Demonstrate the benefits of using mathematical skills as a soldier.
DefinitionDemonstration might include any number of examples of the way mathematics is used in day-to-day operations (e.g., logistical information, quantitative analysis, computational skills) and the way mathematics is used more specifically and at an advanced level (e.g., engineering, technology, statistical analysis, logic, quantitative reasoning).
- In what situations might a soldier use mathematical skills?
- What mathematics-related tools or instruments are commonly used?
- How is math related to logic and quantitative reasoning?
- Why is it important to reason logically?
Related Standards of Learning
The student will select and call library functions to process data, as appropriate.
The student will implement conditional statements that include “if/then” statements, “if/then/else” statements, case statements, and Boolean logic.
The student will implement pre-defined algorithms, including sort routines, search routines, and simple animation routines.
The student will describe the way the computer stores, accesses, and processes variables, including the following topics: the use of variables versus constants, parameter passing, scope of variables, and local versus global variables.
The student will apply graphs to conflict-resolution problems, such as map coloring, scheduling, matching, and optimization.
The student will describe and apply sorting algorithms and coding algorithms used in sorting, processing, and communicating information.
The student will select, justify, and apply an appropriate technique to solve a logic problem.
The student will use algorithms to schedule tasks in order to determine a minimum project time. The algorithms will include critical path analysis, the list-processing algorithm, and student-created algorithms.
The student will analyze graphical displays of univariate data, including dotplots, stemplots, boxplots, cumulative frequency graphs, and histograms, to identify and describe patterns and departures from patterns, using central tendency, spread, clusters, gaps, and outliers.
The student will analyze numerical characteristics of univariate data sets to describe patterns and departures from patterns, using mean, median, mode, variance, standard deviation, interquartile range, range, and outliers.
The student will analyze scatterplots to identify and describe the relationship between two variables, using shape; strength of relationship; clusters; positive, negative, or no association; outliers; and influential points.
The student will describe the methods of data collection in a census, sample survey, experiment, and observational study and identify an appropriate method of solution for a given problem setting.
The student, given data from a large sample, will determine and interpret point estimates and confidence intervals for parameters. The parameters will include proportion and mean, difference between two proportions, difference between two means (independent and paired), and slope of a least-squares regression line.