MAT 203 Principles of Statistics

Instructor

66 Students enrolled

Description
Curriculum

MAT – 203 Principles of Statistics is a self-study course whose grade is based solely on the final examination. This course of study that is necessary to be prepared for the final examination consists of seventeen lessons based on the readings from the textbook. Students should read the entire text of all the reading assignments. There are no formal homework assignments, but students are encouraged to take the practice quiz for each chapter to ensure that they have understood the relevant course material are well prepared for the final exam.
Course Description:
This course deals with how to use various graphical displays and measures of location and variability to describe data. The course considers elementary probability and sampling distributions, and uses the normal and t-distributions in estimation and hypotheses testing. It includes descriptive techniques for simple linear regression and correlation. Use of a graphing calculator is required; computer software may be used. Students are expected to have completed an equivalent of College Algebra.

Learning Outcomes:
Upon successful completion of the course, students will be able to:

Explain the usefulness of obtaining and analyzing data for making decisions and advancing knowledge.
Describe the prevalence of statistics in the advancement of knowledge and will be able to intelligently learn about reports about studies that involve statistical issues.
Recognize that statistical inference is only meaningful within the context of a study.
Apply the basic techniques of statistical inference to data, to interpret the results of a statistical analysis using the concepts of confidence intervals or tests of significance, and to assess when particular inferential procedures are appropriate.

Interpret the results of data collection and critique the quality of studies based upon issues of data collection.
Apply basic data analytical techniques to uncover patterns and truths within data sets, and will understand the primary importance of data visualization.
Explain each step within a study, such as deciding how to collect data, clean data, build appropriate models, and assess and evaluate statistical models in determining what conclusions can be drawn.
Communicate the results of statistical analyses or quantitative findings