Summary

This document introduces various types of data, including categorical and quantitative data. It also discusses data displays such as bar charts, pie charts, contingency tables, histograms, box plots, and stem-and-leaf displays, along with how to understand and analyze the shape, center, and spread of these data. Different measures and concepts like modes, skewness, and outliers are explained in the document.

Full Transcript

8/26 - Intro Varibles-charistics records abt each individual in astudy Identifier number or code unique assigned to each -...

8/26 - Intro Varibles-charistics records abt each individual in astudy Identifier number or code unique assigned to each - individual ex) SS number IP adress , , phone number Categorical-variable that tells us the group/category an individual belongs to ex) race , gender neighborhood religion , , Quantitative-variable that contains measured numerical values w/ measurement units ex) distance, temp, volume mass , , money Chapter 1. 1- Analyzin Categorical Data important features - clear title in data displays - clear axs/labels - units key (If necessary - Area Principle of the should correspond area occupied by part a graph - to the magnitude of the value it represents Frequency table actual aut - Relative frequency-percent out of total amt Data Categorical Condition -check by making pie charts bar charts chart pie - contingency table-standard table Marginal distribution totals in a category - of table totals Conditional Distributions percentages - independence no association b variables - Displaying Quantitative Data with Graphs Distribution of a quantitative variable - whenever you describe the distribution of a quantitate variable you always need to tak about shape , center t spread Histogram - Data covers whole data set data gaps mean no - axls-variable *hape - axis-frequency - Modes - Peaks of display - unimodal bimodal - - multimodal - Uniform doesn't to have appear any obvious mode - Symetry - Bell curve most things aren't symetric = Skewness - A distribution is skewed in the direction of the tails Outliers off from the body of 1 any straglers" or that stand points - the distribution # of games Gretzky Played Stem & Displays leaf 458 - for small Data sets 5 8) 10 = 8 815 means 6 ex 85 4 Truncated Stem a leaf displays 03448899 432 = 413 8000000122 413 = 430 - 439 8) 0 = 80 games Quantitative Data Condition Check by making a histogram dot plot or box plot - , , checking that data quantitative is - : Displaying & Summarizing Quantitative Data Center Median : - middle value of a data set when the values are in numerical order Spread Range : Range max-min - = value per data set - one Disadvantage of Range -single extreme make it very can large not a representative measure of spread Spread: Interquartile Range Lower quartile (01) : quarter of data one lies below Q , : 25th percentile Upper quartile (Q3) : 3/4 of data he below Q & : 75th percentile IQR = Q3-Q , FQR to & use describe terms of median spread when you give center in Lower IQR-values are less spread Higher IQR-values are more spread ↑· 5# Summary min max , , Q , Qz , mechan I · Boxplot 1) length of box spans from Q -Q , - P 2) Draw lines for Q , Q median 3) Connect to form E a box E - 4) Calculate the fences Fence : Q + 1 5/1QR) upper. lower fence : Q , -1 5. (IQR) data values outside of fences are outliers - D indicate on plot w/dots 5) draw from wiskars edges of box to smallest non-outliers largest a Cumulative Relative Frequency Plot (Ogives - A plot that displays Cumulative info frequency cotty- % or proportion of while Mechan t IQR go together If data unimodal somewhat is symmmetric ↳ mean a standard deviation Mean The point where the histogram balances - * = total/n = EX/n Mean Vs Median - Mechan is less influenced by skewness + outliers than the mean > - use medan for skewed distributions Standard Deviation goesoy mean s 2 sprt of variance large-lot of spread - data Distributions comparing What to tell when comparing Data Compare Similarities a differences in shape center a spread - Timepl individual values overtimea ↳ a measure of time is on X-axis = Timeo ·Histogris can see increasing Shape"Center spread - - , or decreasing over time (trends) Test 7Qs2MCQ 5 FRQ , Categorical Data Displays - Area Principle - Contingency Tables (1 Variables) - - Conditional Distributions Quantitative Data Displays - Stem histogram box plot plot dot plot - , , , Snape - -unimodal/bimodal/multimodal/uniform symmetry/Skewness - - outliers - Center - median - mean Spreach - - - IQR - Standard Deviation 5# summary - Compare distributions -

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