Applied Statistics for Data Analysis
PHA 6935 Applied Statistics for Data Analysis


This is a 3-credit course.


Applied Statistics for Data Analysis provides students with the basic knowledge of how scientific evidence is classified and how statistical procedures are utilized to analyze data. This encompasses common descriptive measures such as the mean, standard deviation, and uncertainty of measurements as well as comparative statistics that aim to compare two or more population means or perform simple linear regression. These basic statistical operations are important for every-day tasks conducted in an analytical laboratory. No matter which field the student will be working in, a basic understanding of the scientific method and the statistics used to analyze data is essential to the job performance.


Please review our recommended course order.


Module Topic
Module 1 Introduction to Scientific Evidence and Statistics
Module 2 Measures of central tendency and the normal distribution
Module 3 Probability
Module 4 Discrete random variables and probability distributions
Module 5 Estimation of mean and standard deviation and the normal distribution
Module 6 Hypothesis testing for one or two population means, Student t-test
Module 7 Hypothesis testing for small sample sizes and multinomial experiments, Fisher’s exact test
Module 8 Analysis of Variance and multiple comparison tests
Module 9 Simple linear regression

Required Materials

Introductory Statistics
Author: Prem S. Mann
Publisher: Wiley; 10th edition (2020)
ISBN-13: 978-1119679639
ISBN-10: 111967963X

Recommended Materials

Introductory Statistics Student Study Guide
Author: Prem S. Mann
Publisher: Wiley; 7th edition (1/12/2010)
ISBN: 978-0470572405

Library Access

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