MATH 1530 - Introductory Statistics

3 sem hrs cr

This course is an introduction to probability and statistics which provides an overview to descriptive and inferential statistics. Topics covered include descriptive statistics, elementary probability, distributions, confidence intervals, hypothesis testing, and linear regression. Prerequisite: Exemption from or completion of ENGL 0810  and READ 0810  

In rare and unusual circumstances, a course prerequisite can be overridden with the permission of the Department Lead for the discipline. Corequisite: If a student is not eligible for collegiate-level mathematics, they must enroll in MATH 0530 Learning Support for Introductory Statistics  as a co-requisite with the MATH 1530 course.

 

This course may include proctored exams which must be completed on campus or at an instructor approved proctoring center which may require additional costs to the student. Please consult your instructor for additional details.

Transfer (UT) or Non-Transfer Course (UN): UT

By the end of the course, students will be able to…

• collect and assemble quantitative data, making wide use of tables and graphs.
• develop a working knowledge of probability and its applications to the binomial and normal distributions.
• utilize hypothesis testing as it is related to the mean and proportion for future use in any research.
• describe and test the significance of relationships between two variables using correlation and linear regression.
• apply inferential methods to differentiate configurations of data.

Course Objectives

Throughout the course, students will have the opportunity to…

• construct and graph a frequency distribution as a histogram, and a frequency polygon.
• calculate measures of central tendency.
• calculate measures of variation.
• utilize the concepts of union and intersection when working with problems involving sample spaces, events, and probability experiments.
• determine the probability of an event.
• apply properties of probabilities.
• use counting techniques with probability.
• apply properties of conditional probability and independent events.
• utilize the properties of a binomial distribution.
• calculate a z-score.
• utilize a z-score when finding probabilities for continuous variables.
• find the z-score for a given probability.
• utilize a normal curve to approximate a binomial distribution.
• utilize the central limit theorem to find probabilities associated with sample means.
• test hypotheses about population parameters.
• utilize the t-test when a standard normal z-test is unsuitable.
• construct and utilize confidence intervals.
• calculate appropriate sample sizes for tests of proportions and means.
• determine linear correlation for bivariate data.
• develop a linear regression equation.