{"id":55853,"date":"2025-01-09T12:04:31","date_gmt":"2025-01-09T15:04:31","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/?p=55853"},"modified":"2025-01-23T12:12:27","modified_gmt":"2025-01-23T15:12:27","slug":"null-hypothesis-significance","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/lv\/null-hypothesis-significance\/","title":{"rendered":"Izpratne par nulles hipot\u0113zes noz\u012bm\u012bgumu statistiskaj\u0101 test\u0113\u0161an\u0101"},"content":{"rendered":"

Nulles hipot\u0113zes noz\u012bm\u012bgums ir statistikas test\u0113\u0161anas pamatj\u0113dziens, kas pal\u012bdz p\u0113tniekiem noteikt, vai vi\u0146u dati apstiprina konkr\u0113tu apgalvojumu vai nov\u0113rojumu. \u0160aj\u0101 rakst\u0101 apl\u016bkots nulles hipot\u0113zes noz\u012bm\u012bguma j\u0113dziens, t\u0101 pielietojums p\u0113tniec\u012bb\u0101 un noz\u012bme uz datiem balst\u012btu l\u0113mumu pie\u0146em\u0161an\u0101.<\/p>\n\n\n\n

Visvienk\u0101r\u0161\u0101k\u0101 form\u0101 nulles hipot\u0113ze liecina, ka starp p\u0101rbaud\u0101majiem main\u012bgajiem lielumiem nav noz\u012bm\u012bgas ietekmes vai saist\u012bbas. Citiem v\u0101rdiem sakot, t\u0101 pie\u0146em, ka jebkuras at\u0161\u0137ir\u012bbas, ko nov\u0113rojat datos, ir nejau\u0161as nejau\u0161\u012bbas, nevis re\u0101las ietekmes rezult\u0101ts.<\/p>\n\n\n\n

Nulles hipot\u0113zes noz\u012bme ir t\u0101s objektivit\u0101te. Bet apst\u0101simies pie t\u0101, jo p\u0101r\u0101k liela baro\u0161ana s\u0101kum\u0101 j\u016bs mulsin\u0101s. Uzzin\u0101sim par nulles hipot\u0113zes noz\u012bm\u012bgums<\/strong>  no nulles!<\/p>\n\n\n\n

Izpratne par nulles hipot\u0113zes noz\u012bmi p\u0113tniec\u012bb\u0101<\/h2>\n\n\n\n

Nulles hipot\u0113ze ir galvenais, lai izprastu nulles hipot\u0113zes noz\u012bm\u012bgumu, jo t\u0101 ir pie\u0146\u0113mums, ka statistiskaj\u0101 test\u0113\u0161an\u0101 nav ietekmes vai saist\u012bbas starp main\u012bgajiem. Citiem v\u0101rdiem sakot, tas noz\u012bm\u0113, ka neatkar\u012bgi no t\u0101, ko test\u0113jat - vai tas b\u016btu jauns medikaments, m\u0101c\u012bbu metode vai k\u0101da cita iejauk\u0161an\u0101s -, tai nav ietekmes sal\u012bdzin\u0101jum\u0101 ar standarta vai b\u0101zes scen\u0101riju. <\/p>\n\n\n\n

Nulles hipot\u0113zes m\u0113r\u0137is ir nodro\u0161in\u0101t s\u0101kumpunktu anal\u012bzei, kad j\u016bs pie\u0146emat, ka nav izmai\u0146u vai at\u0161\u0137ir\u012bbu.<\/p>\n\n\n\n

Par nulles hipot\u0113zi var dom\u0101t k\u0101 par noklus\u0113juma poz\u012bciju, kuru j\u016bs m\u0113\u0123in\u0101t atsp\u0113kot vai noraid\u012bt. T\u0101 viet\u0101, lai tie\u0161i pie\u0146emtu, ka j\u016bsu eksperimentam b\u016bs ietekme, j\u016bs vispirms uzskat\u0101t, ka nekas nav main\u012bjies.\u00a0<\/p>\n\n\n\n

\""Mind<\/a>
Bez piep\u016bles veidojiet zin\u0101tniskas ilustr\u0101cijas, izmantojot Mind the Graph<\/a>.<\/figcaption><\/figure>\n\n\n\n

Tas pal\u012bdz jums pieiet situ\u0101cijai objekt\u012bvi un ne\u013cauj izdar\u012bt secin\u0101jumus bez pier\u0101d\u012bjumiem. S\u0101kot ar pie\u0146\u0113mumu, ka \"ietekmes nav\", j\u016bs varat stingri p\u0101rbaud\u012bt savu ideju, izmantojot datus, un tikai tad, ja pier\u0101d\u012bjumi ir pietiekami sp\u0113c\u012bgi, j\u016bs varat noraid\u012bt nulles hipot\u0113zi un apgalvot, ka ir noticis kaut kas b\u016btisks.<\/p>\n\n\n\n

Loma zin\u0101tniskajos eksperimentos<\/h3>\n\n\n\n

Nulles hipot\u0113zei ir iz\u0161\u0137iro\u0161a noz\u012bme zin\u0101tnisk\u0101s izp\u0113tes proces\u0101. T\u0101 rada skaidru pamatu eksperimentiem un datu anal\u012bzei. Veicot eksperimentu, m\u0113r\u0137is parasti ir noskaidrot, vai konkr\u0113ts main\u012bgais ietekm\u0113 citu main\u012bgo. <\/p>\n\n\n\n

