Statistical Reasoning for everyday life

Slides:



Advertisements
Similar presentations
Copyright © 2011 Pearson Education, Inc. Statistical Reasoning.
Advertisements

Chapter 3 Graphic Methods for Describing Data. 2 Basic Terms  A frequency distribution for categorical data is a table that displays the possible categories.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 2 Exploring Data with Graphs and Numerical Summaries Section 2.2 Graphical Summaries.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Lecture Slides Elementary Statistics Eleventh Edition and the Triola.
Slide 1 Spring, 2005 by Dr. Lianfen Qian Lecture 2 Describing and Visualizing Data 2-1 Overview 2-2 Frequency Distributions 2-3 Visualizing Data.
8.1 Types of Data Displays Remember to Silence Your Cell Phone and Put It In Your Bag!
1.1 Displaying and Describing Categorical & Quantitative Data.
Slide Slide 1 Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Lecture Slides Elementary Statistics Tenth Edition and the.
Reading Graphs and Charts are more attractive and easy to understand than tables enable the reader to ‘see’ patterns in the data are easy to use for comparisons.
1 Probabilistic and Statistical Techniques Lecture 3 Dr. Nader Okasha.
Properties of Bar Graphs  Bars can be vertical or horizontal  Bars are of uniform width and uniformly spaced  Length of bars represent value of variable.
Organization and description of data
Section 3.2 ~ Picturing Distributions of Data
Presentation of Data.
Statistics - Descriptive statistics 2013/09/23. Data and statistics Statistics is the art of collecting, analyzing, presenting, and interpreting data.
SECTION 12-1 Visual Displays of Data Slide
More Graphs and Displays
© 2008 Pearson Addison-Wesley. All rights reserved Chapter 1 Section 13-1 Visual Displays of Data.
12.1 – Visual Displays of Data In statistics: A population includes all of the items of interest. A sample includes some of the items in the population.
Chapter 2 Summarizing and Graphing Data
Descriptive Statistics: Tabular and Graphical Methods
July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 3 Organizing and Displaying Data.
Census A survey to collect data on the entire population.   Data The facts and figures collected, analyzed, and summarized for presentation and.
Sta220 - Statistics Mr. Smith Room 310 Class #3. Section
Variable  An item of data  Examples: –gender –test scores –weight  Value varies from one observation to another.
Sta220 - Statistics Mr. Smith Room 310 Class #3. Section
LECTURE 5 10 SEPTEMBER 2009 STA291 Fall Itinerary Graphical Techniques for Interval Data (mostly review) Describing the Relationship Between Two.
Quantitative Skills 1: Graphing
Graphical summaries of data
Copyright © 2011 Pearson Education, Inc. Statistical Reasoning Discussion Paragraph next time….
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter 2 Descriptive Statistics: Tabular and Graphical Methods.
Chapter 1.4. Variable: any characteristic whose value may change from one individual to another Data: observations on single variable or simultaneously.
Statistics Unit 2: Organizing Data Ms. Hernandez St. Pius X High School
Graphing Data: Introduction to Basic Graphs Grade 8 M.Cacciotti.
