t-Test muInferential Statistics
Nhamba dzezviverengero (Inferential statistics) ibazi renhamba dzinoshandiswa kuwana mhedziso pamusoro pehuwandu hwevanhu zvichibva padata remuenzaniso. Chimwe chishandiso chinowanzoshandiswa mukuongorora uku kwezviverengero i-t-test. Iyo t-test inzira yekuverenga inoshandiswa kuona kana paine musiyano mukuru pakati penzira dzemapoka maviri kana kuenzanisa muenzaniso wepakati nepakati pevanhu inozivikanwa. Muchinyorwa chino, tichakurukura pfungwa huru, mhando dzezviverengero zve-t, maitiro ekushandisa, uye mashandisirwo anoshanda e-t-test munzvimbo dzakasiyana-siyana dzekutsvagisa.
Pfungwa huru dzeT-Test
Bvunzo ye-t yakagadzirwa naWilliam Sealy Gosset kutanga kwezana remakore rechi20, paaishandira kambani yedoro reGuinness. Nekuda kwezvikonzero zvekuchengetedza zvakavanzika, akaburitsa basa rake achishandisa zita rekuti "Mudzidzi," izvo zvakaita kuti bvunzo iyi izive bvunzo ye-t yeMudzidzi.
Bvunzo reT rinoshandiswa kuyedza null hypothesis (H0), iyo inotaura kuti hapana musiyano mukuru pakati penzira mbiri kana kuti sample mean yakaenzana ne population mean. Alternative hypothesis (H1) inotaura zvinopesana, kuti pane musiyano mukuru pakati pemapoka kana kuti sample mean yakasiyana ne population mean. T-statistic inoverengerwa zvichibva pa sample mean, variance, uye sample size, uye inoenzaniswa net-distribution kuti ione kukosha.
Mhando dzebvunzo dze t
Kune mhando dzakasiyana dzebvunzo dze t, imwe neimwe inoshandiswa pazvinangwa zvakasiyana:
1. Bvunzo remuenzaniso mumwe chete re t:
- Inoshandiswa kuenzanisa avhareji yemuenzaniso neavhareji yevanhu inozivikanwa.
2. Kuedza kweT-test yemuenzaniso wepaired:
- Inoshandiswa kana tine data rakabatana, semuenzaniso tisati tatanga uye tapedza kurapwa kwakafanana panyaya imwe chete.
3. Muenzaniso we t-test wakazvimiririra:
- Inoshandiswa kuenzanisa avhareji yemapoka maviri akasiyana uye asina hukama.
Muenzaniso Mumwe Chete weT-Test
Bvunzo remuenzaniso mumwe chete (t-test) rinoshandiswa patinoda kuona kana avhareji yemuenzaniso mumwe chete wedata yakasiyana zvakanyanya neavhareji inozivikanwa kana inofungidzirwa yevanhu. Ngatitii tine data rehuremu hwemuenzaniso kubva kuboka revanhu uye tinoda kurienzanisa nehuremu hweavhareji hwevanhu vose.
Kurongeka:
1. Sarudza avhareji yemuenzaniso (\(\bar{X}\)), avhareji yehuwandu hwevanhu (\(\mu\)), uye kutsauka kwakajairika kwemuenzaniso (s).
2. Verenga nhamba ye t uchishandisa fomura:
\[
t = \frac{\bar{X} – \mu}{\frac{s}{\sqrt{n}}}
\]
apo \(n\) ndiyo saizi yemuenzaniso.
3. Enzanisa t-value yakaverengerwa ne critical t-value kubva patafura yekugovera t zvichibva pamadhigirii erusununguko (\(df = n-1\)) uye mwero wekukosha unodiwa.
Kana nhamba ye t yakakura kupfuura t-critical, tinoramba fungidziro isina basa togumisa kuti pane musiyano mukuru.
T-Test yemuenzaniso miviri yekubatana
Bvunzo reT-test rine mienzaniso miviri rinoshandiswa kana tine data remhando mbiri kana kuti mapeya maviri. Muenzaniso unowanzoonekwa ndewebvunzo risati raitwa uye raitwa mushure mekuita bvunzo paboka rimwe chete.
