Master of Science in Applied Statistics


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Course Overview

The online master’s degree in applied statistics provides students with a range of knowledge, skills, and experiential training including: Download Course Catalog.

  • A theoretical foundation in probability and mathematical statistics
  • Regression
  • Experiment design
  • Logistic regression and models of counts
  • Multivariate methods
  • The ability, acquired through case study, to analyze a wide variety of data and apply
    appropriate techniques, according to data type and research objective
  • The opportunity to design and conduct an applied research project with advisor assistance and
    approval

Program Structure:

Course Code First Semester Courses Credit
STA 801 Linear Algebra 5
STA 802 Real Analysis 5
STA 803 Introduction to Mathematical Software 5
STA 804 Introduction to Probability Theory 5
STA 805 Combinatories 5
STA 806 Computer Programming 5
TOTAL CREDITS 30
Course Code Second Semester Courses Credit
STA 811 Statistical Inference 5
STA 812 Applied Stochastic Processes 5
STA 813 Algorithms 5
STA 814 Optimization 5
STA 815 Numerical Analysis 5
STA 816 Regression Analysis 5
TOTAL CREDITS 30
Course Code Third Semester Courses Credit
STA 821 Theoretical Computer Science 5
STA 822 Time Series Analysis 5
STA 823 Information System 5
STA 824 Categorical Data Analysis 5
STA 825 Distribution Theory 5
STA 826 Multivariate Analysis 5
TOTAL CREDITS 30
Course Code Fourth Semester Courses Credit
STA 831 Advanced Probability 4
STA 832 Biostatistics 4
STA 833 Theory of Sampling 4
STA 834 Statistical Techniques in Data Mining 4
STA 835 Testing of Hypothesis 4
ENT 836 Entrepreneurship 5
STA 837 Master Thesis 5
TOTAL CREDITS 30

 

Career Opportunities

The most common role for a graduate with these skills is as an applied statistician, data analyst, or data scientist. As a data analyst or scientist, you will:

  • Help shape the design of a research project or study
  • Play an important role in implementing the study or survey
  • Be responsible for collecting, organizing, and analyzing the data from various primary and/or
    secondary resources, such as surveys conducted as part of the study itself or from existing
    large public or private data sets
  • Help develop guidelines or protocols for collecting the data and extrapolating findings from
    the data
  • Work with sophisticated data management and statistical software to undertake your analyses
    and write reports on your findings
  • Explain past behavior, identify likely outcomes and scenarios, explore future trends, and make
    projections

 

Contact KIU:

  • study@kesmondsuniversity.org
  • admissions@kesmondsuniversity.org
  • www.kesmondsuniversity.org