Python ƒe akpawo tsɔtsɔ sɔ kple wo nɔewo hena A/B dodokpɔ me dzodzro (kple kɔda ƒe kpɔɖeŋuwo) .

Ŋgɔdonya: Ŋusẽ kple Mɔ̃ siwo le A/B Dodokpɔ me

A/B dodokpɔ nye nyametsotsowɔwɔ si wotu ɖe nyatakakawo dzi ƒe dzogoedzikpe, si naa asitsahabɔbɔwo te ŋu yia ŋgɔ wu dɔgbo ƒe seselelãmewo eye wowɔa tiatia siwo woawɔ le aɖaŋu me siwo ŋu kpeɖodzi siwo wokpɔ le nuteƒekpɔkpɔ me da asi ɖo. Eɖanye be èle nyatakakadzraɖoƒe ƒe ɖoɖo yeye aɖe dom kpɔ o, asitsatsa ƒe e-mail ƒe nyati aɖe, alo nɔnɔme aɖe si le wò adzɔnuwo me dom kpɔ o, A/B dodokpɔ si wowɔ nyuie ate ŋu akpɔ ŋusẽ ɖe xexlẽdzesi veviwo dzi vevie. Gake mɔzɔzɔa tso dodokpɔ ŋuti nyatakaka xoxowo dzi va ɖo nyataƒoƒo si me kɔ, si sɔ le akɔntabubu nu dzi ate ŋu ayɔ fũ kple nusiwo me kɔ. Afi siae Python, kple eƒe lãwo ƒe agbenɔnɔ ƒe ɖoɖo si me nyatakakawo ŋuti dzɔdzɔmeŋutinunya ƒe agbalẽdzraɖoƒewo le la, va zua dɔwɔnu vevi aɖe le. Enaa ŋusẽ numekulawo kple mɔ̃ɖaŋudɔwɔlawo be woaku nu me tso emetsonuwo ŋu tsitotsito, gake esi wònye be agbalẽvi sẽŋu geɖe li ta la, esi sɔ tiatia ate ŋu anye kuxi. Le nyati sia me la, míatsɔ Python ƒe agbalẽvi xɔŋkɔ aɖewo asɔ kple wo nɔewo hena A/B dodokpɔ me dzodzro, bliboe kple kɔda ƒe kpɔɖeŋuwo be woafia mɔ wò dɔwɔwɔ.

Scipy.stats: Gɔmeɖoanyi ƒe Mɔnu

Na amesiwo dze egɔme kple A/B dodokpɔ alo hiã na egbɔkpɔnu si le bɔbɔe, si me naneke mele o la, `scipy.stats` module nye tiatia si woayi. Enaa akɔntabubudɔ vevi siwo hiã na nukpɔsusuwo dodokpɔ. Dɔwɔwɔ ƒe ɖoɖo si bɔ la bia be woazã dodokpɔ abe Student ƒe t-dodokpɔ alo Chi-squared dodokpɔ ene atsɔ abu p-xexlẽme. Togbɔ be mɔnu sia te ŋu trɔna bɔbɔe ŋutɔ hã la, ebia be nàtsɔ asi akpɔ nyatakakawo dzadzraɖo gbɔ, abu kakaɖedzi ƒe dometsotsowo, eye nàɖe emetsonu xoxoa gɔme. Enye mɔnu sẽŋu aɖe gake wotsɔ asi wɔe.

"Dze egɔme kple `scipy.stats` zi akɔntabubu siwo le ete la gɔmesese deto dzi, si xɔ asi ŋutɔ na nyatakakaŋutinunyala ɖesiaɖe."

