Probability Distributions

Slides:



Advertisements
Similar presentations
The Normal Distribution
Advertisements

Normal Distribution Sampling and Probability. Properties of a Normal Distribution Mean = median = mode There are the same number of scores below and.
Appendix A. Descriptive Statistics Statistics used to organize and summarize data in a meaningful way.
Introduction to Summary Statistics
It’s an outliar!.  Similar to a bar graph but uses data that is measured.
Introductory Statistics: Exploring the World through Data, 1e
Stem and Leaf Display Stem and Leaf displays are an “in between” a table and a graph – They contain two columns: – The left column contains the first digit.
Random Variables zDiscrete Random Variables: a random variable that can assume only a countable number of values. The value of a discrete random variable.
Continuous Probability Distributions In this chapter, we’ll be looking at continuous probability distributions. A density curve (or probability distribution.
Measures of Dispersion
6-2 The Standard Normal Distribution
The Normal Distributions
© 2002 Thomson / South-Western Slide 6-1 Chapter 6 Continuous Probability Distributions.
Summarizing Scores With Measures of Central Tendency
CHAPTER 2 Percentages, Graphs & Central Tendency.
Objective To understand measures of central tendency and use them to analyze data.
Chapter 3 Statistical Concepts.
1.3 Psychology Statistics AP Psychology Mr. Loomis.
2.1 Visualizing Distributions: Shape, Center, and Spread.
Data Handbook Chapter 4 & 5. Data A series of readings that represents a natural population parameter A series of readings that represents a natural population.
Lecture 7.  To understand what a Normal Distribution is  To know how to use the Normal Distribution table  To compute probabilities of events by using.
Chapter 8 Extension Normal Distributions. Objectives Recognize normally distributed data Use the characteristics of the normal distribution to solve problems.
Continuous Distributions. The distributions that we have looked at so far have involved DISCRETE Data The distributions that we have looked at so far.
Chapter 2: The Normal Distribution Section 1: Density Curves and the Normal Distribution.
Chapter 5 The Normal Curve. In This Presentation  This presentation will introduce The Normal Curve Z scores The use of the Normal Curve table (Appendix.
Copyright © 2012 by Nelson Education Limited. Chapter 4 The Normal Curve 4-1.
JMB Ch6 Lecture2 Review EGR 252 Spring 2011 Slide 1 Continuous Probability Distributions Many continuous probability distributions, including: Uniform.
Statistical Measures. Measures of Central Tendency O Sometimes it is convenient to have one number that describes a set of data. This number is called.
Unit 2: Analyzing Univariate Data Text: Chapter 1 Exploring Data AP Stats Theme I: A / B Displaying quantitative variables: histograms; constructing and.
Statistics for Psychology!
Central Tendency & Dispersion
Statistics Chapter 6 / 7 Review. Random Variables and Their Probability Distributions Discrete random variables – can take on only a countable or finite.
Holt Algebra 2 11-Ext Normal Distributions 11-Ext Normal Distributions Holt Algebra 2 Lesson Presentation Lesson Presentation.
Chapter 3 Displaying Data. 2 Major Points Plotting data: Why bother? Plotting data: Why bother? Histograms Histograms Frequency polygon Frequency polygon.
Lesson 13-3 Histograms.
2.3 Measures of Central Tendency Coach Bridges NOTES.
The Normal Distribution: Comparing Apples and Oranges.
Statistics Josée L. Jarry, Ph.D., C.Psych. Introduction to Psychology Department of Psychology University of Toronto June 9, 2003.
Standard Deviation by Hand 9 – Step Process See 4.2 WS.
Statistics Unit Test Review Chapters 11 & /11-2 Mean(average): the sum of the data divided by the number of pieces of data Median: the value appearing.
Describing Distributions. When making graphs of quantitative data, it is important to be able to tell what the graph is “saying”. In general, you do this.
PROBABILITY DISTRIBUTION. Probability Distribution of a Continuous Variable.
STATS DAY First a few review questions. Which of the following correlation coefficients would a statistician know, at first glance, is a mistake? A. 0.0.
Note: Normal Distribution Many sets of data collected in nature and other situations fit what is called a normal distribution. This means the data would.
Graphing options for Quantitative Data
Types of variables Discrete VS Continuous Discrete Continuous
Displaying Data with Graphs
Statistics Unit Test Review
Summarizing Scores With Measures of Central Tendency
6th Grade Math Lab MS Jorgensen 1A, 3A, 3B.
The Normal Distribution
STATS DAY First a few review questions.
Smart Phone Batteries Shape: There is a peak at 300 and the distribution is skewed to the right. Center: The middle value is 330 minutes. Spread: The.
Lesson 3.1: Normal Distribution
The facts or numbers that describe the results of an experiment.
Types of Distributions
Does graph represent a function? State the domain & range.
Unit 6A Characterizing Data Ms. Young.
Homework Check.
Chapter 6: Normal Distributions
The Shape of Distributions
10-5 The normal distribution
The facts or numbers that describe the results of an experiment.
Hananto Normal Distribution Hananto
Advanced Algebra Unit 1 Vocabulary
What does it mean to “Interpret Data”?
Shape, Center, Spread.
Normal Distributions 11-Ext Lesson Presentation Holt Algebra 2.
12-4 Normal Distribution.
Warm Up 4/30 What are you thankful for?
Presentation transcript:

Probability Distributions Some of the more general probability distributions.

Probability Distributions Graphs – the horizontal axis represents the range of values a variable can take and the vertical axis represents the probability of the event.

Unimodal Distribution This graph is an example of a unimodal distribution as it has only one peak.

Bimodal Distribution This graph is an example of a bimodal distribution as it has two peaks. Notice that they do not have to be the same height.

Skewed Distribution A skewed distribution has its peak off to one side (not in the middle).

Symmetric Distribution Symmetric distributions are as the name suggests, symmetric about the central vertical line.

Mean In a symmetric graph, like the one on the left, the mean value will be at the peak. In a skewed graph, like the one on the right, the mean value will not be at the peak. In this example it will be to the left of the peak.

Large standard deviation This graph has a large standard deviation as it’s peak is wide and short.

Small standard deviation This graph has a small standard deviation as it’s peak it tall and narrow.

Area under the curve The area under the curve indicates what the probability of that outcome is, so for example in this graph it is very likely (about 80%) for an event to occur in the range between the two small vertical lines.

Area under the curve In this graph it is quite unlikely (about 10%) for an event to occur at a value less than the small vertical line.

Area under the curve In this graph it is highly likely (about 90%) for an event to occur at a value greater than the small vertical line.