This course is intended for students with learning disabilities or other reading challenges. Students will learn strategies to improve oral and written language comprehension, reading fluency, vocabulary development through dictionary skills, and textbook reading strategies. The class will read a novel with various perspectives and diverse backgrounds represented. This will foster rich discussions in class, in an inclusive, supportive, and accessible environment that empowers all students to develop their reading skills and gain confidence.

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 covers descriptive and inferential statistics for students of social sciences, science, education, business, and engineering. Included are discussions of graphing and interpreting graphs, measures of the center and variation, binomial and normal probability, hypothesis testing using a variety of standard tests. This course uses technology to analyze data sets. 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". Prerequisites: Course taught at the level of intermediate algebra or placement as determined by the college’s multiple measures assessment process. Transfer credit: CSU; UC. Notes: Prior to Common Course Numbering, this course was known as MATH R105.