{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

# RM 13 - To d a y s O u t l i n e Administrative stuff Data...

This preview shows pages 1–4. Sign up to view the full content.

Today’s Outline Administrative stuff Data Distributions Central Values Sample Variation Probability Standard Error Administrative stuff Blackboard Announcement sent on Friday Stream selection extended until Wednesday midnight New information online about brian tumor pathology Upcoming dates: Tue 10/12 HW2 (GEMS) due today. Electronic copy by 5 pm. Wed 10/13 Stream selection due Thu 10/14 HW3 (lecture series) due. Electronic copy by 5 pm. Tue 10/19 In class Feynman quiz Oil spill presentation “The science and technology of the Gulf of Mexico Spill” Boyd Auditorium (JGB 2.324), Wednesday 13th at 5:15 pm Mike Mason, VP Base Management, BP Exploration and Production Technology David Tsao, Tech Specialist for Remediation Engineering and Technology group, BP Remediation Management, Strike Team leader for remediation of the Deepwater Horizon incident Intended as a robust technical dialogue with UT JSG professionals and students. 1 2 3

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Data Distributions Data is often a collection of measurements of a set of possible values. Outcomes can be discrete (e.g., dice throws) or continuous (e.g., height of UT students). There are two important characteristics used to describe a distribution – the central or typical value, and the spread around that value. The mode is the most common outcome. If you own a shoe store, which shoes size should you stock the most pairs for? If you arrange the data in order from smallest to largest., the median is the value in the middle. Note the median is not sensitive to outliers (extreme values) not typical of the rest of the data. The average athlete salary in 2004 was \$82,450 Half of the 12,000 people employed as athletes earn < \$46K/year Central value So to find the median, you divide your sample in half, and find the value at the halfway point. Why stop there? You can divide your sample into thirds, quarters, tenths, or any number of groups. A visual representation of the sample divided into equal size groups or bins , showing the number of the sample found in each bin, is called a histogram . Not enough bins — doesn’t really show the shape of the distribution Too many bins — each contains one or zero samples and the shape is lost again A good number of bins is a balance of these two extremes. 4 5 6
Sample Mean Σ x i i = 1 n x = n Most commonly we calculate the sample mean , or average Central value x 1 +x 2 +x 3 ... +x n = n In lab last week you collected data using the fishbags. Each fishbag represents a lake full of fish.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 9

RM 13 - To d a y s O u t l i n e Administrative stuff Data...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online