statistics Education, Science Education and Engineering and Technology Education. Each of these concentrations has one shared core course, and the curriculum for each concentration totals 30 credit hours. The M.Ed. in STEM Education Mathematics and Statistics is designed to support advancement in education careers for teachers specializing in math and or statistics.

It has a curriculum that supports mathematics teachers applying for National Board Certification.

Graduate Student Services Coordinator, STEM Education.

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An introduction to statistical analysis for students with a background in calculus. Included in the topics covered are probability distributions, expectation, statistical inference, regression and correlation.

As members of a society increasingly devoted to the use and misuse of numbers, students must learn to correctly interpret statistical presentations in all areas and especially in their major fields. This course is designed to give the students a working knowledge of statistics with an emphasis on application rather than theory.

After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in the Course .

The discussion introduces some of the ethical challenges that are specific to the practice of statistics and encourages students to approach these situations from a Christian perspective (FSLOs: TSQR 4).

The student will complete a work assignment each module week in the WebAssign that is associated with the course textbook. 5 sections from the textbook, but this will vary depending on the length and difficulty of each section included in the assignment. Students will be required to earn a 70% on each assignment before moving on to the next work assignment or test (CLOs: CLO 1, 2, 3, 4, 5 FSLOs: TSQR 1, 2).

This project uses confidence intervals to analyze letter frequencies and applies this to decrypting a fairly simple type of coded message. It an application of inferential statistics within the area of cyber-security, broadly-defined. (CLOs: CLO 1, 3 FSLOs: TSQR 1, 2).

Tests are not cumulative. Each test will be open-book open-notes, contain 12-14 multiple-choice and short answer questions, and have a 3-hour time limit. These tests will be completed in the WebAssign that is associated with the course textbook (CLOs: CLO 1, 2, 3, 4, 5 FSLOs: TSQR 1, 2).

Additional program fees may apply. See program page for details.

Provide additional aid amount you may receiveiAdd all aid (scholarships, grants, etc.) you plan to receive throughout your degree for an estimated total cost.Estimate Your Cost.

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You have to have a lot of self-motivation and self-discipline when you are going to school online, but the amazing thing is at Liberty you do not need to do it by yourself. You really do have resources like someone who is going to school on campus.

Donaghey College of Science, Technology, Engineering, and Mathematics.

The Mathematics Assistance Center (MAC) is here to equip students with the skills needed to succeed in math and statistics as well as dispel myths and negative attitudes associated with math.

Reduce anxiety, particularly anxiety associated with math learning.

Switch negative believes to positive attitudes mathematics.

Increase work grades, test scores, and overall grade.

Mathematics: Comparing Data-Driven Careers.

Statistics vs. Mathematics: Comparing Data-Driven CareersStatistics vs. Mathematics: Comparing Data-Driven CareersStatistics vs. Mathematics: Comparing Data-Driven Careers.

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Data has become a central, defining asset to businesses and governments today. Being able to transform data into readable, understandable insights is a much-needed skill. Mathematical-based professions, such as statisticians and mathematicians, are in high demand in our interconnected world. Being able to turn a jumble of numbers into readable information that a company can act upon is a useful skill. Even governments and their various departments use these professionals to help them understand the progress they have made toward achieving key goals, data-driven or otherwise.

While these two professional fields may look similar, several differences exist concerning statistics versus math. Students considering a Master of Science in Data Science degree need to gain a thorough understanding of the two concepts. Doing so can help them shape their career path in a way that best aligns with their interests and personal goals.

The first step in scrutinizing the differences between statistics and mathematics is to define both terms.

Statistics, sometimes known as statistical analysis, is the scientific procedure of gathering, analyzing, and interpreting data sets to extrapolate patterns and identify trends. These insights can help give businesses a clearer, unbiased picture of the attitudes, behaviors, and interests of current and potential consumers. This information can, in turn, lead to hyperfocused engagement strategies or new products that align with market demands.

