BA Math (Sorry guys!)

[Cofffeee]

I could not find math courses on statistics.com. can anyone provide link for these courses please? I saw tons of dara science courses but not math

The data science courses seem to count as math in some cases. For instance (wants R familiarity, though): https://www.statistics.com/courses/spati...s-using-r/

Learning Outcome:
Upon completion of the course, the student will be able to describe spatial data using maps; define what is meant by spatial analysis and list some of the underlying difficulties; describe the statistical metrics and methods appropriate to spatial data; critique maps produced by other agencies on the WWW and in other media; undertake an analysis of patterns in data using the concept of complete spatial randomness; analyze patterns in point data, and detect non-randomness; analyze continuous field data and create contour maps; produce area/value (choropleth) maps of area aggregated data using the GeoDa package; and interpolate data to produce continuous surface models using a variety of alternative approaches in the 3Dfield package.
Instruction:
The methods of instruction include case studies, practical exercises, lecture, discussion, classroom exercises, and computer based training. The general course topics include describing spatial data using maps, analysis of patterns in point data, analysis of patterns in area data, detecting and measuring spatial autocorrelation in lattice data, analysis of continuous field data, and creating contour-type maps using inverse distance weighting and geostatistical methods.
Assessment:
The methods of assessments include quizzes, case studies, and final projects with a minimum passing score of 70 percent.
Credit Recommendation:
In the upper-division baccalaureate degree category, 3 semester hours in spatial statistics, geospatial statistics, or statistics (4/18).

This one has no prerequisites (unlike the above where you need familiarity with R): https://www.statistics.com/courses/risk-...d-queuing/

Learning Outcome:Upon completion of the course, the student will be able to use simulation to describe and measure the impact of uncertainty on decision problems; use optimization techniques with simulation to mitigate and manage risk; study queuing models used to describe and manage the behavior of waiting lines; and learn to use payoff tables, decision trees, multi-criteria scoring models, and AHP to analyze decisions problems.
Instruction:The methods of instruction include case studies and a final project with a minimum passing score of 80 percent. The general course topics include simulation; implementing and optimizing the model; Poisson distribution, arrival rate; mastering complexity; decision rules, decision trees; expected monetary value, regret, value of information; and sensitivity analysis.
Assessment:The methods of assessment include a final project with a minimum passing score of 80 percent.
Credit Recommendation:In the graduate degree category, 3 semester hours in statistics or decision science (3/18).

No prerequisites for this one either: https://www.statistics.com/courses/optim...ogramming/

Learning Outcome:
Upon completion of the course, the student will be able to describe what types of decisions are amenable to linear programming solutions; formulate a linear programming model, and represent it graphically; solve the LP model with spreadsheet-based software; use LP models for various decisions: make or buy, where to invest; and use sensitivity analysis and shadow prices to gain additional information from the LP solution.
Instruction:
The methods of instruction include case studies, practical exercises, lecture, discussion, and computer-based training. The general course topics include the role of models in decisions; sources of bias and error in human decision making; good decisions vs. good outcomes; formulating linear programming models; graphical representations; solving LP models in spreadsheets; role of sensitivity analysis in the larger decision context; shadow prices; robust optimization; and Simplex Method.
Assessment:
The methods of assessment include quizzes and a final project with a minimum passing score of 70 percent.
Credit Recommendation:
In the upper-division baccalaureate degree category, 3 semester hours in mathematics or business management (3/18).

Thank you