learning objective: concept development: association between two categorical...

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NAME:___________________________ Math _______ , Period ____________ Mr. Rogove Date:__________ G8M6L10: Determining an Association Between Categorical Variables 1 Learning Objective: We will use row relative frequencies and column relative frequencies to determine if there is an association between two categorical variables. (G8M6L10) Concept Development: ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLES No Association Association This means that knowing the value of one variable provides no information about the value of the other variable. Knowing the value if one variable will provide information about the value of the other variable. If row relative frequencies (or column relative frequencies) are about the same for all of the rows (or columns), it is reasonable to say there is no association between the two variables. If the row relative frequencies (or column relative frequencies) are quite different for some of the rows (or columns), it is reasonable to say there is an association between the two variables. Example: Smartphone Use and Gender Use Smart phone Do not Use Smart phone Total Male 30 10 40 Female 45 15 60 Total 75 25 100 Example: Smartphone Use and Age Use Smart phone Do not Use Smart phone Total Under 40 years of age 45 5 50 40 years of age or older 30 20 50 Total 75 25 100

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Page 1: Learning Objective: Concept Development: ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLESmrrogove.weebly.com/uploads/4/3/0/0/43009773/g8m6l10... · 2018-09-11 · NAME:_____ Math _____

NAME:___________________________ Math_______,Period____________Mr.Rogove Date:__________

G8M6L10:DetermininganAssociationBetweenCategoricalVariables1

Learning Objective:Wewilluserowrelativefrequenciesandcolumnrelativefrequenciestodetermineifthereisanassociationbetweentwocategoricalvariables.(G8M6L10)Concept Development:

ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLES

No Association

Association

Thismeansthatknowingthevalueofonevariableprovidesnoinformationaboutthevalueoftheothervariable.

Knowingthevalueifonevariablewillprovideinformationaboutthevalueoftheothervariable.

Ifrowrelativefrequencies(orcolumnrelativefrequencies)areaboutthesameforalloftherows(orcolumns),itisreasonabletosaythereisnoassociationbetweenthetwovariables.

Iftherowrelativefrequencies(orcolumnrelativefrequencies)arequitedifferentforsomeoftherows(orcolumns),itisreasonabletosaythereisanassociationbetweenthetwovariables.

Example:SmartphoneUseandGender

UseSmartphone

DonotUseSmartphone

Total

Male

30 10 40

Female

45 15 60

Total

75 25 100

Example:SmartphoneUseandAge

UseSmartphone

DonotUseSmartphone

Total

Under40

yearsofage

45 5 50

40yearsofageorolder

30 20 50

Total75 25

100

Page 2: Learning Objective: Concept Development: ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLESmrrogove.weebly.com/uploads/4/3/0/0/43009773/g8m6l10... · 2018-09-11 · NAME:_____ Math _____

NAME:___________________________ Math_______,Period____________Mr.Rogove Date:__________

G8M6L10:DetermininganAssociationBetweenCategoricalVariables2

Guided Practice: StepsforDeterminingWhetherorNotThereisanAssociation1.CalculateRowRelativeFrequenciesandColumnRelativeFrequencies.2.Observetherowrelativefrequenciesforeachrow.Iftheyaresimilar,thereisnoassociation.3.Iftherearedifferences,statetheassociation.BelowisthedatacollectedfromoursurveythatcapturesgenderandourfavoritesporttoWATCH.

Baseball Basketball Football Hockey Soccer Grand Total

Female 10 8 7 3 12 40 Male 12 9 8 4 14 47 Grand Total 22 17 15 7 26 87 1.Fillinthetablebelowwiththerowrelativefrequenciesofeachsportwatchedforthemalerowandthefemalerow.

Baseball Basketball Football Hockey Soccer Grand Total

Female

1.00 Male

1.00

2.Isthereanassociationbetweengenderandthetypeofsportsweliketowatch?Explain.3.Fillinthetablebelowwiththecolumnrelativefrequenciesofeachgenderforthecolumnsrelatedtosportswewatch.

Baseball Basketball Football Hockey Soccer

Female Male Grand Total 1.00 1.00 1.00 1.00 1.00

4.Isthereanassociationbetweenthetypeofsportsweliketowatchandourgender?Explain.

Page 3: Learning Objective: Concept Development: ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLESmrrogove.weebly.com/uploads/4/3/0/0/43009773/g8m6l10... · 2018-09-11 · NAME:_____ Math _____

NAME:___________________________ Math_______,Period____________Mr.Rogove Date:__________

G8M6L10:DetermininganAssociationBetweenCategoricalVariables3

Belowisdatacollectedfromoursurveycapturinggenderandmoviepreference.1.Fillinthetablebelowthatsummarizesthedata.

