Stat 202 Discussion
From Sean_Carver
Broad Objectives
Part I
- Understand the traditional way of structuring data (datasets, 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 of a variable (what values the variable takes and how often it takes those values).
- Be able to describe the distribution of a single 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).
- Understand the concept of a transformation of a variable (e.g. z-score, change of units, log) and know the special properties of a linear transformation.
- Understand what it means for data (quantitative variable) to fit a Normal model with parameters (histogram, QQ-Plot, including typical noise) and know how to make predictions based on that assumption.