T-dodokpɔ si tsɔa tɔtrɔ ƒe agbɔsɔsɔme sɔna kple ƒuƒoƒo eve dome ƒe kpɔɖeŋu aɖee nye esi:

````python ƒe ʋuʋudedi tso scipy import stats me import numpy abe np ene # Kpɔɖeŋu nyatakakawo: 1 na tɔtrɔ, 0 na tɔtrɔ aɖeke o group_a = np.array ([1, 0, 1, 1, 0, 0, 1, 0, 0, 1]) # 4 tɔtrɔwo le 10 me group_b = np.array ([1, 1, 0, 1, 1, 1, 0, 1, 1, 0]) # 7 tɔtrɔwo le 10 me t_stat, p_value = stats.ttest_ind (ƒuƒoƒo_a, ƒuƒoƒo_b) print (f "T-akɔntabubu: {t_stat:.4f}, P-asixɔxɔ: {p_asixɔxɔ:.4f}") ne p_asixɔxɔ < 0.05: print("Wokpɔ vovototo si ɖe dzesi le akɔntabubu nu!") ne menye nenema o la: print("Womekpɔ vovototo aɖeke si ɖe dzesi le akɔntabubu nu o.") ```

Akɔntabubu ƒe Kpɔɖeŋuwo: Akɔntabubu ƒe Kpɔɖeŋu si me kɔ

Ne èhiã dodokpɔ tsitotsito kple dodokpɔ tɔxɛwo la, `statsmodels` nye mɔnu bubu si de ŋgɔ wu. Wotrɔ asi le eŋu koŋ na akɔntabubu ƒe kpɔɖeŋuwɔwɔ eye wònaa nyatakaka si me nyatakaka geɖe le wu si wotrɔ asi le na A/B dodokpɔ ƒe nɔnɔmewo. Le agbɔsɔsɔme ŋuti nyatakakawo (abe tɔtrɔ ƒe agbɔsɔsɔme ene), àteŋu azã `proportions_ztest` dɔwɔwɔ, si kpɔa dodokpɔ ƒe akɔntabubu, p-asixɔxɔ, kple kakaɖedzi dometsotsowo ƒe akɔntabubu gbɔ le eɖokui si. Esia na be kɔda la le dzadzɛ eye emetsonuwo gɔmeɖeɖe le bɔbɔe ne wotsɔe sɔ kple `scipy.stats` mɔnu vevi la.

````python ƒe ʋuʋudedi tsɔ statsmodels.stats.proportion vɛ abe agbɔsɔsɔme ene # Dzidzedzekpɔkpɔwo ƒe xexlẽme kple kpɔɖeŋu ƒe lolome zazã dzidzedzekpɔkpɔwo = [40, 55] # Dzimetɔtrɔ ƒe xexlẽme le Ƒuƒoƒo A kple B me nobs = [100, 100] # Zãla siwo katã le Ƒuƒoƒo A kple B me z_stat, p_value = agbɔsɔsɔme.dzidzeme_ztest (dzidzedzekpɔkpɔwo, nobs) print (f "Z-akɔntabubu: {z_stat:.4f}, P-asixɔxɔ: {p_asixɔxɔ:.4f}") ```

Agbalẽdzraɖoƒe Tɔxɛwo: Mɔ Blɔɖetɔ Kekeake si Yi Nu Gɔmesese Gbɔ

Le ƒuƒoƒo siwo wɔa A/B dodokpɔwo enuenu gome la, agbalẽdzraɖoƒe tɔxɛwo ate ŋu ana numekukua nawɔ kabakaba ŋutɔ. Packages abe `Pingouin` alo `ab_testing` naa dɔwɔwɔ deŋgɔ siwo ɖea dodokpɔa ƒe kpukpui blibo ɖe go le kɔda ƒe fli ɖeka me. Zi geɖe la, kpukpui siawo lɔ p-xexlẽme, kakaɖedzi ƒe dometsotsowo, Bayesian ƒe nusiwo ate ŋu adzɔ, kple ŋusẽkpɔɖeamedzi ƒe lolome ƒe akɔntabubu ɖe eme, si naa dodokpɔa me tsonu ƒe nukpɔsusu blibo. Esia nyo ŋutɔ na numekuku tsɔtsɔ de pɔmpi alo dashboard siwo wowɔna le wo ɖokui si me.

ƒe nyawo
• Scipy.stats: Gɔmeɖoanyi, si te ŋu trɔna bɔbɔe, gake asi.
• Akɔntabubu ƒe kpɔɖeŋuwo: Nusiwo do tso eme tsitotsito, nyo ŋutɔ na akɔntabubu ŋuti dzadzɛnyenyetɔwo.
• Pingouin: Akɔntabubu kpui siwo sɔ na zazã, siwo me kɔ.
• ab_testing: Wotrɔ asi le eŋu koŋ na A/B dodokpɔwo, zi geɖe la, Bayesian mɔnuwo hã nɔa eme.