Piem\u0113ram, j\u016bs, iesp\u0113jams, v\u0113laties uzzin\u0101t, vai jaunas z\u0101les mazina simptomus efekt\u012bv\u0101k nek\u0101 placebo. \u0160aj\u0101 gad\u012bjum\u0101 nulles hipot\u0113ze apgalvotu, ka z\u0101\u013cu iedarb\u012bba nav lab\u0101ka nek\u0101 placebo, un j\u016bsu uzdevums ir apkopot datus, kas \u0161o ideju vai nu apstiprina, vai ar\u012b ap\u0161auba.<\/p>\n\n\n\n

Izvirzot nulles hipot\u0113zi, j\u016bs ievie\u0161at eksperiment\u0101 ar\u012b \"falsific\u0113jam\u012bbas\" j\u0113dzienu. Falsific\u0113jam\u012bba noz\u012bm\u0113, ka j\u016bsu hipot\u0113zi var p\u0101rbaud\u012bt un, iesp\u0113jams, pier\u0101d\u012bt, ka t\u0101 ir nepareiza. Tas ir svar\u012bgi, jo nodro\u0161ina, ka j\u016bsu zin\u0101tnisko apgalvojumu pamat\u0101 ir izm\u0113r\u0101mi dati, nevis pie\u0146\u0113mumi vai min\u0113jumi.<\/p>\n\n\n\n

Nulles hipot\u0113zes piem\u0113ri<\/h3>\n\n\n\n

1. piem\u0113rs: jauna uztura pl\u0101na test\u0113\u0161ana<\/strong><\/p>\n\n\n\n

Iedom\u0101jieties, ka test\u0113jat jaunu di\u0113tas pl\u0101nu, lai noskaidrotu, vai tas pal\u012bdz cilv\u0113kiem zaud\u0113t svaru sal\u012bdzin\u0101jum\u0101 ar parasto di\u0113tu. J\u016bsu nulles hipot\u0113ze b\u016btu \u0161\u0101da: \"Jaun\u0101 di\u0113ta neietekm\u0113 svara samazin\u0101\u0161anos, sal\u012bdzinot ar parasto di\u0113tu.\" Tas noz\u012bm\u0113, ka j\u016bs s\u0101kat ar pie\u0146\u0113mumu, ka jaun\u0101 di\u0113ta nav efekt\u012bv\u0101ka par to, ko cilv\u0113ki jau \u0113d.<\/p>\n\n\n\n

Kad jums ir \u0161\u012b nulles hipot\u0113ze, varat v\u0101kt datus, izveidojot divas cilv\u0113ku grupas - vienu, kas iev\u0113ro jauno di\u0113tu, un otru, kas iev\u0113ro savu parasto di\u0113tu. Ja p\u0113c datu anal\u012bzes konstat\u0113siet, ka grupa, kas iev\u0113ro jauno di\u0113tu, zaud\u0113 iev\u0113rojami vair\u0101k svara nek\u0101 kontroles grupa, j\u016bs varat noraid\u012bt nulles hipot\u0113zi. Tas liecin\u0101tu, ka jaunajam di\u0113tas pl\u0101nam ir pozit\u012bva ietekme.<\/p>\n\n\n\n

2. piem\u0113rs: p\u0113t\u012bjums par miega ietekmi uz testa rezult\u0101tiem<\/strong><\/p>\n\n\n\n

Cit\u0101 gad\u012bjum\u0101 j\u016bs, iesp\u0113jams, v\u0113laties izp\u0113t\u012bt, vai vair\u0101k miega uzlabo skol\u0113nu p\u0101rbaudes rezult\u0101tu. J\u016bsu nulles hipot\u0113ze b\u016btu \u0161\u0101da: \"Nav nek\u0101das saist\u012bbas starp miega daudzumu un skol\u0113nu testa rezult\u0101tiem.\" Nulles hipot\u0113ze: \"Nav nek\u0101das saist\u012bbas starp miega daudzumu un skol\u0113nu testa rezult\u0101tiem.\" Citiem v\u0101rdiem sakot, j\u016bs pie\u0146emat, ka tas, cik daudz skol\u0113ni gu\u013c, neietekm\u0113 vi\u0146u sniegumu p\u0101rbaudes darbos.<\/p>\n\n\n\n

P\u0113c tam j\u016bs var\u0113tu v\u0101kt datus par skol\u0113nu miega paradumiem un vi\u0146u testa rezult\u0101tiem. Ja j\u016bs atkl\u0101siet, ka skol\u0113ni, kuri vair\u0101k gu\u013c, past\u0101v\u012bgi uzr\u0101da lab\u0101kus rezult\u0101tus, j\u016bs var\u0113tu noraid\u012bt nulles hipot\u0113zi un secin\u0101t, ka vair\u0101k miega patie\u0161\u0101m uzlabo m\u0101c\u012bbu rezult\u0101tus. <\/p>\n\n\n\n

Tom\u0113r, ja j\u016bsu dati neuzr\u0101da b\u016btiskas at\u0161\u0137ir\u012bbas starp labi atp\u016btu\u0161amies skol\u0113niem un tiem, kuri gu\u013c maz\u0101k, nulles hipot\u0113zi noraid\u012bt neizdosies, kas noz\u012bm\u0113, ka nav pier\u0101d\u012bjumu, kas liecin\u0101tu, ka miegs b\u016btiski ietekm\u0113 p\u0101rbaudes rezult\u0101tus.<\/p>\n\n\n\n

