'Ti 83 84' presentation slideshows

Chapter 6. Continuous Random Variables

Chapter 6. Continuous Random Variables. Reminder: Continuous random variable takes infinitely many values Those values can be associated with measurements on a continuous scale (without gaps or interruptions). Example: Uniform Distribution.

775 views • 60 slides

Chapter 5

Chapter 5. The Binomial Probability Distribution and Related Topics. Table of Contents. 5.1 Introduction to Random Variables and Probability Distributions. 5.2 Binomial Probabilities. 5.3 Additional Properties of the Binomial Distribution.

595 views • 38 slides

Sections 10-1 and 10-2

Sections 10-1 and 10-2. Review and Preview and Correlation. PAIRED DATA. In this chapter, we will look at paired sample data (sometimes called bivariate data ). We will address the following:. Is there a linear relationship? If so, what is the equation? Use that equation for prediction.

265 views • 26 slides

Sections 6-1 and 6-2

Sections 6-1 and 6-2. Review and Preview and The Standard Normal Distribution. NORMAL DISTRIBUTIONS. If a continuous random variable has a distribution with a graph that is symmetric and bell-shaped and can be described by the equation we say that it has a normal distribution. REMARK.

365 views • 24 slides

Sections 5-1 and 5-2

Sections 5-1 and 5-2. Overview The Standard Normal Distribution. NORMAL DISTRIBUTIONS. If a continuous random variable has a distribution with a graph that is symmetric and bell-shaped and can be described by the equation we say that it has a normal distribution. REMARK.

338 views • 22 slides

Section 3-4

Section 3-4. Measures of Relative Standing and Boxplots. THE z SCORE. The z score (or standardized value ) is the number of standard deviations that a given x value is above or below the mean. It is found using the following expressions. Sample : Population :.

276 views • 22 slides

Estimating a Population Mean

196 views • 17 slides