Python paket ahorow a wɔde toto ho ma A/B sɔhwɛ nhwehwɛmu (ne koodu nhwɛso ahorow) .

Nnianim: Tumi ne Afiri a ɛwɔ A/B Sɔhwɛ mu

A/B sɔhwɛ yɛ gyinaesi a wɔde data di dwuma no tweatibo, a ɛma nnwuma tumi kɔ akyiri sen gut nkate na wɔpaw akwan horow a adanse a wonya fi osuahu mu gyina akyi. Sɛ́ ebia woresɔ wɛbsaet nhyehyɛe foforo ahwɛ, aguadi email asɛmti, anaa ade bi a ɛwɔ wo nneɛma mu no, A/B sɔhwɛ a wɔayɛ no yiye betumi anya metrics atitiriw so nkɛntɛnso kɛse. Nanso, akwantu a efi sɔhwɛ ho nsɛm a wɔmfa nhyehyɛ mu so kɔ awiei a emu da hɔ na akontaabu mu nokware so no betumi ayɛ nea nsɛm a ɛyɛ den ahyɛ mu ma. Ɛha na Python a ɛwɔ abɔde a nkwa wom nhyehyɛe a ɛyɛ fɛ a ɛwɔ data nyansahu nhomakorabea ahorow no bɛyɛ adwinnade a ɛho nhia. Ɛma nhwehwɛmufo ne mfiridwumayɛfo tumi ma wɔhwehwɛ nea efi mu ba no mu yiye, nanso esiane sɛ nneɛma pii a tumi wom wɔ hɔ nti, nea ɛfata a wɔbɛpaw no betumi ayɛ asɛnnennen. Wɔ saa asɛm yi mu no, yɛde Python packages a agye din paa no bi bɛtoto ho ama A/B sɔhwɛ nhwehwɛmu, a edi mũ a code nhwɛsoɔ ka ho de akyerɛ wo dwumadie kwan.

Scipy.stats: Fapem kwan a wɔfa so yɛ adwuma

Wɔn a wɔde A/B sɔhwɛ fi ase anaasɛ wohia ano aduru a emu yɛ hare, a ɛnyɛ nea ɛho nhia pii no, `scipy.stats` module no ne nea wɔpaw. Ɛde akontaabu dwumadi atitiriw a ɛho hia ma nsusuwii hunu sɔhwɛ ma. Adwumayɛ kwan a wɔtaa yɛ no fa sɔhwɛ te sɛ Student’s t-test anaa Chi-squared sɔhwɛ a wɔde bedi dwuma de abu p-botae. Bere a ɛyɛ mmerɛw kɛse no, saa kwan yi hwehwɛ sɛ wode nsa di data ahosiesie ho dwuma, bu ahotoso ntamgyinafo, na wokyerɛ raw output no ase. Ɛyɛ ɔkwan a tumi wom nanso ɛyɛ nsaanodwuma.

"Sɛ wode `scipy.stats` fi ase a, ɛhyɛ ntease a emu dɔ wɔ akontaabu a ɛwɔ ase no ho, a ɛsom bo kɛse ma data ho nimdefo biara."