Abos piem\u0113ros nulles hipot\u0113ze kalpo par pamatu test\u0113\u0161anai un pal\u012bdz jums nov\u0113rt\u0113t, vai sav\u0101ktie dati sniedz pietiekamus pier\u0101d\u012bjumus, lai izdar\u012btu j\u0113gpilnus secin\u0101jumus.<\/p>\n\n\n\n

Saist\u012bts raksts: <\/strong>Defin\u0113t hipot\u0113zi: Atkl\u0101jiet pirmo soli zin\u0101tniskaj\u0101 p\u0113tniec\u012bb\u0101.<\/strong><\/a><\/p>\n\n\n\n

Nulles hipot\u0113zes noz\u012bm\u012bguma noz\u012bme test\u0113\u0161an\u0101<\/h2>\n\n\n\n

Nulles hipot\u0113zes m\u0113r\u0137is<\/h3>\n\n\n\n

Nulles hipot\u0113zes noz\u012bm\u012bguma j\u0113dziens ir p\u0113tniec\u012bbas pamat\u0101, nodro\u0161inot neitr\u0101lu s\u0101kumpunktu, lai objekt\u012bvi nov\u0113rt\u0113tu zin\u0101tniskos apgalvojumus. T\u0101s m\u0113r\u0137is ir nodro\u0161in\u0101t neitr\u0101lu s\u0101kumpunktu, pal\u012bdzot p\u0101rbaud\u012bt, vai eksperimenta rezult\u0101ti ir nejau\u0161\u012bbas vai re\u0101las ietekmes rezult\u0101ts. <\/p>\n\n\n\n

Veicot p\u0113t\u012bjumus, bie\u017ei vien pr\u0101t\u0101 ir k\u0101da teorija vai prognoze - kaut kas, ko cerat pier\u0101d\u012bt. Tom\u0113r nulles hipot\u0113ze paredz, ka nav nek\u0101das ietekmes vai saist\u012bbas. Piem\u0113ram, ja p\u0101rbaud\u0101t, vai jauna z\u0101les uzlabo pacientu atvese\u013co\u0161anos, nulles hipot\u0113ze apgalvotu, ka z\u0101l\u0113m nav ietekmes sal\u012bdzin\u0101jum\u0101 ar placebo.<\/p>\n\n\n\n

\u0160is pie\u0146\u0113mums ir \u013coti svar\u012bgs, jo tas nodro\u0161ina anal\u012bzes objektivit\u0101ti. S\u0101kot ar pie\u0146\u0113mumu, ka nekas nav main\u012bjies vai uzlabojies, j\u016bs nodro\u0161in\u0101siet, ka visi secin\u0101jumi ir balst\u012bti uz pamatotiem pier\u0101d\u012bjumiem, nevis uz person\u012bgiem uzskatiem vai cer\u012bb\u0101m. <\/p>\n\n\n\n

Tas pal\u012bdz jums saglab\u0101t objekt\u012bvu pieeju, ne\u013caujot izdar\u012bt p\u0101rsteidz\u012bgus secin\u0101jumus tikai t\u0101p\u0113c, ka v\u0113laties, lai j\u016bsu hipot\u0113ze b\u016btu patiesa.<\/p>\n\n\n\n

Turkl\u0101t nulles hipot\u0113ze ir standarts, p\u0113c kura var nov\u0113rt\u0113t ieg\u016btos rezult\u0101tus. Bez t\u0101s jums neb\u016btu skaidras b\u0101zes l\u012bnijas, ar kuru sal\u012bdzin\u0101t rezult\u0101tus, t\u0101p\u0113c b\u016btu gr\u016bti noteikt, vai dati patie\u0161\u0101m apstiprina j\u016bsu teoriju. <\/p>\n\n\n\n

T\u0101p\u0113c katr\u0101 eksperiment\u0101 nulles hipot\u0113ze darbojas k\u0101 aizsargmeh\u0101nisms, kas nodro\u0161ina, ka j\u016bsu secin\u0101jumi ir pamatoti ar datiem, nevis pie\u0146\u0113mumiem.<\/p>\n\n\n\n

Loma hipot\u0113\u017eu p\u0101rbaud\u0113<\/h3>\n\n\n\n

Hipot\u0113zes p\u0101rbaude ir saist\u012bta ar nulles hipot\u0113zes noz\u012bm\u012bgumu, nov\u0113rt\u0113jot, vai nov\u0113rotie rezult\u0101ti ir noz\u012bm\u012bgi vai tikai nejau\u0161as vari\u0101cijas rezult\u0101ts. \u0160eit nulles hipot\u0113ze k\u013c\u016bst \u013coti svar\u012bga. S\u0101kum\u0101 j\u0101izvirza divas hipot\u0113zes: nulles hipot\u0113ze (kas pie\u0146em, ka ietekmes nav) un alternat\u012bv\u0101 hipot\u0113ze (kas pie\u0146em, ka ietekme vai saist\u012bba past\u0101v).<\/p>\n\n\n\n

Hipot\u0113zes p\u0101rbaudes process parasti ietver datu v\u0101k\u0161anu un to anal\u012bzi, lai noskaidrotu, kuru hipot\u0113zi dati apstiprina. Vispirms pie\u0146em, ka nulles hipot\u0113ze ir patiesa. P\u0113c tam veiciet eksperimentu un v\u0101cat datus, lai p\u0101rbaud\u012btu \u0161o pie\u0146\u0113mumu. <\/p>\n\n\n\n

