MATH& 146 Introduction to Statistics

5 credits

This course covers the organization and graphical representation of data, measures of central tendency and variation, basic probability theory, discrete probability distributions and the binomial formula, the normal distribution, hypothesis testing, confidence intervals, correlation, and linear regression.

Prerequisites: MATH 098 recommended or MATH 099 (or equivalent placement score for MATH& 146)

Quarters Offered: All

Global Outcomes:
This course teaches to the global outcome of Critical Thinking.

Student Outcomes/Competencies:
Upon successful completion of this course the students will be able to:

Organize and graph data using scatterplots, histograms, and boxplots
Calculate mean, standard deviation, z-scores, and percentile values
Solve problems using the basic elements of probability theory, such as sample spaces, the addition rule, and the multiplication rule
Calculate the mean and standard deviation of a probability distribution
Calculate expected value
Calculate probabilities using the binomial probability formula
Calculate probabilities and find percentile values using the normal distribution and the central limit theorem
Construct and interpret confidence intervals
Perform hypothesis tests
Measure and test for correlation
Use regression equations to make predictions

Total Hours: 50 Lecture Hours: 50