# Statistics (STAT) courses

Butte College · 2026-2027 Catalog · 2 courses

Source: https://butte.curriqunet.com/catalog/iq/25393/28400/27505

"Offered" lists sections in this catalog year's class schedules: Fall 2026, Winter 2027, Spring 2027.

### STAT C1000 — Introduction to Statistics

- **Units:** 4
- **Hours:** 68 hours lecture
- **Prerequisite:** 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
- **C-ID:** MATH 110
- **Transfers to:** CSU, UC
- **Offered:** Fall 2026, 32 sections (/c/butte-college/schedule/fall-2026/stat.md); Spring 2027, 25 sections (/c/butte-college/schedule/spring-2027/stat.md)

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. (C-ID MATH 110).

### STAT C1000E — Introduction to Statistics

- **Units:** 4
- **Hours:** 34 hours lecture, 68 hours activity
- **Prerequisite:** 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
- **C-ID:** MATH 110
- **Transfers to:** CSU, UC
- **Offered:** Fall 2026, 9 sections (/c/butte-college/schedule/fall-2026/stat.md); Spring 2027, 7 sections (/c/butte-college/schedule/spring-2027/stat.md)

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. This course has embedded support. (C-ID MATH 110).