P\u0113c tam izmantojiet statistikas metodes, lai analiz\u0113tu datus, piem\u0113ram, apr\u0113\u0137in\u0101tu p-v\u0113rt\u012bbas vai ticam\u012bbas interv\u0101lus. \u0160\u012bs metodes pal\u012bdz nov\u0113rt\u0113t varb\u016bt\u012bbu, ka nov\u0113rotie rezult\u0101ti radu\u0161ies nejau\u0161\u012bbas d\u0113\u013c.<\/p>\n\n\n\n

Ja dati liecina, ka nov\u0113rotie rezult\u0101ti ir \u013coti maz ticami nulles hipot\u0113zes gad\u012bjum\u0101 (parasti to nosaka p v\u0113rt\u012bba, kas ir maz\u0101ka par noteiktu robe\u017ev\u0113rt\u012bbu, piem\u0113ram, 0,05), j\u016bs noraid\u0101t nulles hipot\u0113zi. <\/p>\n\n\n\n

Tas neb\u016bt nenoz\u012bm\u0113, ka alternat\u012bv\u0101 hipot\u0113ze ir absol\u016bti patiesa, ta\u010du tas liecina, ka ir pietiekami daudz pier\u0101d\u012bjumu, lai to atbalst\u012btu sal\u012bdzin\u0101jum\u0101 ar nulles hipot\u0113zi.<\/p>\n\n\n\n

No otras puses, ja dati nesniedz pietiekami sp\u0113c\u012bgus pier\u0101d\u012bjumus, lai noraid\u012btu nulles hipot\u0113zi, j\u016bs to \"nenoraid\u0101t\". Tas noz\u012bm\u0113, ka jums nav pietiekamu pier\u0101d\u012bjumu, lai apgalvotu, ka past\u0101v b\u016btiska ietekme vai saist\u012bba, t\u0101p\u0113c nulles hipot\u0113ze paliek sp\u0113k\u0101.<\/p>\n\n\n\n

Nulles hipot\u0113zes p\u0101rbaude ir b\u016btiska, jo t\u0101 \u013cauj pie\u0146emt pamatotus l\u0113mumus par rezult\u0101tu noz\u012bm\u012bgumu. T\u0101 pal\u012bdz izvair\u012bties no k\u013c\u016bdaini pozit\u012bviem secin\u0101jumiem, kad j\u016bs var\u0113tu k\u013c\u016bdaini secin\u0101t, ka sakar\u012bba past\u0101v, lai gan t\u0101 nepast\u0101v. <\/p>\n\n\n\n

Faktori, kas ietekm\u0113 nulles hipot\u0113zes p\u0101rbaudi<\/h2>\n\n\n\n

B\u016btiskuma l\u012bmenis, ko bie\u017ei apz\u012bm\u0113 ar simbolu \u03b1 (alfa), ir galvenais faktors hipot\u0113\u017eu p\u0101rbaud\u0113. Tas ir slieksnis, ko j\u016bs nosak\u0101t, lai noteiktu, vai j\u016bsu eksperimenta rezult\u0101ti ir statistiski noz\u012bm\u012bgi, t. i., vai nov\u0113rotais efekts, iesp\u0113jams, ir re\u0101ls vai vienk\u0101r\u0161i nejau\u0161\u012bbas rezult\u0101ts. <\/p>\n\n\n\n

Parasti par noz\u012bm\u012bguma l\u012bmeni izv\u0113las 0,05 (vai 5%). Tas noz\u012bm\u0113, ka esat gatavs pie\u0146emt 5% iesp\u0113ju, ka rezult\u0101ti ir nejau\u0161as vari\u0101cijas, nevis patiesas ietekmes rezult\u0101ts.<\/p>\n\n\n\n

Dom\u0101jiet par noz\u012bm\u012bguma l\u012bmeni k\u0101 par robe\u017ev\u0113rt\u012bbu. Ja p-v\u0113rt\u012bba, kas m\u0113ra varb\u016bt\u012bbu nov\u0113rot efektu, ja nulles hipot\u0113ze ir patiesa, ir maz\u0101ka par noz\u012bm\u012bguma l\u012bmeni, j\u016bs noraid\u0101t nulles hipot\u0113zi. Tas liecina, ka ir pietiekami daudz pier\u0101d\u012bjumu, lai secin\u0101tu, ka re\u0101la ietekme vai saist\u012bba past\u0101v. No otras puses, ja p v\u0113rt\u012bba ir liel\u0101ka par noz\u012bm\u012bguma l\u012bmeni, nulles hipot\u0113zi noraid\u012bt neizdodas, kas nor\u0101da, ka dati nesniedz pietiekami sp\u0113c\u012bgus pier\u0101d\u012bjumus, lai apstiprin\u0101tu b\u016btisku secin\u0101jumu.<\/p>\n\n\n\n

Izv\u0113l\u0113tais noz\u012bm\u012bguma l\u012bmenis ietekm\u0113 to, cik stingra ir j\u016bsu test\u0113\u0161ana. Zem\u0101ks noz\u012bm\u012bguma l\u012bmenis (piem\u0113ram, 0,01 vai 1%) noz\u012bm\u0113, ka esat piesardz\u012bg\u0101ks, noraidot nulles hipot\u0113zi, bet tas ar\u012b samazina varb\u016bt\u012bbu, ka tiks ieg\u016bti noz\u012bm\u012bgi rezult\u0101ti. <\/p>\n\n\n\n

Augst\u0101ks noz\u012bm\u012bguma l\u012bmenis (piem\u0113ram, 0,10 vai 10%) palielina izredzes ieg\u016bt noz\u012bm\u012bgus rezult\u0101tus, bet palielina varb\u016bt\u012bbu, ka nulles hipot\u0113zi var nepatiesi noraid\u012bt. T\u0101p\u0113c noz\u012bm\u012bguma l\u012bme\u0146a izv\u0113le ir svar\u012bga, un tai j\u0101atspogu\u013co j\u016bsu p\u0113t\u012bjuma konteksts.<\/p>\n\n\n\n

