chap3 - Chap 3 Random Sampling Probability and the Binomial...

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1 1 Chap 3: Random Sampling, Probability, and the Binomial Distribution Chapter 3 2 Review of Chap. 2 2.1 Frequency Plots – How to organize your data and display it? Categorical data – Bar chart Quantitative data z Stem-and-Leaf Diagrams z Histogram & interpretation 2.2 How to summarize your data? Visual Summary of Data z Shapes of Frequency Distribution z ( Mode, symmetry, skewness) Quantitative Summary

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2 3 Review: How to summarize your data? Quantitative Summary: z Measure of Center Parameter vs. statistics, sample mean, sample median, and the visualization of their relationships. z Modified Boxplot , Quartiles Quartiles (Q1, Q2, Q3), five-number summary, lower fence, upper fence, modified boxplot, parallel boxplot z Measure of Dispersion (how spread is your data) Range, IQR, sample SD, sample variance visualizing those measures of dispersion (range, IQR, SD) and compare them. 4 Visualizing Measures of Dispersion z Range : min Æ max, cover 100% of data Intuitive, but poor for extreme tails of dist z IQR: spread of middle 50% of the data In histogram, Q 1 , Q 2 , Q 3 divide the area under the bars into 4 equal parts. Intuitive, resistant to extreme tails More challenging to estimate in statistics z SD: Less intuitive, may subject to extreme tails of the data Nice statistical property
3 5 Visualize SD z If sample data is approximately asymmetric and bell shaped (as in the textbook, “unimodel, not too skewed, tails are not overly long or short”), then 6 Visualize SD (mean, SD) is the foundation of Classical Statistics.

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