Mathematics is the scientific process of measuring order, structure, and quantity. It uses calculations and logic to develop systems that define concrete and abstract concepts in a wide range of areas. These can include technology finance engineering athletics and even fields that might seem to have little to do with math, such as art. Conceptually speaking, it provides explanations for how things work.

Advanced education in statistics and math can lead to data science careers that apply these elements to achieve specific goals.

Mathematics is one of the oldest fields of human inquiry. Applied mathematics forms a significant part of many scientific fields. However, many mathematicians prefer to stick to the academic realm, solving problems that help expand the accumulated knowledge of the profession. Mathematicians continue to delve into the world of facts and figures, and academics in the field consistently develop new theorems or find innovative ways of testing old ones.

In industry, mathematicians are useful in several areas. A significant number of mathematicians work in government-funded organizations as well as in private enterprise. Mathematics is useful, for instance, to businesses that are leveraging such advanced tools as predictive analytics that enable real-world analytics models to be produced from existing raw data.

Applying mathematical theorems to real-world data can produce surprising results. Occasionally, when predicted outcomes dispute established mathematical models, it offers mathematicians opportunities to conduct further research to discover why.

Regardless of the path an individual chooses, a career as a statistician versus a mathematician can be very rewarding. A number of factors can affect salaries, but the U.S. Bureau of Labor Statistics (BLS) reports competitive compensation for both.

According to the BLS, the median annual salary of a statistician was $95,570 as of May 2021, with the top 10% making a median annual salary of $157,300. Salary can fluctuate by industry for instance, the BLS states that those working in computer systems design and related services bring in an annual mean wage of $119,210, while those in the scientific research and development services field earn a mean annual wage of $115,840.

Positions for mathematical occupations are projected to grow by 29% between 2021 and 2031, according to the BLS.

In their most basic forms, both mathematicians and statisticians deal primarily with numbers. In some cases, nonspecialists may even consider statisticians to be a subset of mathematicians. The work of these two professions displays several similarities, including a heavy dependence on theoretical research. Additionally, both mathematicians and statisticians tend to rely on previous groundwork to perform their calculations. They both use formulas or models to provide a real-world analog of their research.

The primary goals of both fields are also similar. Simplification is at the core. Both professions accomplish this by applying certain field-specific methodologies. Mathematicians may utilize formulas to transform complex readings into something simple to communicate. Similarly, statisticians can use data from thousands of individual sources and categories and transform them into visual representations.

The numbers that represent data points in a statistical model can have different representations depending on what a statistician is looking at. Determining the real-world impact of those numbers is a core competency of a statistician. For a mathematician, whose work is mostly in the realm of the abstract, the concern is representing quantitative data in a form that the average non-specialist can understand.

Another significant difference between the professions is where their work is applied. Governmental agencies traditionally employ mathematicians in large numbers, with some individuals working in private companies that receive some level of government funding. The main goal of mathematicians in these organizations is to quantify data in such a way as to enable key decision-makers to understand the results of math-driven initiatives and experiments.

Entering the fields of mathematics and statistics requires a particular set of skills and abilities that need to be practiced and exercised consistently. Gaining expertise in these skills allows professionals to stand out from other prospective job candidates.

Modeling: These courses focus on designing and applying modeling techniques to approach various problems and generate reasonable solutions. They include the following:.

Programming: Understanding the first principles of a concept enables a mathematician or statistician to conceptualize ways to automate data processing. To help graduates use computers to accomplish this task, several programming courses are offered, including the following:.

Probability: Both statisticians and mathematicians need to understand the impact that random chance plays in their work. Statistical probability courses define the concepts that a student should know to be successful.

This course teaches students best practices on share their findings in ways that emphasize the most crucial information.

Find Your Ideal Career in Statistics or Math.

U.S. Bureau of Labor Statistics, Mathematicians and Statisticians.