Sannolikhet och statistik
Kapitel 5 handlar om Sannolikhet och statistik och består av nio delar (en del har teori, exempel och uppgifter).
Engels litteratur
OpenStax College: Introductory Statistics
5.1 Hur stor är chansen?
Intro
Khan Academy om Probability
Här har jag börjat skriva undertexter (subtitles) på svenska. Det är enkelt, bara att skaffa ett konto på Universal Subtitles och sätta igång. Vi kommer att göra övningar på detta så småningom, där ni får en film var att översätta.
Sidorna 244-248
fre - hemdiagnos denna fredag.
Definition:
Sannolikheten för en händelse = antalet gynnsamma utfall / antal möjliga utfall
med P(A) menas sannolikheten för att händelse A ska inträffa. A kan bestå av flera händelser, exempel vis att slå över tre på en tärning.
P(A eller B) = P(A) + P(B)
5.2 Oberoende händelser
Sidorna 249-251
fre
exempel 1, sid 249
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Kolla gärna Mikael Bondestam som förklarar kast med två tärningar = sannolikhet vid oberoende händelser:
Här kommer en bild som är lämplig att projicera och sedan rita på om man diskuterar sannolikheter vid två tärningsslag:
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Khan Academy
Däremot får alla gå in en kort stund på KhanAcademy på slutet av lektionen. Alla ska välja mig som coach så jag kan se hur det går. När du gör övningarna kan du klicka på Add coach längst ned på sidan. Gör det och adda mig.
Mitt ID är hakan.elderstig@gmail.com
5.3 Händelser i flera steg
Sidorna 252-255
må
Khan om oberoende händelser i flera steg:
Sedan en kul grej bara.
Rulla tärning från http://www.geogebratube.org/student/m712:
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Mikael Bondestam om träddiagram för händelser i flera steg:
Beroende händelser i flera steg, 256-258
ti
MB
Komplementhändelse, 259-260
ti
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Repetition inför provet
onsdag
Några lösningar till uppgifter vi gjorde på sista lektionen.
Khan Academy
Veckodiagnos 10
Detta är en lösning till uppgift 4 på veckodiagnos 10.
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Prov kapitel fyra samt mindre delar av 3 och 5
fredag
Provgränser
- Betyg E krävs 12 poäng
- Betyg C krävs dessutom 6 C-poäng
- Betyg A krävs 11 C-poäng och 3 A-poäng
5.4 Hur ofta inträffar en händelse?
Relativ frekvens
Sid 262-264
Intro från: GGBtube. DubFet textbelklicka för att se hela simuleringen.
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Sidorna 261-266
ons
Här är det lämpligt med några laborationer. Kanske olika uppgifter som gruperna får redovisa på nätet.
5.5 Statistik i samhälle och vetenskap
Sidorna 267-275
fre
Här kan man tänka sig att eleverna gör egna undersökningar och redovisar...
Medelvärde och standardavvikelse
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Fri att använda. Från GeoGebraInstitutet
Gapminder - övning
Här på sidan står det precis vad du ska göra denna lektion.
Samtidigt som vi kör muntliga nationella prov får ni elever uppgifter på Gapminder att jobba med.
Gapminder är en sajt med massor av statistik. Statistiken kommer från bra källor såsom FN. Hans Rosling är forskare och initiativtagare till Gapminder. Vi kan börja med att titta på en film där du får lära känna Hans Rosling lite närmare. Låt dig inte förledas av att han presenterar sitt budskap på ett lättfattligt sätt. han har massor av vetande bakom sitt budskap. Och han har prisats som en av de bästa talarna på TED.
Se Hans Rosling prata om den magiska tvättmaskinen
Det finns fler filmer med Hans Rosling på youtube eller på Gapminder men det hinner du inte nu.
Se istället denna film om befolkningstillväxten. En bra idé kan vara att någon visar den med projektorn.
Inlämningsuppgift
Nu ska du få öva dig själv.
- Du ska göra en introduktionsövning, klicka länken bara. Övningen är obligatorisk! Skriv svar på frågorna och mejla mig.
- Gapminder har du här
- Betyg: Godkänt på uppgiften får du om du har rimliga svar på minst sju frågor. För högre betyg krävs fler frågor och dessutom sådana svar att du visar att du behärskar det här.
Länkar till fler övningar:
- Så jobbar Nacka:
- Varifrån kommer maten?
- CO2 Den kan vi göra senare.
Film - undertexter
En tanke är att eleverna får en film var från Khan Academy och att de gör en översättning till svenska av den engelska undertexten.
Monty Hall
Introfilm:
Man borde kunna hitta en film där de öppnar dörra på nätet ...
Lös det teoretiskt eller leta rätt på en lösning på nätet.
Praktiskt experiment för att testa om det stämmer.
Redovisa
http://sv.wikipedia.org/wiki/Monty_Hall-problemet
En förklaring på nätet:
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laboration
http://www.grand-illusions.com/simulator/montysim.htm
5.6 Vilseledande statistik
Sidorna 276-277
må
5.7 Några statistiska lägesmått
Sidorna 278-282
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