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MATH 1150, Study Guide

by: Nicole Hampton

MATH 1150, Study Guide MATH 1150

Nicole Hampton

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Chapters 1-3 Study Guide Includes a graph quiz to practice with. Test 1
Intro to Statistics
Chao Gu
Study Guide
Math, Statistics, intro to statistics, Exam 1
50 ?




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This 9 page Study Guide was uploaded by Nicole Hampton on Tuesday September 27, 2016. The Study Guide belongs to MATH 1150 at Bowling Green State University taught by Chao Gu in Fall 2016. Since its upload, it has received 17 views. For similar materials see Intro to Statistics in Math at Bowling Green State University.


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Date Created: 09/27/16
Test 1 Study Guide Chapter 1 1.1 Statistics ​- the study of data, organizing/collecting data to be measured Variation​ - differences of changes in an item Data​ - observation that are recorded 1.2 Variable​ - characteristic of people or things var/i/able -> measurements that vary Sample​ - a subset of population Population​ - a collection of all data samples Types: Numerical Categorical -coding categorical data is matching answers with a number -ex. No=0, Yes=1 Stacked data​ - stored in a spreadsheet format, each row has MULTIPLE variables -ex. gender height weight 1 F 65 120 2 M 70 140 3 F 59 115 Unstacked data​ - stored so each column only shows ONE or TWO variables -ex. Male Height Female Height 70 65 - 59 1.3 -Raw data is messy and hard to work with -Organizing it helps to see patterns Two Way Tables​ - shows how many times each combination of categories can occur Frequency​ - the number of times the value is observed in the data set 1.4 Treatment variable​ - whether or not a specific treatment is used -shows which group an individual is in Outcome/Response variable​ - the result you get from the treatment Establishing causality​ - shows the outcome is affected by certain treatment -treatment group -control group Anecdote​ - story of a single individual’s own experience, NOT a general statement Experiment ​- placing participants in two groups and recording differences (treatment or control group) *people are placed Observational study​ - uses already created groups to record differences (treatment of control group) *people choose -Association DOES NOT mean causation Confounding var​iable​ - characteristics other than the treatment that cause​ both outcomes -ex. Online homework <----> grades -study hours -learning environment -foundation ​ Placebo effect ​- reacting to being​ old you had the treatment when it was not given Blind Study​ - participants do not know who is receiving the treatment Double Blind Study​ - participants AND administrators do not know who is receiving the treatment -Random assignment is the least biased STANDARD EXPERIMENT: -large sample sizes -double blind study -controlled and randomized -placebo (if appropriate) Chapter 2 2.1 Distribution​ - describes values, frequencies and shape of data -most important tool for organizing data Numerical Distribution: Shape ---> what’s it look like Center ---> typical value Variability ---> horizontal spread Frequency Table​ - lists all data values with counts -Picture displays helps us to see patterns Dot Plots​ - a chart that contains a dot for each data value Shows individual data values Not as common as histograms Easy to spot outliers Not great for a lot of individual Describes distribution visually values Histograms​ - group data in ​bins -consecutive bins touch -bin width can’t be too large or you’ll lose details Frequency Histograms​: -horizontal axis is NUMERICAL -vertical axis is FREQUENCY of data -easy to visualize distribution Good for large data sets Individual data values are not Helps focus on the general shape of the data visible (lost) Easy to spot outliers Distribution shape is affected by the change in bin width Relative Frequency Histogram​: -shows numerical and proportions -vertical axis shows relative frequencies (percents) -horizontal axis shows numerical data Stemplot​ - aka Stem and Leaf plots -shows all individual data -useful when technology is NOT available or when data set is smaller -leaf unit is what the Leaf numbers represent -ex. Leaf unit = 1 (ones) l (tens) 7 l 589 (75, 78, 79) -Stems (columns) need to be in increasing order -Leaf (rows of the number) need to be in order of observation 2.2 Aspects of Distribution: ● Shape ○ Symmetry ○ Bumps and modes ○ Other features ● Center ○ Typical value ● Spread ○ Data close of spread out ○ Look at horizontal (<--->) spread NOT vertical distances in heights of bars Skewed right -​ the “tail” end of data, the smaller values, are to the right Skewed left​ - the “tail” end of data, the smaller values, are to the left Symmetric Distributions ​- same mirror image to the left and right hand sides Unimodal Distributions​ - ONE mound Bimodal Distributions​ - TWO mounds Multimodal Distributions ​ THREE + mounds Bell Shaped Distributions​ - symmetric and unimodal Outliers ​- data values that are much larger or much smaller than the rest ​ -High variability = high sd -Low variability = low sd IQR ​- Inter Quartile Range IQR = Q3 - Q1 *single number answer Symmetric​ - Mean Standard Deviation Skewed​ - Median (sort first) IQR -Median is NOT affected by outliers, mean is. Graph Test Word Bank: Two-Way tables Dot Plots Stem Plots Histogram Bar Chart Pie Chart Pareto Chart Fill out below which word in the word bank you think goes with which graph/chart. 1) _____________________ 2) ________________________ 3) ____________________ 4) _________________________ 5) ________________________ 6) _______________________ 7) ________________________


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