Master's in Applied Statistics Programs

Last Reviewed/Updated: February 20, 2020

The Masters in Applied Statistics is a degree program developed to train students in the utilization of mathematical and statistical techniques used to extract useful information from large sums of data.

Learning in this degree program can prepare you for working in fields focusing on information technology, business, and even healthcare.

Master of Applied Statistics Degrees

Beginning with insight into some of the most common programming languages used, such as Python, SAS, and R, students in this incredible degree program can grow into a career focused on making discoveries about data and developing models for extracting information for future use.

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At the masters-level, students can also participate in learning about leadership within this field and the data analysis skills required to follow-up on work completed by employees and the training styles most beneficial for your line of work.

While you learn more about the different types of data and have the opportunity to practice your skills on actual data sets, you can potentially add to your future resume to large organizations in search of data experts in the field.

Our team of educational experts has pulled together information from several different Masters in Applied Statistics programs in order to educate you further on what is required during your learning experience. Take a look in the guide below to better prepare yourself for the road ahead.

Online Programs

Education in the online realm is unlike what can be found in traditional learning environments. If you are geared up for a Masters in Applied Statistics program in your future, you should consider the convenience and flexibility provided by online degree programs.

In recent years, the trend of online education has be brought on by profound interest in computer technology and the internet. Most online degree programs allow students to engage in learning from their very own home, with some programs even allowing students to log in at any time of the day or night.

Online Masters in Applied Statistics programs can include online discussion boards for students to communicate with other learners in their program, as well as interactive data practice programs in which you can exercise your skills in data analysis and applied statistics.

An added benefit to online degree programs is that they are subjected to the same quality standards as traditional learning options. Students considering online options for their program can verify the accreditation information of their program through a thorough review of the program's web page or through information provided about the university as a whole.

Choosing online degree programs can be a great decision for students that are working full-time at careers in the field, or even for busy adults that do not want to miss out on free time with their families. Check out more about the contents of Masters in Applied Statistics programs in the sections below.

Online Master's Programs

Rochester Institute of Technology

Master of Science in Applied Statistics

New York has a number of institutions that provide higher education in applied science, but RIT has a very customizable program that allows part-time and full-time enrollment, and courses can be completed either online or on-campus at Rochester. The 30-credit hour curriculum requires four courses, various electives, and the option of a capstone or thesis project at the end. There are four concentrations to choose from that gives students more of a focus for their degree: Clinical Trails, Data Mining and Machine Learning, Industrial Statistics, and Informatics. Typically, the program will take two years to complete for full-time students, and up to three years for part-time status.

There is a time limit of seven years after enrollment. Students can be administered into the online program three times per academic year. Examples of electives that students can choose from are Predictive Analytics, Multivariate Analysis, and Time Series Analysis and Forecasting. Prospective students should hold a Bachelor's degree with a background in mathematics and statistics, and they should submit official transcripts, updated resume, two letters of recommendation, and a personal statement in the application process. GRE scores are not required.

University of Kentucky

Master of Applied Statistics

The College of Arts and Sciences offers a Master's degree within applied statistics that can be fully completed online. This program is geared for students that are looking for careers as statisticians, be it a data analyst or programmer that creates predictions. In addition to determining probability, other skills gained are working with R and SAS programming, and observing relationships among different variables in statistical sets. Unique features of the online program include "Talking with the Expert," which works similar to office hours with direct interaction between faculty and students, and real-time discussion boards will feature interaction among the student body with aid from faculty when necessary.

Admission requirements include transcripts that show at least a 2.75 cumulative GPA in undergraduate work, Graduate Record Examination scores with no minimum, and three letters of recommendation. Prerequisites for the program include two semesters of graduate-level calculus and a semester of statistical methods. The GRE must be submitted and cannot be waived. The school does not accept transfer credits from any other universities, even accredited. All coursework is distributed through the Canvas learning management system.

University of Kansas

Master of Science in Applied Statistics and Analytics

The KU Edwards Campus has a full applied statistics program that can be 100 percent completed online. Students have the option to choose the following concentrations to pursue: Statistics, Analytics, and Data Science. Within the curriculum, four courses will be dedicated to the concentration, four foundational courses, two additional electives, and the program culminates with a comprehensive exam. Online benefits include an asynchronous course format that is completely self-paced for students and virtual communication with faculty and other students in the program.

In addition to the Master's degree, there are two different graduate certifications that students can choose from in Applied Statistics and Applied Data Science. Both of these programs can also be completed online. The majority of the curriculum is the same for both, with the only unique classes being Categorical Data Analysis and Experimental Design for the statistics certification, and Data Acquisition and Visualization, and Statistical Learning I for the data science certification. Each program requires 15 credit hours to graduate.