Unit 5C Statistical Tables and Graphs. TYPES OF DATA There are two types of data: Qualitative data – describes qualities or nonnumerical categories EXAMPLES:
Copyright © 2014 Pearson Education. All rights reserved Picturing Distributions of Data LEARNING GOAL Be able to create and interpret basic.
1 Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 3 Graphical Methods for Describing Data.
Section 2.2 Bar Graphs, Circle Graphs, and Time-Series Graphs 2.2 / 1.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Section 2-2 Frequency Distributions.
When data is collected from a survey or designed experiment, they must be organized into a manageable form. Data that is not organized is referred to as.
Unit 4 Statistical Analysis Data Representations.
© 2008 Pearson Addison-Wesley. All rights reserved Chapter 5 Statistical Reasoning.
WELCOME TO THE UNIT 3 SEMINAR NAME: CAROL HANNAHS StatCrunch Workshop….. Sunday, Jan 22 at 7 pm ET MM207 Project.
Slide Slide 1 Section 2-4 Statistical Graphics. Slide Slide 2 Key Concept This section presents other graphs beyond histograms commonly used in statistical.
Chapter 2: Organizing Data Section 1: Bar Graphs, Circle Graphs, and Time Plots.
MM07 Statistics Welcome to the Unit 3 Seminar Dr. Bob.
Displaying Data  Data: Categorical and Numerical  Dot Plots  Stem and Leaf Plots  Back-to-Back Stem and Leaf Plots  Grouped Frequency Tables  Histograms.
Data Analysis. Data Analysis Discussion 1.Why are graphs, tables, and charts important? 2.What are the different ways in which you can represent data?
Copyright © 2014 Pearson Education. All rights reserved Picturing Distributions of Data LEARNING GOAL Be able to create and interpret basic.
Sullivan – Fundamentals of Statistics – 2 nd Edition – Chapter 2 Section 2 – Slide 1 of 37 Chapter 2 Section 2 Organizing Quantitative Data.
Slide Copyright © 2009 Pearson Education, Inc. Ch. 3.1 Definition A basic frequency table has two columns: One column lists all the categories of.
Histograms, Frequency Polygons, and Ogives 2-2 Graphs Note: This PowerPoint is only a summary and your main source should be the book. Instructor: Alaa.
Copyright © 2009 Pearson Education, Inc. 3.2 Picturing Distributions of Data LEARNING GOAL Be able to create and interpret basic bar graphs, dotplots,
Graphical Presentation Dr. Amjad El-Shanti MD, PMH,Dr PH University of Palestine 2016.
Graphs that Enlighten and Graphs that Deceive Chapter 2 Section 4.
Graphs Another good way to organize this data is with a Graph. Graph – a diagram that shows a relationship between two sets of numbers. So do we have two.
2.3 Other Types of Graphs Instructor: Alaa saud Note: This PowerPoint is only a summary and your main source should be the book.
2.3 Other Types of Graphs Instructor: Alaa saud Note: This PowerPoint is only a summary and your main source should be the book.
 2012 Pearson Education, Inc. Slide Chapter 12 Statistics.
Descriptive Statistics: Tabular and Graphical Methods
3.2 Picturing Distributions of Data
3 2 Chapter Organizing and Summarizing Data
Statistical Tables and Graphs
Lecture 3 part-2: Organization and Summarization of Data
Bar Graphs, Circle Graphs, and Time-Series Graphs
Types of Graphs… and when to use them!.
Statistical Reasoning Discussion Paragraph next time….
Statistical Reasoning
Chapter 3 Visual Display of Data.
Presentation transcript:

Statistical Reasoning for everyday life Intro to Probability and Statistics Mr. Spering – Room 113

3.2 Picturing Distributions of Data Distribution – refers to the way in which values are spread over all possible values. We can summarize a distribution in a table or show a distribution visually with a graph. {i.e. bar graph, histogram, pareto chart, dot plot, pie chart, stem-and-leaf plot, line chart, time-series diagram, scatter plot, and box-whisker plot (review in section 4.3)}

3.2 Picturing Distributions of Data (Crucial Components) Important Labels for Graphs Vertical scale – numbers along the vertical axis should clearly indicate the scale. The numbers should line up with the tick marks – the marks along the axis that precisely locate the numerical values. Horizontal scale – the categories should be clearly indicated along the horizontal axis (Tick marks may not be necessary for qualitative data, but should be included for quantitative data.) Vertical axis title – Include a title that describes the variable shown on the vertical axis Horizontal axis title – Include a title that describes the variable shown on the horizontal axis Title/caption and legend (key) – the graph should have a title or caption that explains what is being shown, and if applicable, lists the source of the data. If multiple data sets are displayed on a single graph, include a legend or key to identify the individual data sets.

3.2 Picturing Distributions of Data Bar graph – is a diagram consisting of bars that represent the frequencies (or relative frequencies) for particular categories. The lengths of the bars are proportional to the frequency. EXAMPLE: Number of police officers in Crimeville, 1993 to 2001

3.2 Picturing Distributions of Data Dot plot (line plot) – similar to a bar graph, except each individual data value is represent by a dot or symbol. EXAMPLE: Barley Yields, Grand Rapids

3.2 Picturing Distributions of Data Pareto chart – is a bar graph with the bars arranged in order according to frequency. Pareto charts make sense only for data at the nominal level of measurement.

3.2 Picturing Distributions of Data Pie Chart (circle graph) – circle divided so that each wedge represents that relative frequency of a particular category. The wedge size is proportional to the relative frequency and 360 degrees. The entire pie represents the total relative frequency of 100%. Example: Music preferences in young adults 14 to 19

3.2 Picturing Distributions of Data Histogram – is a bar graph showing a distribution for quantitative data (at the interval or ratio level); the bars have a natural order and the bar widths have specific meaning. EXAMPLE: Exam Scores of 27 students

3.2 Picturing Distributions of Data Stem-and-leaf plot – much like a histogram turned sideways, except in place of bars we see a listing of the individual data sources or values. {Allows us to list all data easily} Example: Data Set A   Data Set B Leaf Stem 3 2 0 4 1 5 6 7 The numbers 40, 42, and 43 are from Data Set A. The numbers 41, 45, 46, and 47 are from Data Set B.

3.2 Picturing Distributions of Data Line chart (line graph) – shows distribution of quantitative data as a series of dots connected by lines. Each dot is the center of the bin it represents and the vertical position is the frequency value for the bin. {Line charts help us to see increasing and decreasing trends.} Example:

3.2 Picturing Distributions of Data Scatter plot – is a chart that uses Cartesian coordinates to display values for two variables. The data is displayed as a collection of points, each having one coordinate on the horizontal axis and one on the vertical axis. A scatter plot does not specify dependent or independent variables. Either type of variable can be plotted on either axis. Scatter plots represent the association (not causation) between two variables.

3.2 Picturing Distributions of Data Time-series diagram (plots over time) – A histogram or line chart in which the horizontal axis represents time. NEXT SLIDE…

3.2 Picturing Distributions of Data EXAMPLE: Time-series diagram

3.2 Picturing Distributions of Data Summary: Many different ways to display data. Remember be very observant, and study displays carefully for misleading information. Finally, make sure you can recognize and interpret all forms of display.

3.2 Picturing Distributions of Data GOOD LUCK !!!!!!!

3.2 Picturing Distributions of Data How many degrees hotter was it on Wednesday than Thursday? 30-10=20 degrees hotter

3.2 Picturing Distributions of Data Data from an experiment was put into a circle graph and a bar graph. Which set of bars could show the same data as the circle graph? A C B D

3.2 Picturing Distributions of Data A band director surveyed her students to ask them their favorite instrument. The table shows the results of the survey. FAVORITE INSTRUMENTS Instrument Drums Flute Piano Trumpet Violin Number of Students 5 16 10 6 9 Which is the most appropriate graph of the information in the table to show what fraction of the students choose each instrument?

3.2 Picturing Distributions of Data The following stem-and-leaf plot shows the ages of the teachers at Central Heights Elementary School. Which age group has the most teachers? Stem Leaf 2 4 9 3 0 3 3 7 4 1 4 5 5 2 5 8 KEY: 4 | 5 = 45 A Teachers in their twenties C Teachers in their forties B Teachers in their thirties D Teachers in their fifties Teachers in their thirties

3.2 Picturing Distributions of Data The graph shows the population of four towns. a. Which town appears to have about three times the population of Town C? b. Which town actually has twice the population of Town C? c. Explain why the graph is misleading. Town A Town D Left out important/relevant information

3.2 Picturing Distributions of Data HW: pg 110 # 1, 5 – 14 all, 19, 21, 25