I un II tipa k\u013c\u016bdas<\/h3>\n\n\n\n

Hipot\u0113\u017eu p\u0101rbaud\u0113 var rasties divu veidu k\u013c\u016bdas: I tipa un II tipa k\u013c\u016bdas. \u0160\u012bs k\u013c\u016bdas ir tie\u0161i saist\u012btas ar testa rezult\u0101tu un noz\u012bm\u012bguma l\u012bme\u0146a izv\u0113li.<\/p>\n\n\n\n

I tipa k\u013c\u016bda<\/h4>\n\n\n\n

I tipa k\u013c\u016bda rodas tad, ja nulles hipot\u0113zi noraida, lai gan t\u0101 paties\u012bb\u0101 ir patiesa. Citiem v\u0101rdiem sakot, j\u016bs secin\u0101t, ka ietekme vai saist\u012bba past\u0101v, lai gan paties\u012bb\u0101 t\u0101s nav. <\/p>\n\n\n\n

To sauc ar\u012b par \"viltus pozit\u012bvu rezult\u0101tu\", jo tiek atkl\u0101ts kaut kas, k\u0101 paties\u012bb\u0101 nav.<\/p>\n\n\n\n

Noteiktais noz\u012bm\u012bguma l\u012bmenis (\u03b1) ir I tipa k\u013c\u016bdas varb\u016bt\u012bba. Piem\u0113ram, ja j\u016bsu noz\u012bm\u012bguma l\u012bmenis ir 0,05, past\u0101v 5% varb\u016bt\u012bba, ka j\u016bs k\u013c\u016bdaini noraid\u012bsiet nulles hipot\u0113zi, ja t\u0101 ir patiesa. <\/p>\n\n\n\n

I tipa k\u013c\u016bdas sekas var b\u016bt nopietnas, \u012bpa\u0161i t\u0101d\u0101s jom\u0101s k\u0101 medic\u012bna vai farm\u0101cija. Ja tiek test\u0113ts jauns medikaments un rodas I tipa k\u013c\u016bda, p\u0113tnieki var uzskat\u012bt, ka medikaments ir efekt\u012bvs, lai gan tas t\u0101 nav, kas var rad\u012bt kait\u012bgas sekas.<\/p>\n\n\n\n

Lai samazin\u0101tu I tipa k\u013c\u016bdas risku, varat izv\u0113l\u0113ties zem\u0101ku noz\u012bm\u012bguma l\u012bmeni. Tom\u0113r p\u0101r\u0101k liela piesardz\u012bba, p\u0101r\u0101k pazeminot noz\u012bm\u012bguma l\u012bmeni, var rad\u012bt ar\u012b tr\u016bkumus, jo t\u0101 var apgr\u016btin\u0101t re\u0101l\u0101s ietekmes atkl\u0101\u0161anu (kas izraisa cita veida k\u013c\u016bdu - II tipa k\u013c\u016bdu).<\/p>\n\n\n\n

II tipa k\u013c\u016bda<\/h4>\n\n\n\n

II tipa k\u013c\u016bda rodas tad, ja jums neizdodas noraid\u012bt nulles hipot\u0113zi, ja t\u0101 paties\u012bb\u0101 ir nepatiesa. Vienk\u0101r\u0161\u0101k sakot, tas noz\u012bm\u0113, ka j\u016bs nesaskat\u0101t re\u0101lu ietekmi vai sakar\u012bbu, kas patie\u0161\u0101m eksist\u0113. To sauc par \"viltus negat\u012bvu\", jo j\u016bs neatkl\u0101jat kaut ko, kas paties\u012bb\u0101 past\u0101v.<\/p>\n\n\n\n

II tipa k\u013c\u016bdas varb\u016bt\u012bbu apz\u012bm\u0113 ar simbolu \u03b2 (beta). At\u0161\u0137ir\u012bb\u0101 no noz\u012bm\u012bguma l\u012bme\u0146a, ko iestat\u0101t pirms test\u0113\u0161anas, \u03b2 ietekm\u0113 t\u0101di faktori k\u0101 izlases lielums, efekta lielums un noz\u012bm\u012bguma l\u012bmenis. <\/p>\n\n\n\n

Liel\u0101ka izlase samazina II tipa k\u013c\u016bdas iesp\u0113jam\u012bbu, jo t\u0101 sniedz vair\u0101k datu, t\u0101d\u0113j\u0101di \u013caujot viegl\u0101k noteikt re\u0101lo ietekmi. L\u012bdz\u012bgi ar\u012b liel\u0101kus ietekmes lielumus (sp\u0113c\u012bg\u0101kas sakar\u012bbas) ir viegl\u0101k noteikt, un tas samazina II tipa k\u013c\u016bdas iesp\u0113jam\u012bbu.<\/p>\n\n\n\n

II tipa k\u013c\u016bdas var b\u016bt tikpat problem\u0101tiskas k\u0101 I tipa k\u013c\u016bdas, jo \u012bpa\u0161i, ja likmes ir augstas. <\/p>\n\n\n\n

