# Academics  /  Courses  /  DescriptionsIEMS 303: Statistics

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### Prerequisites

IEMS 202 or equivalent; CS 150 or equivalent

### Description

Introduction to the foundations of statistics and statistical computing for data analysis and their applications. Covers descriptive statistics and statistical inference for estimation, testing and prediction.

• This course is a major requirement for Industrial Engineering
• May not receive credit for both 303 and any of the following:
• IEMS 201, STAT 210, STAT 320-1, BMD ENG 220, or CHEM ENG 312.

LEARNING OBJECTIVES

• Be able to use the R statistical package to prepare and analyze data
• Understand estimation, sampling distributions and their properties, including bias and the variance of an estimate
• Find probabilities involving sample means or totals from both normal and non-normal populations
• Know when to use, compute, interpret and apply confidence, prediction and tolerance intervals
• State null and alternative hypotheses, compute and evaluate test statistics, compute P-values, and draw conclusions
• Estimate simple linear regression models, evaluate whether model assumptions hold with residual and QQ plots, test hypotheses, compute confidence and prediction intervals in R, interpret R-squared

TOPICS

• Frequency distributions, histograms, measures of center, position and dispersion
• Distributions of the sample mean, proportion and variance
• Confidence intervals for means, proportions and variances; prediction and tolerance intervals
• Single- and two-sample hypothesis tests for means, proportions and variances
• Simple linear regression: model assumptions, least squares estimates and properties, confidence and prediction intervals, hypothesis tests, and diagnostics
• Introduction to the multiple linear regression model

MATERIALS

Recommended: Probability and Statistics for Engineering and the Sciences by Jay L. Devoured

ISBN 13: 978-1305251809