Difference between revisions of "Stat 202 Discussion"

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(Part I)
(Part I)
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* Understand the traditional way of structuring data (tables, cases, variables, values).
 
* Understand the traditional way of structuring data (tables, cases, variables, values).
* Be able to recognize the types of variable in a data set (quantitative, identifier, categorical (ordinal, nominal, binary)).
+
* Be able to recognize the types of variables in a data set (quantitative, identifier, categorical (ordinal, nominal, binary)).
 
* Understand that different analyses and displays are appropriate for different types of variables.
 
* Understand that different analyses and displays are appropriate for different types of variables.
* Understand the concept of a distribution (what values it takes and how often it takes those values).
+
* Understand the concept of a distribution (what values a variable takes and how often it takes those values).
 
* Be able to describe the distribution of a quantitative variable (histogram, box plot, QQ plot, shape, outliers, center, spread, modes, symmetry, skewness, normal/bell shaped, mean, median, standard deviation, Q1, Q3, IQR, percentiles).
 
* Be able to describe the distribution of a quantitative variable (histogram, box plot, QQ plot, shape, outliers, center, spread, modes, symmetry, skewness, normal/bell shaped, mean, median, standard deviation, Q1, Q3, IQR, percentiles).
 
* Be able to describe the distribution of a categorical variable (bar plot, pie chart, frequency table).
 
* Be able to describe the distribution of a categorical variable (bar plot, pie chart, frequency table).

Revision as of 16:50, 31 October 2018

Broad Objectives

Part I

  • Understand the traditional way of structuring data (tables, cases, variables, values).
  • Be able to recognize the types of variables in a data set (quantitative, identifier, categorical (ordinal, nominal, binary)).
  • Understand that different analyses and displays are appropriate for different types of variables.
  • Understand the concept of a distribution (what values a variable takes and how often it takes those values).
  • Be able to describe the distribution of a quantitative variable (histogram, box plot, QQ plot, shape, outliers, center, spread, modes, symmetry, skewness, normal/bell shaped, mean, median, standard deviation, Q1, Q3, IQR, percentiles).
  • Be able to describe the distribution of a categorical variable (bar plot, pie chart, frequency table).