• Therewere47boyssurveyedand87peopletotal

• 18boyslikedactionmovies

• 18girlslikedcomedies • 1boylikeddramas• 27studentsoveralllikedaction

movies• 33studentsoverallliked

comedies• 5studentsoveralllikeddramas

MoviePreference Action Comedy Drama Science

FictionTOTAL

Male

Female

TOTAL

2.IftherewereNOassociationbetweengenderandmoviepreference,wouldyouexpectmoreboysthangirlstolikedramasorlessboysthangirlstolikedramamovies?Explain.3.Fillinthetablebelowwithrowrelativefrequenciesofeachmoviepreferenceforbothgenders.

MoviePreference Action Comedy Drama Science

FictionTOTAL

Male Female

4.Ifyouweretoselectastudentatrandom,whatmovietypewouldyouthinktheyprefer?Explainwhyyoumadethischoice.

Page 4: Learning Objective: Concept Development: ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLESmrrogove.weebly.com/uploads/4/3/0/0/43009773/g8m6l10... · 2018-09-11 · NAME:_____ Math _____

NAME:___________________________ Math_______,Period____________Mr.Rogove Date:__________

G8M6L10:DetermininganAssociationBetweenCategoricalVariables4

5.Ifyoufoundoutthattherandomlyselectedstudentismale,wouldyoupredictthattheypreferredcomedies?Whyorwhynot?6.Doesknowingthegenderofastudenthelpyoumakepredictwhattypeofmovietheywilllike?7.Fillinthetablebelowwiththecolumnrelativefrequenciesofeachgenderforthemoviepreferences.

MoviePreference Action Comedy Drama Science

FictionMale Female TOTAL

8.Ifyouweretoselectastudentatrandomwouldyouexpectthemtobeaboyoragirl?Explainyouranswer.9.Ifyouweretoldthattherandomlyselectedstudentpreferredtowatchdramas,wouldyouthinktheywereaboy?10.Isthereanassociationbetweenthemovieswelikeandourgender?

Page 5: Learning Objective: Concept Development: ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLESmrrogove.weebly.com/uploads/4/3/0/0/43009773/g8m6l10... · 2018-09-11 · NAME:_____ Math _____

NAME:___________________________ Math_______,Period____________Mr.Rogove Date:__________

G8M6L10:DetermininganAssociationBetweenCategoricalVariables5

Independent Practice: Oursurveyalsolookedattheamountofsleepandhowstudentsgottoschool.Belowisthedatapresentedinatwowaytable.

AmountofSleep Lessthan6hours

Between6and8hours

Morethan8hours

Total

Modeoftransportation

Bike

0 9 12 21

Walk

0 9 9 18

Incar/scooter

3 20 25 48

Total

3 38 46 87

1.Iftherewasnoassociationbetweenhowstudentsgettoschoolandtheamountofsleeptheygeteachnight,wouldyouexpectthatmorebikeridersgetoverhoursofsleeporlessthan8hoursofsleep?Explainyouranswer.2.Drawarowrelativefrequencytableofeachofthenightlysleepamountsforthespecificmodesoftransportation.

AmountofSleep Lessthan6hours

Between6and8hours

Morethan8hours

Total

Modeoftransportation

Bike

Walk

Incar/scooter

3.Dothesedatasuggestanassociationbetweentheamountofsleepstudentsgetandhowtheygettoschool?Explainyouranswers.

Page 6: Learning Objective: Concept Development: ASSOCIATION BETWEEN TWO CATEGORICAL VARIABLESmrrogove.weebly.com/uploads/4/3/0/0/43009773/g8m6l10... · 2018-09-11 · NAME:_____ Math _____

NAME:___________________________ Math_______,Period____________Mr.Rogove Date:__________

G8M6L10:DetermininganAssociationBetweenCategoricalVariables6

Activating Prior Knowledge: Apregnantwomanwilloftenundergoanultrasoundtesttomonitorherbaby’shealth.Thesetestscanalsobeusedtopredictthegenderofthebaby,butit’snotalways100%accurate.Below,dataongenderpredictedbyultrasoundandactualgenderofthebabyfor1,000babiesissummarizedbelow.

PredictedGender

Female

Male

Actual

Gender Female

432 48

Male

130 3901.Whatistheproportionofthe1,000babieswhowerepredictedtobefemalebutwereactuallymale?2.Forthebabiespredictedtobefemale,whatproportionofthepredictionswerecorrect?3.Forthebabiespredictedtobemale,whatproportionofthepredictionswereincorrect?Closure: GiveexitTicketfromLesson14?(canbepage5ofthelessonhandout)Notes: Thisislesson14fromModule6Grade8