Recommended Course Sequences

Your field of interest will determine the sequences of courses that you should take while working on your degree. Please consult the list of interests below.

Data science is an interdisciplinary field that incorporates applied statistics, applied mathematics, and computer science. The Applied Statistics M.S. program at CSULB will equip you with a conceptual foundation, as well as practical experience. This powerful combination will empower you with the skills fthat many employers seek.

If you are interested in data science, the following is the recommended course sequence. This prospective program is contingent upon the thesis choice for the culminating activity. Only the final Spring semester would change should the student select the comprehensive exam option.

  1. Fall #1
    • STAT 475 Data Analysis with SAS
    • STAT 510 Regression Analysis
    • STAT 530 Experimental Design and Analysis
  2. Spring #1
    • STAT 520 Statistical Inference
    • STAT 550 Multivariate Statistical Analysis
    • STAT 574 Data Mining
  3. Fall #2
    • STAT 572 Computational Statistics
    • STAT 576 Data Informatics
    • STAT 580 Time Series
  4. Spring #2
    • STAT 698 Thesis or Project
      or non-STAT elective (see list below)

Advancement to Candidacy should typically be completed by the end of your first academic year.

Non-STAT Electives

Possibilities include:

  • BIOL 574: Bioinformatics
  • CECS 406: Topics in Machine Learning
  • IS 480: Advanced Database Management
  • MATH 521: Matrix Method in Data Analysis and Pattern Recognition
  • MKTG 675: Marketing Analytics
  • PHYS 590: Topics in Data Science with Python

Please Note

All programs are subject to the parameters delineated in the CSULB Catalog, which overrules any conflicting information presented here.

Statistical methods have been applied extensively to the life sciences and to medicine, including modern applications to genomics data. CSULB boasts faculty who have been research statisticians in cutting edge oncology studies, as well as Food and Drug Administration (FDA) clinical trials.

If you are interested in biostatistics, the following is the recommended course sequence.

  1. Fall #1
    • STAT 475 Data Analysis with SAS
    • STAT 510 Regression Analysis
    • STAT 530 Experimental Design and Analysis
  2. Spring #1
    • STAT 520 Statistical Inference
    • STAT 550 Multivariate Statistical Analysis
    • STAT 592 Advanced Methods in Biostatistics
  3. Fall #2
    • STAT 483 Survey Sampling
    • STAT 590 Survival Analysis
    • non-STAT elective (see list below)
  4.  Spring #2
    • STAT 698 Thesis or Project
      or STAT 560 Nonparametric Statistics

Advancement to Candidacy should typically be completed by the end of your first academic year.

Non-STAT Electives

Possibilities include:

  • BIOL 574: Bioinformatics
  • CECS 406: Topics in Machine Learning
  • HSC 500. Principles of Epidemiology
  • IS 480: Advanced Database Management
  • MATH 521: Matrix Method in Data Analysis and Pattern Recognition

Please Note

This prospective program is contingent upon the thesis choice for the culminating activity. Only the final Spring semester would change should the student select the comprehensive exam option.

All programs are subject to the parameters delineated in the CSULB Catalog, which overrules any conflicting information presented here.

The trends and seasonality in data related to sales, marketing and other economic indicators can be decoded using statistics. These techniques produce forecasts that inform data driven decision making.

If you are interested in applications in economics or finance, the following is the recommended course sequence. This prospective program is contingent upon the thesis choice for the culminating activity. Only the final Spring semester would change should the student select the comprehensive exam option.

  1. Fall #1
    • STAT 475 Data Analysis with SAS
    • STAT 510 Regression Analysis
    • STAT 530 Experimental Design and Analysis
  2. Spring #1
    • STAT 520 Statistical Inference
    • STAT 550 Multivariate Statistical Analysis
    • STAT 484/485 Actuarial Science
  3. Fall #2
    • STAT 576 Data Informatics
    • STAT 580 Time Series
    • non-STAT elective*
  4. Spring #2
    • STAT 698 Thesis or Project
      or STAT 544 Statistical Consulting

Advancement to Candidacy should typically be completed by the end of your first academic year.

Non-STAT Electives

Possibilities include:

  • CECS 406: Topics in Machine Learning
  • ECON 586: Econometrics II
  • IS 480: Advanced Database Management
  • MKTG 665: Seminar in Marketing Research
  • MKTG 675: Marketing Analytics

Please Note

All programs are subject to the parameters delineated in the CSULB Catalog, which overrules any conflicting information presented here.

Pre-Approved Outside Courses

Provided your program plan maintains compliance with the current catalog, you are allowed to take non-STAT courses to count towards your 30 units necessary for graduation. Generally speaking, graduate advisor approval is necessary, but there is a pre-approved list of courses you are recommended to choose from. This includes:

  • All MATH 4xx or MATH 5xx courses
  • All MTED 4xx or MTED 5xx courses
  • BIOL 574/474: Bioinformatics
  • CECS 406/456: Machine Learning
  • ECON 586: Econometrics II
  • ENGR 570: Applied Data Analysis for Engineers
  • HSC 500: Principles of Epidemiology
  • IS 480: Advanced Database Management
  • IS 570: Business Intelligence
  • MKTG 665: Seminar in Marketing Research
  • MKTG 675: Seminar in Marketing Analytics

It is important to note that you should have covered the prerequisite material listed in the relevant course descriptions in the CSULB Catalog before you consider taking them. For most of the courses outside of the Mathematics & Statistics Department, your quantitative background as a STAT graduate student should be sufficient.

To request enrollment in the courses you are interested in, please email the course's instructor. You can find who the instructor is in the CSULB Schedule of Classes.