Kpɔɖeŋu si zãa nususugblɔ ƒe `ab_testing` agbalẽdzraɖoƒe:

````python ƒe ʋuʋudedi # Nukpɔsusu ƒe kpɔɖeŋu na agbalẽdzraɖoƒe tɔxɛ aɖe tso ab_testing import analyze_ab_dodokpɔ emetsonuwo = analyze_ab_dodokpɔ ( ƒuƒoƒo_a_trɔtrɔwo=40, . ƒuƒoƒo_a_wo katã=100, . ƒuƒoƒo_b_trɔtrɔwo=55, . ƒuƒoƒo_b_katã = 100 ) . print (emetsonuwo.kpukpui ()) ```

Kukuɖenuŋu ƒe tsɔtsɔ de Wò Asitsatsa ƒe Dɔwɔɖoɖo me

Package nyuitɔ tiatia nye aʋa la ƒe akpa aɖe ko. Asixɔxɔ vavãtɔ si le A/B dodokpɔ ŋu dzena ne wotsɔ gɔmesesewo de wò asitsadɔwo me nyuie. Afi siae modular business OS abe Mewayz ene nyo wu. Le esi teƒe be numekuku ŋɔŋlɔdzesiwo naɖe ɖe vovo le Jupyter nuŋlɔɖigbalẽ me la, Mewayz ɖea mɔ na wò be nàtsɔ numekuku ƒe dɔwɔwɔ bliboa ade wò asitsatsa ƒe ɖoɖowo me tẽ. Àteŋu awɔ module si ahe dodokpɔ ŋuti nyatakakawo, awɔ numekukua to Python package si nèlɔ̃ zazã me, eye wòayɔ dashboard si woateŋu akpɔ na ƒuƒoƒo bliboa le eɖokui si. Esia naa dekɔnu si nye dodokpɔ siwo wotu ɖe nyatakakawo dzi, si kpɔa egbɔ be wotsɔ kpeɖodzi siwo ŋu kakaɖedzi le naa nyametsotso ɖesiaɖe, tso adzɔnuwo wɔwɔ dzi va ɖo asitsatsa ƒe aʋawɔnyawo dzi. To Mewayz ƒe modularity zazã me la, àteŋu atu A/B dodokpɔ ƒe ɖoɖo sesẽ si ŋu ŋusẽ le eye woateŋu akpɔe.

Nyabiase Siwo Wobiana Enuenu

Ŋgɔdonya: Ŋusẽ kple Mɔ̃ siwo le A/B Dodokpɔ me

A/B dodokpɔ nye nyametsotsowɔwɔ si wotu ɖe nyatakakawo dzi ƒe dzogoedzikpe, si naa asitsahabɔbɔwo te ŋu yia ŋgɔ wu dɔgbo ƒe seselelãmewo eye wowɔa tiatia siwo woawɔ le aɖaŋu me siwo ŋu kpeɖodzi siwo wokpɔ le nuteƒekpɔkpɔ me da asi ɖo. Eɖanye be èle nyatakakadzraɖoƒe ƒe ɖoɖo yeye aɖe dom kpɔ o, asitsatsa ƒe e-mail ƒe nyati aɖe, alo nɔnɔme aɖe si le wò adzɔnuwo me dom kpɔ o, A/B dodokpɔ si wowɔ nyuie ate ŋu akpɔ ŋusẽ ɖe xexlẽdzesi veviwo dzi vevie. Gake mɔzɔzɔa tso dodokpɔ ŋuti nyatakaka xoxowo dzi va ɖo nyataƒoƒo si me kɔ, si sɔ le akɔntabubu nu dzi ate ŋu ayɔ fũ kple nusiwo me kɔ. Afi siae Python, kple eƒe lãwo ƒe agbenɔnɔ ƒe ɖoɖo si me nyatakakawo ŋuti dzɔdzɔmeŋutinunya ƒe agbalẽdzraɖoƒewo le la, va zua dɔwɔnu vevi aɖe le. Enaa ŋusẽ numekulawo kple mɔ̃ɖaŋudɔwɔlawo be woaku nu me tso emetsonuwo ŋu tsitotsito, gake esi wònye be agbalẽvi sẽŋu geɖe li ta la, esi sɔ tiatia ate ŋu anye kuxi. Le nyati sia me la, míatsɔ Python ƒe agbalẽvi xɔŋkɔ aɖewo asɔ kple wo nɔewo hena A/B dodokpɔ me dzodzro, bliboe kple kɔda ƒe kpɔɖeŋuwo be woafia mɔ wò dɔwɔwɔ.

Scipy.stats: Gɔmeɖoanyi ƒe Mɔnu