Piem\u0113ram, ja p\u0101rbaud\u0101t, vai jauna \u0101rst\u0113\u0161ana ir efekt\u012bva, un pie\u013caujat II tipa k\u013c\u016bdu, j\u016bs varat secin\u0101t, ka \u0101rst\u0113\u0161anai nav ietekmes, lai gan paties\u012bb\u0101 t\u0101 ir efekt\u012bva, t\u0101d\u0113j\u0101di liedzot pacientiem sa\u0146emt potenci\u0101li labv\u0113l\u012bgu terapiju.<\/p>\n\n\n\n

Ir svar\u012bgi l\u012bdzsvarot abu veidu k\u013c\u016bdu risku. Ja p\u0101r\u0101k lielu uzman\u012bbu piev\u0113r\u0161at I tipa k\u013c\u016bdu nov\u0113r\u0161anai, nosakot \u013coti zemu noz\u012bm\u012bguma l\u012bmeni, j\u016bs paaugstin\u0101t II tipa k\u013c\u016bdu risku, izlai\u017eot patiesos secin\u0101jumus. No otras puses, ja cen\u0161aties izvair\u012bties no II tipa k\u013c\u016bd\u0101m, nosakot augst\u0101ku noz\u012bm\u012bguma l\u012bmeni, j\u016bs palielin\u0101t iesp\u0113ju pie\u013caut I tipa k\u013c\u016bdu. T\u0101p\u0113c \u013coti svar\u012bga ir r\u016bp\u012bga pl\u0101no\u0161ana un p\u0113t\u012bjuma konteksta apsv\u0113r\u0161ana.<\/p>\n\n\n\n

Lasiet ar\u012b: <\/strong>Hipot\u0113\u017eu p\u0101rbaude: Hipot\u0113\u017eu hipot\u0113zes: principi un metodes.<\/strong><\/a><\/p>\n\n\n\n

Nulles hipot\u0113zes noz\u012bm\u012bguma lietojumi re\u0101laj\u0101 dz\u012bv\u0113<\/h2>\n\n\n\n

Ikdienas piem\u0113ri<\/h3>\n\n\n\n

Nulles hipot\u0113zes j\u0113dziens attiecas ne tikai uz sare\u017e\u0123\u012btiem zin\u0101tniskiem p\u0113t\u012bjumiem, bet ar\u012b uz daudziem ikdienas dz\u012bves scen\u0101rijiem. Lai pal\u012bdz\u0113tu jums to lab\u0101k izprast, apl\u016bkosim divus vienk\u0101r\u0161us, saprotamus piem\u0113rus, kuros tiek izmantota nulles hipot\u0113ze.<\/p>\n\n\n\n

1. piem\u0113rs: jauna treni\u0146u pl\u0101na test\u0113\u0161ana<\/strong><\/p>\n\n\n\n

Iedom\u0101jieties, ka esat non\u0101cis pie jauna treni\u0146u pl\u0101na, kas apgalvo, ka tas pal\u012bdz\u0113s jums zaud\u0113t vair\u0101k svara, sal\u012bdzinot ar pa\u0161reiz\u0113jo rut\u012bnas. \u0160aj\u0101 gad\u012bjum\u0101 nulles hipot\u0113ze b\u016btu, ka jaunais treni\u0146u pl\u0101ns b\u016btiski nepalielina j\u016bsu svara zudumu, sal\u012bdzinot ar pa\u0161reiz\u0113jo re\u017e\u012bmu. Citiem v\u0101rdiem sakot, j\u016bs s\u0101kat ar pie\u0146\u0113mumu, ka jaunais pl\u0101ns nepal\u012bdz\u0113s jums zaud\u0113t vair\u0101k svara.<\/p>\n\n\n\n

P\u0113c tam j\u016bs var\u0113tu to p\u0101rbaud\u012bt, iev\u0113rojot abus treni\u0146u pl\u0101nus noteikt\u0101 laika posm\u0101, sekojot svara zudumam katr\u0101 no tiem. Ja, apkopojot pietiekami daudz datu, j\u016bs konstat\u0113siet, ka, izmantojot jauno pl\u0101nu, j\u016bs zaud\u0113jat iev\u0113rojami vair\u0101k svara, j\u016bs var\u0113tu noraid\u012bt nulles hipot\u0113zi, secinot, ka jaunais pl\u0101ns ir efekt\u012bvs. <\/p>\n\n\n\n

No otras puses, ja j\u016bsu svara zuduma rezult\u0101ti ir l\u012bdz\u012bgi, nulles hipot\u0113zi noraid\u012bt neizdosies, kas noz\u012bm\u0113, ka jaunais pl\u0101ns nav devis nek\u0101du papildu labumu.<\/p>\n\n\n\n

2. piem\u0113rs: miega lietotnes efektivit\u0101tes nov\u0113rt\u0113\u0161ana<\/strong><\/p>\n\n\n\n

Pie\u0146emsim, ka lejupiel\u0101d\u0113jat miega aplik\u0101ciju, kas apgalvo, ka t\u0101 pal\u012bdz\u0113s uzlabot miega kvalit\u0101ti. J\u016bs v\u0113laties p\u0101rbaud\u012bt, vai \u0161\u012bs lietotnes lieto\u0161ana patie\u0161\u0101m uzlabo miegu. J\u016bsu nulles hipot\u0113ze b\u016btu, ka lietotne neietekm\u0113 miega kvalit\u0101ti.<\/p>\n\n\n\n

