April 2025
Intermediate to advanced
324 pages
7h 15m
Italian
Content preview from Think Stats, 3a edizione
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Capitolo 14. Metodi analitici
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Questo libro si è concentrato su metodi di calcolo come la simulazione e il ricampionamento, ma alcuni dei problemi che abbiamo risolto hanno soluzioni analitiche che possono essere calcolate molto più velocemente.
Questo capitolo presenta alcuni di questi metodi e ne spiega il funzionamento. Alla fine del capitolo, fornisco suggerimenti per integrare i metodi computazionali e analitici per l'analisi dei dati.
Grafici di probabilità normale
Molti metodi analitici si basano sulle proprietà della distribuzione normale, per due motivi: le distribuzioni di molte misure nel mondo reale sono ben approssimate da distribuzioni normali e le distribuzioni normali hanno proprietà matematiche che le rendono utili per l'analisi.
Per dimostrare il primo punto, analizzeremo alcune misurazioni del set di dati dei pinguini. Poi esploreremo le proprietà matematiche della distribuzione normale. Le istruzioni per scaricare i dati si trovano nel quaderno di questo capitolo.
Possiamo leggere i dati in questo modo:
penguins=pd.read_csv("penguins_raw.csv")penguins.shape
(344, 17)
Il set di dati contiene le misurazioni di tre specie di pinguini. Per questo esempio, selezioneremo i pinguini Adélie:
adelie=penguins.query('Species.str.startswith("Adelie")').copy()len(adelie)
152
Per vedere se i pesi dei pinguini seguono una distribuzione ...
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