Applied Statistics
MATH 2020, 2020H
Fall 2025
This course is an introductory course in the use of descriptive and inferential statistics. Topics include graphical and numerical descriptive measures, probability, common random variables and their distributions including the binomial and normal distributions, the Central Limit Theorem, sampling procedures, confidence intervals and hypothesis testing of one variable, and an introduction to correlation and simple linear regression.
Required Textbooks:
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Elementary Statistics
by
For courses in Introductory Statistics.
Real data brings statistics to life
From cybersecurity to drones and Internet traffic, statistics influences and shapes the world around us. Market-leading author Marty Triola is committed to keeping Elementary Statistics current, with an unprecedented amount of new real data, to help students of all majors understand the role of statistics in the world around us. The revision continues to bolster the hallmarks that have made it so effective, giving students the foundational skills to apply statistical procedures and interpret data. Updates in the 14th Edition keep the text and MyLab® more relevant and supportive than ever; a wealth of new data sets, exercises, and examples along with larger data sets, content updates, and new videos support students.
Elementary Statistics is part of a series that also includes an Essentials version as well as technology-specific texts, Elementary Statistics Using the TI-83/84 Plus Calculator and Elementary Statistics Using Excel®. Data sets and other resources for this series are available in MyLab Statistics or pearson.com/math-stats-resources.
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Call Number: AVAILABLE FOR PURCHASE ONLINEISBN: 8220144721360
- Produce and explain graphical and numerical measures of central tendency and variation in data.
- Apply probability fundamentals and distributions.
- Describe data coming from binomial and normal distributions.
- Produce point and interval estimates and conduct proper hypothesis tests for population means and proportions.
- Demonstrate understanding of correlation and simple linear regression of data.
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