T-sɔhwɛ a ɛde nsakraeɛ dodoɔ toto akuo mmienu ntam ho nhwɛsoɔ nie:

````python a ɔyɛ ɔkraman efi scipy import stats mu import numpy sɛ np # Nhwɛsoɔ data: 1 ma nsakraeɛ, 0 ma nsakraeɛ biara group_a = np.array ([1, 0, 1, 1, 0, 0, 1, 0, 0, 1]) # 4 nsakraeɛ wɔ 10 mu group_b = np.array ([1, 1, 0, 1, 1, 1, 0, 1, 1, 0]) # 7 nsakraeɛ wɔ 10 mu t_stat, p_value = stats.ttest_ind (kuw_a, kuw_b) . print (f "T-akontaabu: {t_stat:.4f}, P-bo: {p_bo:.4f}") sɛ p_botae < 0.05 a: print("Wɔahu nsonsonoe a ɛho hia wɔ akontaabu mu!") anyɛ saa a: print("Wanhu nsonsonoe biara a ɛho hia wɔ akontaabu mu.") ```

Statsmodels: Akontaabu Nhwɛso a Ɛkɔ Akyiri

Sɛ wo hia nsɛm a ɛkɔ akyiri ne sɔhwɛ soronko a, `statsmodels` yɛ ɔkwan foforo a ɛkɔ akyiri. Wɔayɛ no titire ama akontabuo nhwɛsoɔ na ɛma nsɛm a ɛma nsɛm pii a wɔayɛ ama A/B sɔhwɛ tebea ahodoɔ. Wɔ proportion data (te sɛ nsakraeɛ dodoɔ) ho no, wobɛtumi de `proportions_ztest` dwumadie no adi dwuma, a ɛdi sɔhwɛ akontabuo, p-botaeɛ, ne ahotosoɔ ntamgyinafoɔ no akontabuo ho dwuma ɔno ara. Wei ma koodu no ho tew na nea efi mu ba no yɛ mmerɛw sɛ wɔbɛkyerɛ ase sɛ wɔde toto mfitiase `scipy.stats` kwan no ho a.

````python a ɔyɛ ɔkraman fa statsmodels.stats.proportion ba sɛ kyɛfa # Wɔde akontaabu a ɛfa nkonimdi ne nhwɛsode akɛse ho bedi dwuma nkonimdie = [40, 55] # Nsakyeraeɛ dodoɔ a ɛwɔ Kuo A ne B mu nobs = [100, 100] # Wɔn a wɔde di dwuma nyinaa wɔ Kuw A ne B mu z_stat, p_value = kyɛfa.nsusuwii_ztest (nkonimdi, nobs) . print (f "Z-akontaabu: {z_stat:.4f}, P-bo: {p_bo:.4f}") ```

Nhomakorabea a Wɔayɛ no Titiriw: Ɔkwan a Ɛyɛ Mmerewa a Ɛfa Nhumu

Wɔ akuo a wɔtaa yɛ A/B sɔhwɛ no fam no, nwomakorabea titire bɛtumi ama nhwehwɛmu nhyehyɛeɛ no ayɛ ntɛmntɛm kɛseɛ. Packages te sɛ `Pingouin` anaa `ab_testing` de dwumadie a ɛkorɔn a ɛde sɔhwɛ no mu nsɛm tiawa a edi mũ ba wɔ code line baako mu. Saa nsɛm a wɔaboaboa ano yi taa ka p-botae, ahotoso ntamgyinafo, Bayesian probabilities, ne nkɛntɛnso kɛse ho akontaabu, na ɛma wonya adwene a edi mũ wɔ nea efii sɔhwɛ no mu bae no ho. Eyi yɛ papa ma nhwehwɛmu a wɔde bɛka nsuo afiri anaa dashboard a wɔde afiri yɛ ho.

• Scipy.stats: Fapem, ɛyɛ mmerɛw, nanso nsaanodwuma.
• Statsmodels: Nsɛm a ɛkɔ akyiri a ɛfiri mu ba, ɛyɛ kɛseɛ ma akontabuo mu ahotewfoɔ.
• Pingouin: Akontaabu a wɔaboaboa ano a ɛyɛ mmerɛw sɛ wɔde di dwuma, a ɛkɔ akyiri.
• ab_testing: Wɔayɛ no titiriw ama A/B sɔhwɛ, ɛtaa de Bayesian akwan ka ho.