Colorado State University - Fort Collins

Master of Applied Statistics

The Master's degree at the College of Natural Sciences in Fort Collins can be completed on-campus or online with the curriculum being the same in either pathway. Students have the ability to blend the two versions together if they live close enough to campus. Online coursework is distributed through the Canvas learning management system, and lectures can be viewed live when they take place or view the recording on-demand. Office hours are available to online students, and students can discuss topics within these classes amongst themselves in discussion boards or online conferencing. Exams will take place at an approved testing center within the student's area.

There are two specializations for students to consider when pursuing the degree: Data Science and Statistical Science. Up to 31 credit hours are needed to complete either pathway and it can be completed in just one year for full-time students. Prerequisites needed include calculus at least through multivariables, linear algebra, and undergraduate statistics. Students should have at least a Bachelor's degree from an accredited university. The GRE should have been taken within the last five years and scores should be submitted. Example electives that students can choose from are Business Intelligence, Mixed Models, and Applied Bayesian Statistics.

What is Applied Statistics?

What you know about general statistics can contribute to how well you can understand the basis for applied statistics. This area of study involves utilizing statistics to interpret data from both parametric and nonparametric tests.

Students within this degree program may analyze data from ANOVA, descriptive statistics, or even chi squares as part of their quest to make determinations about the meaning of this information, as well as provide these results in a format that is easily understood by those being reported to. In data science, applied statistics can be a helpful process for extracting knowledge from a wealth of uncertainty – which can be valuable for a wide range of reasons.

Large sums of data involving numbers can present a wide range of uncertainty for data professionals tasked with interpreting it. Missing values, variability, and time-to-event analyses are just a small portion of the available methods for use by professionals within this professional field.

The skills learned throughout this degree program can promote your move into this complex and fascinating field within data science. The interpretation of value-based data can provide businesses and individuals with more information into the meaning of data, which can be beneficial when seeking better ways to operate a business, reach the public, and identify relevant trends within marketing and development.

Studies into applied statistics can provide you with a foundation to explore different types of career options in the field, providing you with a more diverse professional experience after graduation. Our team of experts has provided you with a short list of some of the common statistical tools used by applied statisticians in the field below. Read through these to gain a better understanding of what this profession can mean for you in the future.

  • Statistical Machine Learning: Professionals working in areas responsible for the development of new machine learning technologies can learn skills relevant to their future within this field. Tools that may be utilized within this specific area of practice may include Topic Modeling, Tree-Based and Rule-Based Regression, Gradient Boosting, and Support Vector Machines.
  • Exploratory Data Analysis: Exploratory Data Analysis (EDA) involves the investigation into data and its patterns in order to test hypotheses, identify patterns, and visualize anomalies within the data set. This type of process can help professionals learn as much as they can about a new set of data in order to make assumptions about its meaning and what it represents.
  • Statistical Learning: When using Statistical Learning as a method for success within this field, professionals seek to build a statistical model based on predictors and response. The model developed within this process should be able to accurately predict response variables based upon predictor variables. Statistical Learning is categorized into Supervised Statistical Learning – which is the development of a model based on one or more inputs, and Unsupervised Statistical Learning – which is a model that contains inputs but not supervising output.

Typical Prerequisites for a Master’s in Applied Statistics Degree

When you are considering a Masters in Applied Statistics, you should be aware of the prerequisite requirements that can be part of your admissions into this program. Different university programs may have varying expectations, making full research into your program of interest necessary prior to enrollment.

A large number of students considering a transition into this degree field may come from undergraduate degree programs in Statistics, Computer Science, or even advanced programs in Calculus or Mathematics. Each of these programs could provide you with quick access to the prerequisite course requirements set forth by the graduate program.

Some courses that you may be required to complete prior to being accepted into this program include courses in single-variable calculus, multi-variable calculus, linear algebra, statistics, and computer programming. If you did not have access to these courses during your undergraduate program, you may receive conditional enrollment while you complete these courses through your graduate school.

In addition to course-related prerequisites, some universities may also ask that applicants to their program also have some type of experience in a data-related field. In some cases, substituted experience in statistical careers or computer programming could be acceptable for admissions.

The courses that are required to be completed prior to the actual degree program can often provide you with more helpful knowledge about the subject area, which can provide you with a higher level of predicted success throughout your program.

Typical Master of Applied Statistics Courses

One of the most important steps to take prior to enrollment into a Masters in Applied Statistics programs is reviewing the curriculum. It is within this area that you can learn more about the actual consistency of the program and what to expect as a new learner.

The courses that you take during this program can be diverse depending on a few factors including which school you choose, whether or not you have chosen a specialization, and the type of prerequisite courses that you have completed as of your enrollment date.

Our team of educational experts has collected some example courses from actual online Masters in Applied Statistics programs currently open for enrollment. Read more in the list below to see more about each topic and what it can teach you during your experience.

