Grunnprinsipper ved bygging av et datamateriale

Jun 12, 2012Download as pptx, pdf

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Grunnprinsipper ved bygging
av et datamateriale

Viktige begreper
 Enheter: de objektene at datamateriale innholder
informasjon om (eks. personer, brukere, skoleelever,
foreldre, kommuner, land osv)

 Variabler: kjennetegn eller opplysninger om disse
enhetene (eks. kjønn, påstand, holdning, geografisk
beliggenhet osv)

 Kategorier/verdier: hver variabel deles inn i
kategorier eller verdier (eks. mann, kvinne, helt enig,
ganske enig, helt uenig osv)

Huskeregel
 Enheter: Hvem er det vi vil vite noe om?

 Variabler: Hva vil vi vite om dem?

 Verdiene: Svaralternativene på variablene

Ulike typer variabler
 Ikke-metriske variabler: De forskjellige verdiene
består i utgangspunktet ikke av tall (eks. kjønn,
nasjonalitet)

 Metriske variabler: Variabler som i utgangspunktet
består av tall. De kan måle størrelser, mengder,
prosentandeler osv (eks. alder)

Klassifisering og koding
For at et materiale skal kunne legges inn i et
statistikkprogram, må følgende krav være oppfylt:

1. Informasjonen må kunne ordnes i entydige variabler
2. Hver variabel må ha gyldige verdier (uttømmende,
gjensidig utelukkende)

Ulike typer spørsmål
 Åpne spørsmål har ingen svaralternativer og svarene
må klassifiseres etterpå (Stor jobb!)

 Lukkede spørsmål:
a) ett avkryssingsalternativ
b) flere avkryssingsalternativer (multirespons)

VIKTIG:
Test ut spørreskjemaet på en ”prøvekanin” for å sjekke
om de oppfatter spørsmålene på samme måte som deg!

Noen enveis analysemetoder
 Ikke-metriske variabler: frekvens teller opp hvor
mange av enhetene som har de ulike verdiene på en
variabel
Aktuelle statistiske mål er modus og median

 Metriske variabler: enveis deskriptiv gir et
oppsummerende mål som forteller hvordan
fordelingen ser ut på en variabel (eks. en kurve som viser
aldersfordelingen)

 Aktuelle statistiske mål er modus, median,
gjennomsnitt, standardavvik

Noen toveis analysemetoder
Toveis analyser brukes for å studere sammenhenger
eller samvariasjon mellom to variabler

 Krysstabell: Brukes for å studere sammenhenger
mellom to ikke-metriske variabler
Den variabelen som påvirker kalles uavhengig variabel
Den variabelen som blir påvirket kalles avhengig
variabel

Årsakssammenheng
Uavhengig variabel: Avhengig variabel:
Kjønn  Lesevaner

Variabelen kjønn påvirker variabelen lesevaner.

Tips: Den uavhengige (den påvirkende) variabelen
kommer først i tid.

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Grunnprinsipper ved bygging av et datamateriale

1. Grunnprinsipper ved bygging av et datamateriale

2. Viktige begreper  Enheter: de objektene at datamateriale innholder informasjon om (eks. personer, brukere, skoleelever, foreldre, kommuner, land osv)  Variabler: kjennetegn eller opplysninger om disse enhetene (eks. kjønn, påstand, holdning, geografisk beliggenhet osv)  Kategorier/verdier: hver variabel deles inn i kategorier eller verdier (eks. mann, kvinne, helt enig, ganske enig, helt uenig osv)

3. Huskeregel  Enheter: Hvem er det vi vil vite noe om?  Variabler: Hva vil vi vite om dem?  Verdiene: Svaralternativene på variablene

4. Ulike typer variabler  Ikke-metriske variabler: De forskjellige verdiene består i utgangspunktet ikke av tall (eks. kjønn, nasjonalitet)  Metriske variabler: Variabler som i utgangspunktet består av tall. De kan måle størrelser, mengder, prosentandeler osv (eks. alder)

5. Klassifisering og koding For at et materiale skal kunne legges inn i et statistikkprogram, må følgende krav være oppfylt: 1. Informasjonen må kunne ordnes i entydige variabler 2. Hver variabel må ha gyldige verdier (uttømmende, gjensidig utelukkende)

6. Ulike typer spørsmål  Åpne spørsmål har ingen svaralternativer og svarene må klassifiseres etterpå (Stor jobb!)  Lukkede spørsmål: a) ett avkryssingsalternativ b) flere avkryssingsalternativer (multirespons) VIKTIG: Test ut spørreskjemaet på en ”prøvekanin” for å sjekke om de oppfatter spørsmålene på samme måte som deg!

7. Noen enveis analysemetoder  Ikke-metriske variabler: frekvens teller opp hvor mange av enhetene som har de ulike verdiene på en variabel Aktuelle statistiske mål er modus og median  Metriske variabler: enveis deskriptiv gir et oppsummerende mål som forteller hvordan fordelingen ser ut på en variabel (eks. en kurve som viser aldersfordelingen)  Aktuelle statistiske mål er modus, median, gjennomsnitt, standardavvik

8. Noen toveis analysemetoder Toveis analyser brukes for å studere sammenhenger eller samvariasjon mellom to variabler  Krysstabell: Brukes for å studere sammenhenger mellom to ikke-metriske variabler Den variabelen som påvirker kalles uavhengig variabel Den variabelen som blir påvirket kalles avhengig variabel

9. Årsakssammenheng Uavhengig variabel: Avhengig variabel: Kjønn  Lesevaner Variabelen kjønn påvirker variabelen lesevaner. Tips: Den uavhengige (den påvirkende) variabelen kommer først i tid.

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Grunnprinsipper ved bygging av et datamateriale

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Grunnprinsipper ved bygging av et datamateriale