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Unformatted text preview: Who: what is being studied, individual cases What : the variables Relative frequency table : displays percentages instead of counts Area principle: area occupied by a part of the graph should correspond to its value Bar chart : displays the distribution of a categorical variable Relative frequency: shows percentages Contingency table : shows how individuals are distributed along each variable Histogram: shows distribution of quantitative variables Stem and leaf : shows individual values (having a key is very important) Marginal distribution: the frequency distribution of variables Dot plot : dot along axis for each data point Segmented Bar Chart: treats each bar as a whole and divides it up proportionally into segments corresponding to the percentage of each group Simpsons paradox: When averages are taken between numbers that cannot be evenly averaged unfair averaging When describing, always use shape, center, and spread humps in histogram are called modes (unimodal, bimodal, multimodal, uniform) symmetric, or skewed (Graphs are skewed towards the tail) mention outliers median is resistant to outliers Interquartile Range (IQR)= Q3 Q1 Measures of Center: Use mean when graph is symmetric, median when skewed Measures of Spread: Use standard deviation when graph is symmetric, IQR when skewed, range can also be used to generally describe data Fences of Box plot = Q1  1.5IQR (lower fence) Q3 + 1.5IQR (upper fence) Z score = (ymean of y)/STD 689599.7 Rule 68% of values lay within 1STD  1STD, 95 lay between 2 2 STDs, 99.7% lay within 3 STDs Standard deviation = (  ) y y 2n 1 5 Number Summary:...
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This note was uploaded on 04/04/2008 for the course ILRST 2100 taught by Professor Vellemanp during the Fall '07 term at Cornell University (Engineering School).
 Fall '07
 VELLEMANP

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