  • Business Database Systems: This course can provide students with valuable information pertaining the purpose and value of business database systems. Some of the core topics that you might expect to learn during this class include data mining, data modeling, encryption, and database design. Common business database systems like electronic mobile devices, ERP systems, data warehouses, and point-of-sale systems may be explored throughout learning in this course in order to help students apply their knowledge of data to each of the defined areas.
  • Statistical Consulting: One challenging aspect of Applied Statistics involves the communication of learned information to the paying resources. This course can outline some of the communication-related skills that can be relevant to work in this area, as well as some of the most helpful methods for displaying information for clients to review. Simplification of information may be a point of discovering in this course as students learn more about graphical representation of data, general presentation speaking skills, and consultation with current and future clients.
  • Machine Learning: If you are involved in an Applied Statistics program for generalized learning or if you have a specific career path in mind, courses like Machine Learning can be beneficial for helping you gain all-inclusive skills for work in the field. Students participating in this course can learn specific elements like K-means clustering, evaluation of model performance, neural networks, and dimension reduction. Each of these skills can be applied directly to general AS careers or machine learning careers.

Considering Tuition and Applied Statistics Scholarships

Graduate-level education can often come at a hefty price for new student on a search for better career opportunities. There are different methods for lowering the costs of your program and acquiring funds to help you cover the costs of your Masters in Applied Statistics degree.

Lowering your costs can first be achieved by choosing to pursue your degree online. This method allows you to completely eliminate the need for travel, housing, and food-related costs of living on campus, which can add up significantly when dedicating around 2 years of your time to an on-campus program.

Locating scholarships can also be beneficial in lowering your overall costs of higher education. Some of the most helpful ways to identify scholarship opportunities for new students is to explore what is offered by the school they are enrolling in, what is available within the community, and what is offered online.

Ellis R. Ott Scholarship for Applied Statistics and Quality Management

A simple internet search for scholarships within this degree field revealed many different scholarship opportunities for statistical learners. One opportunity, offered by The American Society for Quality, provides the Ellis R. Ott Scholarship for Applied Statistics and Quality Management.

Opportunities like this one may require that you provide proof of your excellence in undergraduate degree programs, as well as a professional letter regarding your intent as an applied statistician.

University-specific scholarships may be available to students that are working specifically on the Masters in Applied Statistics program, which can also include requirements including a minimum 3.0 GPA, an Applied Statistics degree specialization, and community or campus engagement.

Careers in Applied Statistics for Master’s Degree Graduates

In a world that is so reliant on computer technology and online business, a Masters in Applied Statistics can lead you into a wide variety of fascinating fields once you have completed it. In this section, our team will provide you with some more information about where you can work after graduation from this area.

Through a search of available job opportunities for Applied Statistics graduates, it was found that there is a wealth of organizations that are looking for educated professionals within this field to fill their staff. Organizations that are interested in gaining information from public social sites like Facebook are currently hiring analysts to draw information from this website, as well as from other online resources utilized by these organizations.

Healthcare organizations can also benefit from the expertise of statistics professionals with this degree. One organization currently seeking new applicants for an open position require a graduate that can help to organize, gather, and assess data provided from their scheduling software.

The general roles that you take once moving into the professional field can vary depending on the organization that you apply with. Many students may move on to be statistical analysts responsible for drawing information from different data resources, applied statisticians that can oversee data choices and data analysis, and even statistical managers that organize and supervised data projects for their organization.

Applied Statistics and Data Science Related Salaries

According to the US Bureau of Labor Statistics, job opportunities for mathematics and statisticians are expected to grow by 30 percent between the years of 2018-28. In terms of industries, working a federal government position is pays the highest with a median annual salary of $106,670. Insurance companies, the health care sector, and academia are significantly lower than that, hovering between $73,000 to $82,000 across the United States.

These salary figures can vary wildly throughout the nation, however, While the highest-paying jobs in statistics are mostly located in the Northeast (New York, Massachusetts, Maryland, etc.), other states to consider are North Carolina, Minnesota, Washington, California, and Idaho. The last one on the list has the lowest concentration among the highest salaries, but the average sits at $113,780 annually. This is sparked by electronics producer Micron, which has its headquarters in Boise, Idaho. They are responsible for products under the Ballistix and Crucial branding, as well as IM Flash Technologies.

Careers in applied statistics can take many position forms, such as a digital marketing analyst, data scientist, software developer, intelligence analyst, and more, as these all deal with statistical analytics to some extent. These opportunities are available in various tech firms, financial institutions, academic universities, health care facilities, and more. Some of the top metropolitan locations for these jobs in terms of pay include Silicon Valley in California, Boston in Massachusetts, Boulder in Colorado, and Raleigh in North Carolina.

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