Dambudziko guru rine chekuita nemakodhi ezviverengero zvisingaite muPython nderekuti zvinogona kunetsa kunzwisisa nekududzira mhedzisiro. Python mutauro une simba, asi zvinogona kunetsa kuverenga nekunzwisisa kodhi inoshandiswa kune inferential statistics. Pamusoro pezvo, kune akawanda akasiyana mapakeji anowanikwa einferential manhamba muPython, izvo zvinogona kuita kuti zviome kusarudza iyo chaiyo yeimwe ongororo. Chekupedzisira, mamwe emapaketi aya anogona kunge asiri echizvino-zvino kana kuvimbika sevamwe, saka zvakakosha kuti utsvage usati waashandisa.
1. Chi-Square Test of Independence: from scipy.stats import chi2_contingency chi2, p, dof, expected = chi2_contingency(observed) 2. One-Way ANOVA: from scipy import stats F, p = stats.f_oneway(sample1, sample2, sample3) 3. Pearson’s Correlation Coefficient: from scipy.stats import pearsonr corr, _ = pearsonr(x, y)
Mutsara wekutanga: Mutsetse uyu unopinza chi1_contingency basa kubva muraibhurari ye scipy.stats, uye wobva waishandisa kuverenga chi-square test yekuzvimirira pane yakaonekwa data. Mhedzisiro yebvunzo iyi inochengetwa mumhando chi2, p, dof, uye zvinotarisirwa.
Mutsara wechi2: Mutsara uyu unopinza basa f_oneway kubva kuraibhurari ye scipy, uye wobva waishandisa kuverenga nzira imwe chete ANOVA pamasampuli matatu (sample1, sample2, sample3). Mhedzisiro yebvunzo iyi inochengetwa mumhando F uye p.
Mutsara wechitatu: Mutsetse uyu unopinza basa re pearsonr kubva muraibhurari ye scipy.stats, wobva warishandisa kuverenga Pearson's coefficient coefficient pakati pezvinhu zviviri (x na y). Mhedzisiro yebvunzo iyi inochengetwa mumhando dzecorr uye _.
Chii chinonzi inferential statistics
Inferential statistics ibazi rezviverengero rinoshandisa data kubva kumuenzaniso kuita fungidziro kana zvirevo pamusoro pehuwandu. Zvinosanganisira kutora mhedziso nezvehuwandu zvichienderana nedata rakaunganidzwa kubva kumuenzaniso. MuPython, inferential statistics inogona kushandiswa kutora mhedziso uye kufanotaura nekushandisa akasiyana matekiniki akadai sekuyedzwa kwekufungidzira, ongororo yekubatanidza, kuongorora kudzoreredza, nezvimwe. Matekiniki aya anotibvumira kutora miono ine musoro kubva kudata redu uye kutibatsira kuita sarudzo dziri nani.
Mhando dzeinferential statistics
MuPython, kune akati wandei marudzi einferential manhamba anogona kushandiswa kuongorora data. Izvi zvinosanganisira t-bvunzo, ANOVA, chi-square bvunzo, correlation bvunzo, uye regression ongororo. T-bvunzo inoshandiswa kuenzanisa nzira dzemapoka maviri kana anopfuura e data. ANOVA inoshandiswa kuenzanisa nzira dzemapoka akawanda e data. Chi-square bvunzo dzinoshandiswa kuyedza hukama pakati pemhando dzakasiyana. Correlation bvunzo inoyera simba uye gwara rehukama hwemutsara pakati pemhando mbiri. Chekupedzisira, regression ongororo inoshandiswa kufanotaura kuchinjika kunotsamira kubva kune imwe kana akawanda akazvimirira akasiyana.
Unonyora sei inferential statistics
Inferential statistics ibazi rezviverengero rinoshandisa data kubva kumuenzaniso kuita fungidziro pamusoro pehuwandu hwakatorwa sample. MuPython, inferential manhamba anogona kuitwa pachishandiswa maraibhurari akasiyana seSciPy, StatsModels, uye NumPy.
Kuti uite zviverengero zvisingaite muPython, unozofanirwa kutanga wapinza maraibhurari anodiwa wobva washandisa mabasa akadai serevo (), median (), mode(), musiyano(), standard deviation(), t-test(), chi -square test() etc. Semuyenzaniso, kana waida kuverenga zvinoreva dataset rakapihwa, waigona kushandisa zvinoreva () basa kubva paNumPy:
import numpy se np
data = [1,2,3,4]
kureva_value = np.mean(data)
dhinda(kureva_kukosha) # Kubuda: 2.5