Kurongeka:
1. Verenga musiyano wepairi dzedata (\(d\)) uye avhareji yemusiyano (\(\bar{d}\)).
2. Verenga kutsauka kwakajairwa kwemusiyano (s_d).
3. Nhamba ye t inoverengwa uchishandisa fomura:
\[
t = \frac{\bar{d}}{\frac{s_d}{\sqrt{n}}}
\]
4. Enzanisa t-value yakaverengerwa ne critical t-value kubva patafura yekugovera t ne \(df = n-1\).
T-Test yeMienzaniso Miviri Isina Kuenderana
Iyi bvunzo ye-t inoshandiswa kuenzanisa nzira dzemapoka maviri akasiyana.
Kurongeka:
1. Sarudza avhareji uye standard deviation yemasampuli maviri (\(\bar{X_1}\), s1, n1) uye (\(\bar{X_2}\), s2, n2).
2. Verenga nhamba ye t uchishandisa fomura:
\[
t = \frac{\bar{X_1} – \bar{X_2}}{\sqrt{\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2}}}
\]
3. Dhigirii rerusununguko rinoverengerwa uchishandisa fomura yakaoma kunzwisisa kana uchishandisa mutemo wekuchengetedza (n1+n2-2).
4. Enzanisa t-value yakaverengerwa ne critical t-value.
Maitiro Ekushandisa T-Test
Kuita bvunzo ye-t hakungodi kuverenga nhamba chete asiwo kunzwisisa kwakakwana kwenyaya yekutsvagisa uye fungidziro dziripo:
1. Kuumbwa kweFungidziro: Sarudza fungidziro dzisina basa nedzimwe dzinofanira kuyedzwa.
2. Kuunganidza nekuongorora Data: Iva nechokwadi chekuti data rinosangana nepfungwa dzepakutanga dze t-test dzakadai sekujairika uye zviyero zvekuyera zvakakodzera.
3. Verenga nhamba ye t: Shandisa fomura yakakodzera yerudzi rwe t-test inoshandiswa.
4. Enzanisa neT-Distribution uye Dudzira Mhedzisiro: Enzanisa t-test yakaverengerwa net-test yakakosha uye ona sarudzo maererano ne null hypothesis.
5. Ita Miedzo Yekuwedzera Kana Zvichidikanwa: Dzimwe nguva mimwe miedzo inodiwa kuti ive nechokwadi chekuti mhedzisiro yacho ndeyechokwadi, senge bvunzo yaLevene yekuenzana kwemarudzi akasiyana mubvunzo yeT-test ine sampuli mbiri isina hukama.
Mashandisirwo Anoshanda eT-Test
Bvunzo re-t rinoshandiswa munzvimbo dzakasiyana-siyana kusimbisa zvirongwa nezvisarudzo. Semuenzaniso:
– Zvekurapa: Kuongororwa kwe-t kunoshandiswa kuongorora kushanda kwekurapa kutsva nekuenzanisa kurapwa kusati kwaitwa uye kwaitwa mushure mekurapwa muboka rimwe chete.
– Dzidzo: Kuenzanisa mamakisi ebvunzo pakati penzira mbiri dzekudzidzisa kuti uone kuti ndeipi nzira inoshanda zvakanyanya.
– Bhizinesi: Kuenzanisa kwekutengesa kweavhareji isati yatanga uye mushure mekushambadzira.
Semuenzaniso, mukutsvagurudza kwezvekurapa, muongorori angada kuziva kana mushonga mutsva uchikonzera shanduko huru muBP. Nekutora murwere asati atora uye mushure mekurapwa, vanogona kushandisa bvunzo yeT-test ine sampuli mbiri kuti vaongorore.
Mhedziso
Bvunzo ye-t chishandiso chakakosha muhuwandu hwezviverengero. Nekunzwisisa pfungwa huru, mhando dzebvunzo dze-t, uye maitiro akakodzera ekushandisa, vaongorori vanogona kuita sarudzo dzakarurama uye dzakavimbika dzinobva padata. Nekushandiswa kwakapararira munzvimbo dzakasiyana siyana, bvunzo ye-t inoramba iri chinhu chikuru mukuongorora kwezviverengero zvekuyedza fungidziro uye kuwana mhedziso dzakakodzera nezvehuwandu hwevanhu zvichibva padata remuenzaniso.