Lai to p\u0101rbaud\u012btu, varat ned\u0113\u013cu sekot l\u012bdzi saviem miega paradumiem, neizmantojot lietotni, un p\u0113c tam v\u0113l ned\u0113\u013cu, izmantojot lietotni. Ja konstat\u0113siet, ka p\u0113c lietotnes lieto\u0161anas j\u016bsu miegs ir iev\u0113rojami uzlabojies, piem\u0113ram, esat iemidzis \u0101tr\u0101k vai ret\u0101k pamodies, j\u016bs var\u0113tu noraid\u012bt nulles hipot\u0113zi. Tas liecin\u0101tu, ka lietotne patie\u0161\u0101m uzlabo j\u016bsu miegu. Bet, ja dati neuzr\u0101da nek\u0101du iev\u0113rojamu at\u0161\u0137ir\u012bbu, jums neizdosies noraid\u012bt nulles hipot\u0113zi, kas noz\u012bm\u0113, ka lietotnei, visticam\u0101k, nav nek\u0101das izm\u0113r\u0101mas ietekmes.<\/p>\n\n\n\n

Bie\u017e\u0101k sastopamie mald\u012bgie priek\u0161stati par nulles hipot\u0113zes noz\u012bm\u012bgumu<\/h3>\n\n\n\n

Nulles hipot\u0113zes noz\u012bm\u012bguma interpret\u0113\u0161ana var b\u016bt sare\u017e\u0123\u012bta, jo past\u0101v t\u0101di izplat\u012bti k\u013c\u016bdaini priek\u0161stati k\u0101 statistisk\u0101 noz\u012bm\u012bguma piel\u012bdzin\u0101\u0161ana praktiskai noz\u012bmei.<\/p>\n\n\n\n

Bie\u017e\u0101k sastopamie mald\u012bgie priek\u0161stati<\/h4>\n\n\n\n

Viens no izplat\u012bt\u0101kajiem mald\u012bgajiem priek\u0161statiem ir, ka, ja nulles hipot\u0113zi neizdodas noraid\u012bt, tas noz\u012bm\u0113, ka nulles hipot\u0113ze noteikti ir patiesa. Tas t\u0101 nav. Nulles hipot\u0113zes nenoraid\u012b\u0161ana vienk\u0101r\u0161i noz\u012bm\u0113, ka jums nav pietiekami daudz pier\u0101d\u012bjumu, lai apstiprin\u0101tu alternat\u012bvo hipot\u0113zi. <\/p>\n\n\n\n

Tas nepier\u0101da, ka nulles hipot\u0113ze ir pareiza, bet gan to, ka sav\u0101ktie dati nesniedz pietiekamu atbalstu citam secin\u0101jumam.<\/p>\n\n\n\n

V\u0113l viens p\u0101rpratums ir uzskat\u012bt, ka nulles hipot\u0113zes noraid\u012b\u0161ana autom\u0101tiski noz\u012bm\u0113, ka ieg\u016btie rezult\u0101ti ir svar\u012bgi vai v\u0113rt\u012bgi. Statistisk\u0101 noz\u012bm\u012bba noz\u012bm\u0113 tikai to, ka nov\u0113rot\u0101 ietekme ir maz ticama nejau\u0161\u012bbas d\u0113\u013c, pamatojoties uz j\u016bsu sav\u0101ktajiem datiem. Tas ne vienm\u0113r noz\u012bm\u0113, ka efekts ir liels vai praktiski noz\u012bm\u012bgs. <\/p>\n\n\n\n

Piem\u0113ram, j\u016bs varat atrast statistiski noz\u012bm\u012bgu rezult\u0101tu, kas liecina par nelielu ietekmi, kurai re\u0101laj\u0101 dz\u012bv\u0113 ir maza ietekme.<\/p>\n\n\n\n

K\u013c\u016bdu nov\u0113r\u0161ana<\/h4>\n\n\n\n

Lai izvair\u012btos no \u0161\u012bm k\u013c\u016bd\u0101m, ir svar\u012bgi atcer\u0113ties, ka statistisk\u0101 noz\u012bm\u012bba ir tikai viena no puzles da\u013c\u0101m. J\u0101\u0146em v\u0113r\u0101 ar\u012b praktiskais noz\u012bm\u012bgums, kas nosaka, vai nov\u0113rotais efekts ir pietiekami liels, lai tam b\u016btu noz\u012bme re\u0101laj\u0101 pasaul\u0113. <\/p>\n\n\n\n

Piem\u0113ram, pat tad, ja jauna m\u0101c\u012bbu metode nodro\u0161ina nelielu uzlabojumu testa rezult\u0101tos, tas var neb\u016bt pietiekami noz\u012bm\u012bgs, lai pamatotu visas m\u0101c\u012bbu programmas mai\u0146u.<\/p>\n\n\n\n

V\u0113l viens svar\u012bgs padoms ir p\u0101rliecin\u0101ties, ka nepa\u013caujaties tikai uz p-v\u0113rt\u012bb\u0101m. P-v\u0113rt\u012bbas var pal\u012bdz\u0113t jums izlemt, vai nulles hipot\u0113zi noraid\u012bt vai nenoraid\u012bt, bet t\u0101s jums neatspogu\u013co visu inform\u0101ciju. <\/p>\n\n\n\n

\u013boti svar\u012bgi ir apl\u016bkot ar\u012b ietekmes lielumu un ticam\u012bbas interv\u0101lus ap ieg\u016btajiem rezult\u0101tiem. Tie sniedz skaidr\u0101ku priek\u0161statu par to, cik ticami ir j\u016bsu ieg\u016btie rezult\u0101ti.<\/p>\n\n\n\n

