This course is an introduction to statistical thinking and processes, including methods and concepts for discovery and decision-making using data. Topics include descriptive statistics; probability and sampling distributions; statistical inference; correlation and linear regression; analysis of variance, chi-squared, and t-tests; and application of technology for statistical analysis including the interpretation of the relevance of the statistical findings. Students apply methods and processes to applications using data from a broad range of disciplines. Successful completion of this course fulfills the mathematics competency requirement for the AA/AS degree. Notes: Prior to Common Course Numbering, this course was known as MATH V44. Prerequisites: Placement as determined by the college's multiple measures assessment process or completion of a course taught at or above the level of intermediate algebra. Transfer credit: CSU; UC. Formerly: MATH V44; Math 44.

This course is an introduction to statistical thinking and processes, including methods and concepts for discovery and decision-making using data. Topics include descriptive statistics; probability and sampling distributions; statistical inference; correlation and linear regression; analysis of variance, chi-squared, and t-tests; and application of technology for statistical analysis including the interpretation of the relevance of the statistical findings. Students apply methods and processes to applications using data from a broad range of disciplines. Successful completion of this course fulfills the mathematics competency requirement for the AA/AS degree. Notes: Prior to Common Course Numbering, this course was known as MATH V44. Prerequisites: Placement as determined by the college's multiple measures assessment process or completion of a course taught at or above the level of intermediate algebra. Transfer credit: CSU; UC. Formerly: MATH V44; Math 44.

This course is an introduction to statistical thinking and processes, including methods and concepts for discovery and decision-making using data. Topics include descriptive statistics; probability and sampling distributions; statistical inference; correlation and linear regression; analysis of variance, chi-squared, and t-tests; and application of technology for statistical analysis including the interpretation of the relevance of the statistical findings. Students apply methods and processes to applications using data from a broad range of disciplines. Course Credit Limitations: MC, CSU, and UC - Credit will not be awarded for both the honors and regular versions of a course. Credit will be awarded only for the first course completed with a grade of “C” or better or "P". Moorpark College Honors Program requires a letter grade. Credit Limitation: MC and CSU: STAT C1000, STAT C1000H, MATH M15, MATH M15H, PSY M125 and SOC M125 combined: maximum credit, 1 course; UC: STAT C1000, STAT C1000H, MATH M15, MATH M15H, MATH M37DS, PSY M125 and SOC M125 combined: maximum credit, 1 course. Prerequisites: Placement as determined by the college’s multiple measures assessment process or completion of a course taught at or above the level of intermediate algebra. Notes: Prior to Common Course Numbering, this course was known as MATH M15.Transfer credit: CSU; UC. Formerly: MATH M15.

Covers limits, continuity, differentiation and integration of algebraic functions, and differentiation and integration of transcendental functions with applications. Honors work challenges students to be more analytical and creative through expanded assignments and enrichment opportunities. Prerequisites: Course taught at the level of precalculus or placement as determined by the college’s multiple measures assessment process. Transfer credit: CSU; UC.