8/4/2019 Statistics Chapter 1 Study Guide

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Statistics Chapter 1 Study Guide How do we get good data?

*** You should have all of this information in your notes; however, because of the

missing books situation, I will give you a filled out study guide in class to supplement

class notes. In the future, I will only give you a blank version for you to study from with

your book ***

1.1 Where do data come from?

Statisticsthe art and science of dealing with data Individualsthe objects described by a set of data Variablesany characteristic of an individual

o Numericalvariables involving numberso Categoricalvariables that do not involve numbers

Observationalstudyobserves individuals and measures variables of interestbut does not attempt to influence the responses. The purpose is to describe

some group or situation Sample surveyssurvey some group of individuals by studying only some of its

members, selected not because they are of special interest, but because they

represent the larger group

Populationthe entire group of individuals about which we want information Samplea part of the population from which we actually collect information,

which is used to draw conclusions about the whole

Census - a sample survey that attempts to include the entire population in thesample

Experimentdeliberately imposes some treatment on individuals in order toobserve their responses. The purpose is to study whether the treatment causes a

change in the response

1.2 Measuring

Measurea property of a person or thing when we assign a number torepresent the property

Instrumentthing used to make a measurement Unitsused to record the measurement Variablenumerical variables are measureable Valida variable is a valid measure of a property if it is relevant or appropriate

as a representation of that property

Rate(fraction, proportion, or percent) rate at which something occurs is morevalid than a simple count of occurrences Countamount of times something occurs Predictive validitya measurement of a property has predictive validity if it can

be used to predict success on tasks that are related to the property measured

Biassystematically overstates or understates the true value of the property itmeasures

Reliableif random error is small

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Averagesare more reliable than counts Errors in measurementmeasured value = true value + bias + random error Random errora measurement process has random error if repeated

measurements on the same individual give different results

1.3 Do the numbers make sense? Percent change - amount of change x 100 = % Change

starting value

Missing informationimportant information left out of the report oradvertisement on purpose

Inconsistenciesnumbers that dont agree as they should Incorrect arithmeticcalculation errors Implausiblesurprisingly large or small numbers Too regular or agree too wellif the data agrees too perfectly, it might be

cause for suspicion

Hidden agendaif the data is trying to convince you to think a certain way