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by: Taylor Kim

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8

# Stats Study Guide Math 120 Statistics

Taylor Kim
Cal State Fullerton
GPA 4.0
Introduction to Probabilities
Gulhan Bourget

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Here's a study guide with r codes and examples of stuff that was covered in CH 1-3. There is examples and how to with sample data from the book.
COURSE
Introduction to Probabilities
PROF.
Gulhan Bourget
TYPE
Study Guide
PAGES
8
WORDS
CONCEPTS
Statistics, Math
KARMA
50 ?

## Popular in Math

This 8 page Study Guide was uploaded by Taylor Kim on Tuesday October 6, 2015. The Study Guide belongs to Math 120 Statistics at California State University - Fullerton taught by Gulhan Bourget in Summer 2015. Since its upload, it has received 76 views. For similar materials see Introduction to Probabilities in Math at California State University - Fullerton.

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## Reviews for Stats Study Guide

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Date Created: 10/06/15
Review 13 RCodes and More There are different types of graphical displays used in stats 1 Dotplot 2 Five Number Summary 3 Bargraph 4 pie chart 5 barplot aka histogram Review in Class 1052015 Using a Random Set of Dag use a set of random data you must write it as name of data set ccolumn abc d e f g for example I will call my data length 156790936785455878 and iwill write it in r script as lengthc156790936785455878 From there I will make different plots stem and leaf plot stemlength You should get The decimal point is 1 digits to the right of the 05 2 458 6778 8503 Table for length tablelength length 15 45 58 67 78 85 90 93 11121111 histength Hist gIram f length 3C Frequency 15 Ii D5 I I I I I I I1 ED 4 EU EU mi I Eli39lth Barplot totengthc156790936785455878 xabc391039392039393039394039 barplottotlength main39Length Histogram39xlab3910 20 30 4039colc39red3939bue39 Length HiEt gEr l Tll 3910 Eli 3Q 46 EC SC I I I iii 2E I Boxplot boxplotlength strength boxplotlength names 39Boxplot of Length39 coc39red39 maintitle quotBoxplot of Lengthquot Pie chart totengthc156790936785455878 colnamec391039392039393039394039395039 per100totengthsumtotength Iengthperpastecolname3939round per03939 pieper abesengthper mainquotLengthquot Length amn xn 431 15 FF EU 11 2 LEE 513111 4313 1U 14 3 1m 238 39 i itplat oi Length D m E my D 39339 Find the mean and standard deviation gt meanength 1 6644444 gt sdength 1 2478967 Find the zscore of 34 34meanIengthsdength 11308789 How to interpret the standard deviation 34 is 131 standard deviations below the mean if the zscore is positive its above the mean Now we are going to try to do these functions using a data set from the book Using httomathfacutvfuertonedumoriMath120Dataasciichuotimetxt This compares body weight and time it takes for college students to chug a beer plotWeightChugTime plotWeightChugTime mChugTimeWeight tabechugtime corWeightChugTime strchugtime withdata expressionchugtime plotWeightChugTime plotWeightChugTime mChugTimeWeight moutmChugTimeWeight summarymout Ei l Edit Weight 1 I IEi 39339 I ii ChugTime gt corWeight ChugTime 1 07878927 The correlation is a moderate negative linear relationship gt corWeight ChugTime 2 1 0620775 The correlation coefficient is 062 so the chugtime explains 62 of the variations between weight observed among men Call lmformula ChugTime Weight Coefficients Intercept Weight 1329750 004579 weight1329750004579chugtime Questions to think about when interpreting s0pe and y intercept how body weight affects change in chug time is there a difference in chug time due to body weight changing chug time does a change in body weight lead to a change in chug time chugtime 1329750004579 weight The b0 is 1329750 so that when weight is 0 the estimated chugtime is 13 seconds There is no meaningful interpretation For the sope004579 so for every pound increase in weight the chug time decreases by 004 seconds ChugTime CI

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