Organizing Data.

Slides:



Advertisements
Similar presentations
Very simple to create with each dot representing a data value. Best for non continuous data but can be made for and quantitative data 2004 US Womens Soccer.
Advertisements

Chapter 2 Organizing Data Understandable Statistics Ninth Edition
Copyright © 2014 Pearson Education, Inc. All rights reserved Chapter 2 Picturing Variation with Graphs.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Lecture Slides Elementary Statistics Eleventh Edition and the Triola.
8.1 Types of Data Displays Remember to Silence Your Cell Phone and Put It In Your Bag!
Frequency Distributions and Graphs
Data a collection of facts, such as values or measurements.
Organizing and Summarizing Data Chapter 2.1,
Copyright © Cengage Learning. All rights reserved. 2 Descriptive Analysis and Presentation of Single-Variable Data.
StatisticsStatistics Graphic distributions. What is Statistics? Statistics is a collection of methods for planning experiments, obtaining data, and then.
Chapter 2 Organizing Data Understanding Basic Statistics Fifth Edition By Brase and Brase Prepared by Jon Booze.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 2 Descriptive Statistics: Tabular and Graphical Methods.
Unit 4 Statistical Analysis Data Representations.
GrowingKnowing.com © Frequency distribution Given a 1000 rows of data, most people cannot see any useful information, just rows and rows of data.
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
Displaying Distributions with Graphs. the science of collecting, analyzing, and drawing conclusions from data.
Understanding Basic Statistics
Chapter 4 Displaying Quantitative Data Describing One Quantitative Variable Distribution of variable –Summary of different values observed for the variable.
Copyright 2011 by W. H. Freeman and Company. All rights reserved.1 Introductory Statistics: A Problem-Solving Approach by Stephen Kokoska Chapter 2 Tables.
Statistics - is the science of collecting, organizing, and interpreting numerical facts we call data. Individuals – objects described by a set of data.
Describing Data Week 1 The W’s (Where do the Numbers come from?) Who: Who was measured? By Whom: Who did the measuring What: What was measured? Where:
Descriptive Statistics: Tabular and Graphical Methods
Descriptive Statistics: Tabular and Graphical Methods
Chapter 1.1 Displaying Distributions with graphs.
Chapter(2) Frequency Distributions and Graphs
Frequency Distributions and Graphs
Chapter 2 Frequency Distribution and Graph
Welcome to Week 02 Tues MAT135 Statistics
Chapter 4 Review December 19, 2011.
Chapter 2 Descriptive Statistics
Graphics GrowingKnowing.com © 2013.
Unit 4 Statistical Analysis Data Representations
Displaying Quantitative Data
Statistical Reasoning
Laugh, and the world laughs with you. Weep and you weep alone
Displaying Distributions with Graphs
Descriptive Statistics
DS2 – Displaying and Interpreting Single Data Sets
Chapter 2 Presenting Data in Tables and Charts
Organizing and Visualizing Variables
CHAPTER 1: Picturing Distributions with Graphs
Honors Statistics Chapter 4 Part 4
DAY 3 Sections 1.2 and 1.3.
Frequency Distributions and Graphs
An Introduction to Statistics
STA 291 Spring 2008 Lecture 3 Dustin Lueker.
Describing Distributions of Data
Frequency Distributions
Give 2 examples of this type of variable.
The facts or numbers that describe the results of an experiment.
Drill {A, B, B, C, C, E, C, C, C, B, A, A, E, E, D, D, A, B, B, C}
Sexual Activity and the Lifespan of Male Fruitflies
Statistics: The Interpretation of Data
Identifying key characteristics of a set of data
CHAPTER 1 Exploring Data
Bellwork Thursday, April 19th
CHAPTER 1 Exploring Data
Basic Practice of Statistics - 3rd Edition
Basic Practice of Statistics - 3rd Edition
Statistics Frequencies
Honors Statistics Review Chapters 4 - 5
The facts or numbers that describe the results of an experiment.
CHAPTER 1 Exploring Data
Understanding Basic Statistics
Experimental Design Experiments Observational Studies
Organizing, Displaying and Interpreting Data
Displaying Distributions with Graphs
Types of variables. Types of variables Categorical variables or qualitative identifies basic differentiating characteristics of the population.
Chapter 2: Organizing Data
Graphical Descriptions of Data
Presentation transcript:

Organizing Data

Frequency ·. How many of the data are. in a category or range · Frequency ·   How many of the data are in a category or range ·    Just count up how many there are

Notation: n  number in sample x  number in a certain category

Relative frequency ·. Percent (or fraction) of the Relative frequency ·   Percent (or fraction) of the data that are in a certain category

Frequency Distribution. Counting how many of the Frequency Distribution Counting how many of the data are in various ranges or categories

Histogram A bar graph that shows a frequency distribution

Types of distributions

Uniform Distribution ·. All ranges or categories. have nearly the same Uniform Distribution ·  All ranges or categories have nearly the same value ·   a.k.a. “Rectangular” distribution

Skewed Distribution ·. Top-heavy or bottom-. heavy · Skewed Distribution ·   Top-heavy or bottom- heavy ·     More data at one end than the other

Normal Distribution ·. Big in the middle, small at. the sides · Normal Distribution ·   Big in the middle, small at the sides ·    Makes a mirror image

· a.k.a. “Symmetrical” distribution · a.k.a. “bell curve”

·. Normal distributions are. the best distributions for ·   Normal distributions are the best distributions for statistical purposes ·   In a large population, virtually any characteristic will take on an approximately normal distribution.