Nhwɛso a wɔde hypothetical `ab_testing` nhomakorabea di dwuma:

````python a ɔyɛ ɔkraman # Nhwɛso a ɛyɛ nsusuwii hunu ma nhomakorabea titiriw bi efi ab_testing mu no, fa hwehwɛ_ab_test mu nea efii mu bae = analyze_ab_test ( kuw_a_nsakrae=40, . kuw_a_ne nyinaa=100, . kuw_b_nsakrae=55, . kuw_b_ne nyinaa=100 ) . print (nea efii mu bae.nsɛm a wɔaboaboa ano ()) ```

Nhwehwɛmu a Wɔde Bɛka Wo Adwumayɛ Adwumayɛ Nkɔsoɔ Ho

Paket a ɛfata a wobɛpaw no yɛ ɔko no fã bi kɛkɛ. Botae ankasa a ɛwɔ A/B sɔhwɛ so no hu bere a wɔde nhumu ahorow ahyɛ w’adwuma dwumadi mu a ɛnyɛ den no. Eyi ne baabi a modular adwumayɛ OS te sɛ Mewayz di mu. Sɛ anka wobɛnya nhwehwɛmu nkyerɛwee a wɔatew wɔn ho wɔ Jupyter nkyerɛwde nhoma mu no, Mewayz ma wo kwan ma wode nhwehwɛmu adwumayɛ nhyehyɛe no nyinaa hyɛ wo adwumayɛ nhyehyɛe mu tẽẽ. Wubetumi ayɛ module a ɛtwetwe sɔhwɛ data, de Python paket a wopɛ di dwuma de yɛ nhwehwɛmu no, na ɛde dashboard a kuw no nyinaa hu no ma ankasa. Eyi ma wonya amammerɛ a ɛfa nhwehwɛmu a wɔde data di dwuma ho, na ɛhwɛ hu sɛ gyinaesi biara, efi nneɛma a wɔyɛ so kosi aguadi ɔsatu so no, wɔde adanse a wotumi de ho to so bɛma wɔahu. Ɛdenam Mewayz modularity a wode bedi dwuma so no, wubetumi ayɛ A/B sɔhwɛ nhyehyɛe a ɛyɛ den a ɛwɔ tumi na wotumi kɔ hɔ.

Nsɛmmisa a Wɔtaa Bisa

Nnianim: Tumi ne Afiri a ɛwɔ A/B Sɔhwɛ mu

A/B sɔhwɛ yɛ gyinaesi a wɔde data di dwuma no tweatibo, a ɛma nnwuma tumi kɔ akyiri sen gut nkate na wɔpaw akwan horow a adanse a wonya fi osuahu mu gyina akyi. Sɛ́ ebia woresɔ wɛbsaet nhyehyɛe foforo ahwɛ, aguadi email asɛmti, anaa ade bi a ɛwɔ wo nneɛma mu no, A/B sɔhwɛ a wɔayɛ no yiye betumi anya metrics atitiriw so nkɛntɛnso kɛse. Nanso, akwantu a efi sɔhwɛ ho nsɛm a wɔmfa nhyehyɛ mu so kɔ awiei a emu da hɔ na akontaabu mu nokware so no betumi ayɛ nea nsɛm a ɛyɛ den ahyɛ mu ma. Ɛha na Python a ɛwɔ abɔde a nkwa wom nhyehyɛe a ɛyɛ fɛ a ɛwɔ data nyansahu nhomakorabea ahorow no bɛyɛ adwinnade a ɛho nhia. Ɛma nhwehwɛmufo ne mfiridwumayɛfo tumi ma wɔhwehwɛ nea efi mu ba no mu yiye, nanso esiane sɛ nneɛma pii a tumi wom wɔ hɔ nti, nea ɛfata a wɔbɛpaw no betumi ayɛ asɛnnennen. Wɔ saa asɛm yi mu no, yɛde Python packages a agye din paa no bi bɛtoto ho ama A/B sɔhwɛ nhwehwɛmu, a edi mũ a code nhwɛsoɔ ka ho de akyerɛ wo dwumadie kwan.

Scipy.stats: Fapem kwan a wɔfa so yɛ adwuma

