Statistics Notes Week 3
Statistics Notes Week 3 Stat 190-01
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This 5 page Class Notes was uploaded by Elizabeth Schnarr on Friday September 9, 2016. The Class Notes belongs to Stat 190-01 at Truman State University taught by Sunghoon Chung in Fall 2016. Since its upload, it has received 5 views. For similar materials see Basic Statistics in Math at Truman State University.
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Date Created: 09/09/16
Week 3: 9/59/11 Statistics Chapter 2: Summarizing Data in Tables and Graphs Section 2: Organize Discrete and Continuous Data Shapes of distribution ● When describing a distribution one must pay attention to its shape, center, and spread Uniform Distribution: Bellshaped Distribution ● These two shapes are considered to be symmetrical Week 3: 9/59/11 Skewed Right Distribution Skewed Left Distribution ● Wherever the tail (thinner part) is on the graph is the direction the graph is skewed ● Peaks in graphs are called modes ● There are unimodals, bimodals, and multimodals Week 3: 9/59/11 Example of modes: Unimodal Bimodal Multimodal Week 3: 9/59/11 Statistics Chapter 5: Probability Sections 14 Definitions ● Experiment: an act or process of observation that leads to a single outcome that cannot be predicted with certainty ● Sample Space: (S), the collection of all possible outcomes ● Event: (E) any collection of outcomes from a probability experiment ● Simple event: (e) events with one outcome Intro ● Probability is the measure of the likelihood of a random phenomenon (experiment) or chance behavior ● Probability describes the longterm proportion with which a certain outcome will occur in situations with shortterm uncertainty ● Deals with experiments that yield random shortterm results or outcomes, yet reveal longterm predictability Event Example Sample space: S= (HT), (HH), (TT), (TH) Event Outcomes in Event 1 head and 1 tail (HT), (TH) Head on 1st coin (HT), (HH) At least 1 head (HT), (HH), (TH) Heads on both (HH) Week 3: 9/59/11 Probability Model Rules… 1. Probability Event, P(E), must be greater than or equal to 0 and less than or equal to 1 2. Sum of the probabilities of all outcomes must equal 1 Example of a Probability Model… Color Probability Brown 0.12 Yellow 0.15 Red 0.12 Blue 0.23 Orange 0.23 Green 0.15
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