Na amesiwo dze egɔme kple A/B dodokpɔ alo hiã na egbɔkpɔnu si le bɔbɔe, si me naneke mele o la, `scipy.stats` module nye tiatia si woayi. Enaa akɔntabubudɔ vevi siwo hiã na nukpɔsusuwo dodokpɔ. Dɔwɔwɔ ƒe ɖoɖo si bɔ la bia be woazã dodokpɔ abe Student ƒe t-dodokpɔ alo Chi-squared dodokpɔ ene atsɔ abu p-xexlẽme. Togbɔ be mɔnu sia te ŋu trɔna bɔbɔe ŋutɔ hã la, ebia be nàtsɔ asi akpɔ nyatakakawo dzadzraɖo gbɔ, abu kakaɖedzi ƒe dometsotsowo, eye nàɖe emetsonu xoxoa gɔme. Enye mɔnu sẽŋu aɖe gake wotsɔ asi wɔe.

Akɔntabubu ƒe Kpɔɖeŋuwo: Akɔntabubu ƒe Kpɔɖeŋu si me kɔ

Ne èhiã dodokpɔ tsitotsito kple dodokpɔ tɔxɛwo la, `statsmodels` nye mɔnu bubu si de ŋgɔ wu. Wotrɔ asi le eŋu koŋ na akɔntabubu ƒe kpɔɖeŋuwɔwɔ eye wònaa nyatakaka si me nyatakaka geɖe le wu si wotrɔ asi le na A/B dodokpɔ ƒe nɔnɔmewo. Le agbɔsɔsɔme ŋuti nyatakakawo (abe tɔtrɔ ƒe agbɔsɔsɔme ene), àteŋu azã `proportions_ztest` dɔwɔwɔ, si kpɔa dodokpɔ ƒe akɔntabubu, p-asixɔxɔ, kple kakaɖedzi dometsotsowo ƒe akɔntabubu gbɔ le eɖokui si. Esia na be kɔda la le dzadzɛ eye emetsonuwo gɔmeɖeɖe le bɔbɔe ne wotsɔe sɔ kple `scipy.stats` mɔnu vevi la.

Agbalẽdzraɖoƒe Tɔxɛwo: Mɔ Blɔɖetɔ kekeake si Yi Nugɔmesese Gbɔ

Le ƒuƒoƒo siwo wɔa A/B dodokpɔwo enuenu gome la, agbalẽdzraɖoƒe tɔxɛwo ate ŋu ana numekukua nawɔ kabakaba ŋutɔ. Packages abe `Pingouin` alo `ab_testing` naa dɔwɔwɔ deŋgɔ siwo ɖea dodokpɔa ƒe kpukpui blibo ɖe go le kɔda ƒe fli ɖeka me. Zi geɖe la, kpukpui siawo lɔ p-xexlẽme, kakaɖedzi ƒe dometsotsowo, Bayesian ƒe nusiwo ate ŋu adzɔ, kple ŋusẽkpɔɖeamedzi ƒe lolome ƒe akɔntabubu ɖe eme, si naa dodokpɔa me tsonu ƒe nukpɔsusu blibo. Esia nyo ŋutɔ na numekuku tsɔtsɔ de pɔmpi alo dashboard siwo wowɔna le wo ɖokui si me.

Kukuɖenuŋu ƒe tsɔtsɔ de Wò Asitsatsa ƒe Dɔwɔɖoɖo me

Package nyuitɔ tiatia nye aʋa la ƒe akpa aɖe ko. Asixɔxɔ vavãtɔ si le A/B dodokpɔ ŋu dzena ne wotsɔ gɔmesesewo de wò asitsadɔwo me nyuie. Afi siae modular business OS abe Mewayz ene nyo wu. Le esi teƒe be numekuku ŋɔŋlɔdzesiwo naɖe ɖe vovo le Jupyter nuŋlɔɖigbalẽ me la, Mewayz ɖea mɔ na wò be nàtsɔ numekuku ƒe dɔwɔwɔ bliboa ade wò asitsatsa ƒe ɖoɖowo me tẽ. Àteŋu awɔ module si ahe dodokpɔ ŋuti nyatakakawo, awɔ numekukua to Python package si nèlɔ̃ zazã me, eye wòayɔ dashboard si woateŋu akpɔ na ƒuƒoƒo bliboa le eɖokui si. Esia naa dekɔnu si nye dodokpɔ siwo wotu ɖe nyatakakawo dzi, si kpɔa egbɔ be wotsɔ kpeɖodzi siwo ŋu kakaɖedzi le naa nyametsotso ɖesiaɖe, tso adzɔnuwo wɔwɔ dzi va ɖo asitsatsa ƒe aʋawɔnyawo dzi. To Mewayz ƒe modularity zazã me la, àteŋu atu A/B dodokpɔ ƒe ɖoɖo sesẽ si ŋu ŋusẽ le eye woateŋu akpɔe.