Wɔn a wɔde A/B sɔhwɛ fi ase anaasɛ wohia ano aduru a emu yɛ hare, a ɛnyɛ nea ɛho nhia pii no, `scipy.stats` module no ne nea wɔpaw. Ɛde akontaabu dwumadi atitiriw a ɛho hia ma nsusuwii hunu sɔhwɛ ma. Adwumayɛ kwan a wɔtaa yɛ no fa sɔhwɛ te sɛ Student’s t-test anaa Chi-squared sɔhwɛ a wɔde bedi dwuma de abu p-botae. Bere a ɛyɛ mmerɛw kɛse no, saa kwan yi hwehwɛ sɛ wode nsa di data ahosiesie ho dwuma, bu ahotoso ntamgyinafo, na wokyerɛ raw output no ase. Ɛyɛ ɔkwan a tumi wom nanso ɛyɛ nsaanodwuma.

Statsmodels: Akontaabu Nhwɛso a Ɛkɔ Akyiri

Sɛ wo hia nsɛm a ɛkɔ akyiri ne sɔhwɛ soronko a, `statsmodels` yɛ ɔkwan foforo a ɛkɔ akyiri. Wɔayɛ no titire ama akontabuo nhwɛsoɔ na ɛma nsɛm a ɛma nsɛm pii a wɔayɛ ama A/B sɔhwɛ tebea ahodoɔ. Wɔ proportion data (te sɛ nsakraeɛ dodoɔ) ho no, wobɛtumi de `proportions_ztest` dwumadie no adi dwuma, a ɛdi sɔhwɛ akontabuo, p-botaeɛ, ne ahotosoɔ ntamgyinafoɔ no akontabuo ho dwuma ɔno ara. Wei ma koodu no ho tew na nea efi mu ba no yɛ mmerɛw sɛ wɔbɛkyerɛ ase sɛ wɔde toto mfitiase `scipy.stats` kwan no ho a.

Nhomakorabea a Wɔayɛ no Titiriw: Ɔkwan a Ɛyɛ Mmerewa a Ɛfa Nhumu

Wɔ akuo a wɔtaa yɛ A/B sɔhwɛ no fam no, nwomakorabea titire bɛtumi ama nhwehwɛmu nhyehyɛeɛ no ayɛ ntɛmntɛm kɛseɛ. Packages te sɛ `Pingouin` anaa `ab_testing` de dwumadie a ɛkorɔn a ɛde sɔhwɛ no mu nsɛm tiawa a edi mũ ba wɔ code line baako mu. Saa nsɛm a wɔaboaboa ano yi taa ka p-botae, ahotoso ntamgyinafo, Bayesian probabilities, ne nkɛntɛnso kɛse ho akontaabu, na ɛma wonya adwene a edi mũ wɔ nea efii sɔhwɛ no mu bae no ho. Eyi yɛ papa ma nhwehwɛmu a wɔde bɛka nsuo afiri anaa dashboard a wɔde afiri yɛ ho.

Nhwehwɛmu a wode bɛka W’adwumayɛ adwumayɛ ho

Paket a ɛfata a wobɛpaw no yɛ ɔko no fã bi kɛkɛ. Botae ankasa a ɛwɔ A/B sɔhwɛ so no hu bere a wɔde nhumu ahorow ahyɛ w’adwuma dwumadi mu a ɛnyɛ den no. Eyi ne baabi a modular adwumayɛ OS te sɛ Mewayz di mu. Sɛ anka wobɛnya nhwehwɛmu nkyerɛwee a wɔatew wɔn ho wɔ Jupyter nkyerɛwde nhoma mu no, Mewayz ma wo kwan ma wode nhwehwɛmu adwumayɛ nhyehyɛe no nyinaa hyɛ wo adwumayɛ nhyehyɛe mu tẽẽ. Wubetumi ayɛ module a ɛtwetwe sɔhwɛ data, de Python paket a wopɛ di dwuma de yɛ nhwehwɛmu no, na ɛde dashboard a kuw no nyinaa hu no ma ankasa. Eyi ma wonya amammerɛ a ɛfa nhwehwɛmu a wɔde data di dwuma ho, na ɛhwɛ hu sɛ gyinaesi biara, efi nneɛma a wɔyɛ so kosi aguadi ɔsatu so no, wɔde adanse a wotumi de ho to so bɛma wɔahu. Ɛdenam Mewayz modularity a wode bedi dwuma so no, wubetumi ayɛ A/B sɔhwɛ nhyehyɛe a ɛyɛ den a ɛwɔ tumi na wotumi kɔ hɔ.