chapter 1 statistics n.
Skip this Video
Loading SlideShow in 5 Seconds..
CHAPTER 1 STATISTICS PowerPoint Presentation
Download Presentation

Loading in 2 Seconds...

play fullscreen
1 / 19

CHAPTER 1 STATISTICS - PowerPoint PPT Presentation

  • Uploaded on

CHAPTER 1 STATISTICS. Statistics is a way of reasoning, along with a collection of tools and methods, designed to help us understand the world. READ THE BOOK. Think Show Tell For Example Step-by-Step What can go wrong* What have we learned?. CHAPTER 2 DATA.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'CHAPTER 1 STATISTICS' - tieve

Download Now An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
chapter 1 statistics


Statistics is a way of reasoning, along with a collection of tools and methods, designed to help us understand the world

read the book
  • Think
  • Show
  • Tell
  • For Example
  • Step-by-Step
  • What can go wrong*
  • What have we learned?
chapter 2 data
  • Information together with its context
    • Numerical
    • Names
    • Labels
  • Five W’s
    • Who, What, When, Where, Why
    • How
  • Respondents: Individuals who answer a survey
  • Subjects or Participants: People on whom we experiment. (Experimental Units)
  • Records or Cases: Rows in a database or data table. Individuals about whom or about which, we have the data.
  • Variables
    • Characteristics recorded about each individual. These are usually columns in a data table, and they should have a name that identifies what has been measured.
      • Categorical (or Qualitative)
      • Quantitative (Numerical values with measurement units)
      • Ordinal
more w s
…more W’s
  • Where and When?
    • Country? Year?
  • How?
    • How the data was collected?
  • Why?
    • Reason for the study
  • Investments. According to an article in Fortune (Dec.28, 1992), 401(K) plans permit employees to shift part of their before-tax salaries into investments such as mutual funds. Employers typically match 50% of the employees’ contribution up to about 6% of salary. One company, concerned with what it believed was a low employee participation rate in its 401(k) plan, sampled 30 other companies with similar plans and asked for their 401(k) participation rates.
identify the w s
Identify the W’s
  • Who ?
    • 30 Companies
  • What ?
    • Participation Rates
      • Quantitative (Units : Percent)
  • When ?
    • Sometime after 1992
identify the w s cont
Identify the W’s (cont.)
  • Where ?
    • USA
  • Why ?
    • The company was concerned with its participation rate compared with other companies
  • How ?
    • Companies were sampled using an unspecified method
  • Flowers. In a study appearing in the journal Science a research team reports that plants in southern England are flowering earlier in the spring. Records of the first flowering dates for 385 species over a period of 47 years indicate that flowering has advanced an average of 15 days per decade, an indication of climate warming according to the authors.
identify the w s1
Identify the W’s
  • Who ?
    • 385 species of flowers over 47 years
  • What ?
    • First flowering date
      • Quantitative (Units : days)
  • When ?
    • Not specified
identify the w s cont1
Identify the W’s (cont.)
  • Where ?
    • Southern England
  • Why ?
    • Researchers associate this behavior with climate warming
  • How ?
    • Observation. ( Method not specified)
chapter 3 displaying and describing categorical data
Chapter 3. Displaying and Describing Categorical Data
  • Make a picture
  • First Make piles
    • Organize the counts by categories in a frequency table (counts) or a relative frequency table (percentages)
    • Both types of tables describe the distribution of the categorical variable because they name the possible categories and tell how frequently each occurs
the area principle
The Area Principle
  • The area occupied by a part of the graph. It should correspond to the magnitude of the value it represents
bar charts
Bar Charts
  • A bar chart displays the distribution of a categorical variable, showing the counts for each category next to each other for easy comparison.
pie charts
Pie Charts
  • Relative proportion (percentages instead of counts).
  • Pie charts show the whole group of cases as a circle, each of the pieces has a size proportional to the fraction of the whole in each category.
contingency tables
Contingency Tables
  • Two categorical variables
marginal and conditional distributions
Marginal and Conditional distributions
  • Marginal Distribution
    • Distribution of either variable alone (at the margin of the table)
  • Conditional Distribution
    • A distribution in one variable for only those individuals satisfying some condition on another variable.
  • Note : If the distribution of one variable is the same for all categories of another we say that the variables are independent.
  • Step-by-Step page 31
  • What can go wrong
    • Check the charts on pages 34
    • Simpson’s Paradox (page 35)