Visbeidzot, izvairieties no k\u0101rdin\u0101juma manipul\u0113t ar datiem vai turpin\u0101t test\u0113\u0161anu, l\u012bdz atrodat noz\u012bm\u012bgu rezult\u0101tu. \u0160\u0101da prakse, kas paz\u012bstama k\u0101 \"p-hacking\", var novest pie k\u013c\u016bdainiem secin\u0101jumiem. T\u0101 viet\u0101 r\u016bp\u012bgi izpl\u0101nojiet savu p\u0113t\u012bjumu, sav\u0101ciet pietiekami daudz datu un veiciet pien\u0101c\u012bgu anal\u012bzi, lai p\u0101rliecin\u0101tos, ka j\u016bsu secin\u0101jumi ir pamatoti ar dro\u0161iem pier\u0101d\u012bjumiem.<\/p>\n\n\n\n

Kopsavilkum\u0101, lai gan nulles hipot\u0113zes p\u0101rbaude var b\u016bt sp\u0113c\u012bgs instruments, ir svar\u012bgi r\u016bp\u012bgi interpret\u0113t rezult\u0101tus un izvair\u012bties no bie\u017ei sastopamajiem mald\u012bgajiem priek\u0161statiem. Koncentr\u0113joties ne tikai uz statistisko noz\u012bm\u012bgumu, bet ar\u012b uz ieg\u016bto rezult\u0101tu noz\u012bmi re\u0101laj\u0101 dz\u012bv\u0113, j\u016bs pie\u0146emsiet uz datiem balst\u012btus un j\u0113gpiln\u0101kus l\u0113mumus.<\/p>\n\n\n\n

Nulles hipot\u0113ze kalpo par statistikas test\u0113\u0161anas pamatelementu, nodro\u0161inot objekt\u012bvu s\u0101kumpunktu, lai analiz\u0113tu, vai nov\u0113rot\u0101 ietekme ir re\u0101la vai nejau\u0161a. R\u016bp\u012bgi nosakot noz\u012bm\u012bguma l\u012bmeni, var l\u012bdzsvarot I un II tipa k\u013c\u016bdu risku, nodro\u0161inot ticam\u0101kus rezult\u0101tus. <\/p>\n\n\n\n

Nulles hipot\u0113zes piem\u0113ro\u0161ana ikdienas scen\u0101rijos pal\u012bdz\u0113s jums saskat\u012bt t\u0101s praktisko v\u0113rt\u012bbu, savuk\u0101rt, izvairoties no izplat\u012btiem k\u013c\u016bdainiem priek\u0161statiem un piev\u0113r\u0161ot uzman\u012bbu gan statistiskajai, gan praktiskajai noz\u012bm\u012bbai, tiks nodro\u0161in\u0101ts, ka j\u016bsu secin\u0101jumi ir j\u0113gpilni. <\/p>\n\n\n\n

Izpratne par \u0161iem j\u0113dzieniem \u013cauj ar liel\u0101ku p\u0101rliec\u012bbu pie\u0146emt uz datiem balst\u012btus l\u0113mumus.<\/p>\n\n\n\n

Lasiet ar\u012b: <\/strong>K\u0101 rakst\u012bt hipot\u0113zi<\/strong><\/a><\/p>\n\n\n\n

Augsta ietekme un liel\u0101ka j\u016bsu darba atpaz\u012bstam\u012bba<\/h2>\n\n\n\n

Izpratne par nulles hipot\u0113zes noz\u012bm\u012bgumu ir \u013coti svar\u012bga, ta\u010du efekt\u012bva rezult\u0101tu pazi\u0146o\u0161ana var b\u016bt \u013coti svar\u012bga. Mind the Graph<\/a> sniedz p\u0113tniekiem r\u012bkus, ar kuriem var izveidot vizu\u0101li saisto\u0161as infografikas un diagrammas, padarot sare\u017e\u0123\u012btus statistikas j\u0113dzienus viegl\u0101k saprotamus. Neatkar\u012bgi no t\u0101, vai m\u016bsu platforma paredz\u0113ta akad\u0113misk\u0101m prezent\u0101cij\u0101m, p\u0113tnieciskajiem darbiem vai sabiedr\u012bbas inform\u0113\u0161anai, t\u0101 pal\u012bdz jums dal\u012bties ar sav\u0101m atzi\u0146\u0101m, nodro\u0161inot skaidr\u012bbu un ietekmi. S\u0101ciet p\u0101rveidot savus datus vizu\u0101los att\u0113los jau \u0161odien.<\/p>\n\n\n\n

\""Anim\u0113ts<\/a>
Anim\u0113ts GIF, kas demonstr\u0113 pla\u0161u zin\u0101tnes jomu kl\u0101stu, ko aptver Mind the Graph<\/a>.<\/figcaption><\/figure>\n\n\n\n
\n
Ieg\u016bstiet liel\u0101ku sava darba atpaz\u012bstam\u012bbu<\/strong><\/a><\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

Uzziniet vair\u0101k par nulles hipot\u0113zes noz\u012bm\u012bgumu, t\u0101 noz\u012bmi p\u0113tniec\u012bb\u0101 un ietekmi uz statistikas rezult\u0101tiem.<\/p>","protected":false},"author":33,"featured_media":55854,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[961,982],"tags":[],"yoast_head":"\nUnderstanding Null Hypothesis Significance in Statistical Testing - Mind the Graph Blog<\/title>\n<meta name=\"description\" content=\"Learn about null hypothesis significance, its role in research, and how it impacts statistical findings.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mindthegraph.com\/blog\/lv\/null-hypothesis-significance\/\" \/>\n<meta property=\"og:locale\" content=\"lv_LV\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Understanding Null Hypothesis Significance in Statistical Testing - 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