Difference between revisions of "Stat 202 Discussion"
From Sean_Carver
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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 | + | * 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 | + | * 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).
