# STAT 201

## Download as PDF

## Statistics for Engineers and Scientists

Statistics
College of Computational, Mathematical, & Physical Sciences

### Course Description

The scientific method; probability, random variables, common discrete and continuous random variables, central limit theorem; confidence intervals and hypothesis testing; completely randomized experiments; factorial experiments.

### When Taught

Fall, Winter, Spring

### Min

3

### Fixed

3

### Fixed

3

### Fixed

0

### Title

Test Statistic and P-Value

### Learning Outcome

Compute the test statistic and p-value for H0 : µ = µ0 from a random sample

### Title

Statistically Significant Interaction

### Learning Outcome

Explain a statistically significant interaction

### Title

Simple Problems

### Learning Outcome

Solve simple problems using axioms of probability, conditional probability, independence, and Bayes' theorem

### Title

Experimental Design

### Learning Outcome

Understand the basics of experimental design, including the definition of the experimental unit, response, variable, factor(s), and level(s) of a basic experiment, and the role of randomization and replication to permit causal inference

### Title

Interval for µ

### Learning Outcome

Compute the confidence interval for μ from a random sample and make the correct decision about an experiment when given a confidence interval

### Title

Compute Probabilities

### Learning Outcome

Compute probabilities, expected value, and variance using the pdf of a discrete univariaterandom variable

### Title

Numerical and Graphics Summary

### Learning Outcome

Compute numerical and graphics summary statistics using professional statistical software and explain difference between populations given the summaries (numerical or graphical)

### Title

Sampling Distribution

### Learning Outcome

Understand the definition of the sampling distribution of x-bar, and identify the mean, variance, and shape of the sampling distribution given the population information

### Title

Normal Distribution

### Learning Outcome

Compute probabilities for the normal distribution

### Title

One-factor ANOVA Table

### Learning Outcome

Compute the ANOVA table for data from a completely randomized design using professional statistical software

### Title

Two-factor ANOVA Table

### Learning Outcome

Compute the ANOVA table for data from a two factor experiment using professional statistical software