Bimodal Distribution ·. 2 “humps” ·. More than one most Bimodal Distribution ·   2 “humps” ·     More than one most common value (or range)

Other terms used when organizing data:

Cluster ·. a number or range where. there is a lot of data · Cluster ·   a number or range where there is a lot of data ·   the “humps” in a normal or bimodal distribution ·   These are of interest when we are looking for trends.

Gap · a range where there is no data (or sometimes very little data)

Outlier ·. A piece of data that lies. outside of the main body Outlier ·  A piece of data that lies outside of the main body of the data ·   Something much bigger or much smaller than the rest

·. An “exception” to the rule ·. There is always a gap ·    An “exception” to the rule ·   There is always a gap between an outlier and the rest of the data

· In analyzing data, we look for reasons to explain gaps and outliers.

COMMON WAYS OF ORGANIZING DATA

· Bar Graph o Shows differences in numbers by category

·. Pareto Chart. o. a special kind of bar. graph that organizes · Pareto Chart o    a special kind of bar graph that organizes data (which must combine to make a whole) from largest to smallest to make it easier to compare things.

o This makes it easier to spot categories with the most data.

· Pictograph or pictogram o    Uses pictures of objects to approximate a bar graph

o. While pictographs can. be fun to look at, be. careful that the o    While pictographs can be fun to look at, be careful that the information is still clearly communicated.

·. Circle Graph. o. Shows PERCENT. (relative frequency) in · Circle Graph o   Shows PERCENT (relative frequency) in different categories, by dividing a circle into angles.

o. The parts must. combine to make a. whole. o. Sometimes circle o   The parts must combine to make a whole. o   Sometimes circle graphs will show raw numbers, but they are designed to show percents.

o A doughnut is a variation on the same idea.

o. You can figure out how. many degrees are in. each angle by taking o   You can figure out how many degrees are in each angle by taking the percent X 360o.

o. A divided rectangle. (sometimes in the form. of a thermometer) also o   A divided rectangle (sometimes in the form of a thermometer) also accomplishes the same purpose.

·. Line Graph OR Time. Plot. o. Also called a “time · Line Graph OR Time Plot o   Also called a “time plot” or “time series graph” o   Shows how a variable changes over time.

·. Ogive. o Line graph that. shows CUMULATIVE. frequency distribution · Ogive o    Line graph that shows CUMULATIVE frequency distribution (the grand total of everything up to a certain date)

Percentage of Children Who Have Had Some Form of Formal Schooling at Different Ages

o. The percentage. always grows,. because you take what o   The percentage always grows, because you take what you had before and add onto it. o   So the line will always go up or stay the same.

Public Buildings in the United States Fully Compliant with the Americans with Disabilities Act

o. Usually levels off at the. top. o. Often approaches, but o   Usually levels off at the top. o    Often approaches, but rarely equals 100% (or the total number in the group)

Other things you might use an ogive for: •. Percent of babies who Other things you might use an ogive for: • Percent of babies who have spoken their first word by different ages

•. Number of people who. have seen an. advertisement that was • Number of people who have seen an advertisement that was first introduced during the Superbowl after various amounts of time

•. Number of homes that. have air conditioning. turned on when the • Number of homes that have air conditioning turned on when the temperature reaches different levels • Percent of people who have ever had sexual relations by different ages

When you make a graph …

·. You should include a title. or explanation of the. graph’s purpose · You should include a title or explanation of the graph’s purpose. · You should choose an appropriate type of graph for what you want to display.

·. You must include a scale. and legend. ·. The scale must go in even · You must include a scale and legend. · The scale must go in even intervals.

·. Bar and line graphs should. always start at zero (or · Bar and line graphs should always start at zero (or indicate 0 if both positive and negative numbers are possible). Sometimes for practical reasons you must show a break, but realize this is always deceptive.

Categories being. compared should be of. comparable size. · Categories being compared should be of comparable size. · For instance, if you use age groups, you should go in even intervals.

Percentages on circle. graphs should add up to. 100%. · Percentages on circle graphs should add up to 100%. · Categories can’t overlap and must account for everything.

· Pictographs should include pictures that are the same size.

· You should avoid 3-D graphics, which magnify differences in size.

·. Make sure your graph. shows only the. information—not · Make sure your graph shows only the information—not extraneous or misleading details.

Examples of misleading graphs:

· Using the wrong type of graph

· Bar or line graphs that don’t start at 0 or have an even scale

· Pictographs with two- dimensional figures

· Graphs with misleading 3-D graphics

· Overlapping categories

Stem & Leaf Plots

One quick way to organize quantitative data is a stem & leaf plot One quick way to organize quantitative data is a stem & leaf plot. The plot itself approximates a histogram.

Stem ·. the first part of a number ·. for example, the tens in a Stem ·  the first part of a number ·    for example, the tens in a 2-digit number

Leaf · the end of a number · for example, the ones in a 2-digit number

To make a stem & leaf plot: 1. Draw a line down the To make a stem & leaf plot: 1. Draw a line down the middle of your paper

2. Place the stems of your. numbers in order down the 2.  Place the stems of your numbers in order down the left side of the line (including any missing numbers)

3. After each stem, write the leaves of the associated numbers

·. Write the leaves in. order from smallest to. largest. · ·    Write the leaves in order from smallest to largest ·    If a leaf repeats, write it more than once.

Example: 35, 17, 26, 39, 28, 50, 37, 21, 17, 35, 19

Making a stem & leaf plot ·  sorts the data from smallest to highest ·    gives you an idea of the type of distribution · shows outliers & gaps