Summary Stats  Data and Models Book cover image

Summary Stats Data and Models

- Richard D De Veaux
ISBN-10 1292022450 ISBN-13 9781292022451
126 Flashcards & Notes
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A snapshot of the summary - Stats Data and Models Author: Richard D De Veaux ISBN: 9781292022451

  • 1 Stats starts here

  • What is one of the interesting chalanges of Statistics?

     

    Here can be more than one right answer. 

  • 2 Data

  • 2.2 Data Tables

  • Why do we make data tables?

    To organize the values and make the context of the data clear.

  • 2.3 who

  • What do rows of a data table correspond with?

    Individual cases about Whom (or which- if they're not people) we record some characteristics.

  • What are experimental units?

    Animals,  websites or other inanimate subjects on which we experiment.

     

  • 2.4 What and why

  • What is a quantitative variable?

    A measured variable with units answers questions about the quantity of what is measured.

  • What should you do when it isn't clear if a variable is categorial or quantitive?

    Think about Why you are looking at it and what you want it to tell you.

  • 2.6 Identifying identifiers

  • What are identifier variables?

    It assigns a variable as a unique identity.

  • What can you do with identifier variables?

    -Combine data from different source

    -protect confidentiality

    -provide unique labels.

  • 2.8 What can go wrong

  • What can go wrong in reading data?

    -You can label a variable as categorial or quantitative without thinking about the question you want it to answer.

    -When variable's values are numbers, don't assume it's quantitative. They don't have to be.

    -not being skeptical about discovering the truth with the data you're interpretating.

  • 3 Displaying and describing categorial data

  • 3.1 The three rules of data analysis

  • Why do you have to make pictures of the data?

    -A display of your data will reveal things you are nog likely to see in a table of numbers and will help you to think clearly about the patterns and relationships that may be hiding in your data. 

    -It will show the important features and patterns. It shows you things you did not ecpect to see:  the extraordinary (possibly wrong) data values or unexpecterd patterns.

    -the best way to tellothers about your data.

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