{"id":29079,"date":"2023-08-18T06:23:21","date_gmt":"2023-08-18T09:23:21","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/construct-in-research-copy\/"},"modified":"2024-12-05T15:47:43","modified_gmt":"2024-12-05T18:47:43","slug":"hypothesis-testing","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/lv\/hipotezu-parbaude\/","title":{"rendered":"Hipot\u0113\u017eu p\u0101rbaude: Hipot\u0113\u017eu hipot\u0113zes: principi un metodes."},"content":{"rendered":"

Hipot\u0113\u017eu p\u0101rbaude ir pamatinstruments, ko izmanto zin\u0101tniskos p\u0113t\u012bjumos, lai apstiprin\u0101tu vai noraid\u012btu hipot\u0113zes par popul\u0101cijas parametriem, pamatojoties uz izlases datiem. T\u0101 nodro\u0161ina struktur\u0113tu sist\u0113mu hipot\u0113zes statistisk\u0101s noz\u012bm\u012bbas nov\u0113rt\u0113\u0161anai un secin\u0101jumu izdar\u012b\u0161anai par popul\u0101cijas patieso raksturu. Hipot\u0113\u017eu p\u0101rbaudi pla\u0161i izmanto t\u0101d\u0101s jom\u0101s k\u0101 biolo\u0123ija, psiholo\u0123ija, ekonomika un in\u017eenierzin\u0101tnes.<\/strong> lai noteiktu jaunu \u0101rst\u0113\u0161anas meto\u017eu efektivit\u0101ti, izp\u0113t\u012btu attiec\u012bbas starp main\u012bgajiem lielumiem un pie\u0146emtu uz datiem balst\u012btus l\u0113mumus. Tom\u0113r, neraugoties uz hipot\u0113\u017eu test\u0113\u0161anas noz\u012bm\u012bgumu, hipot\u0113\u017eu test\u0113\u0161ana var b\u016bt sare\u017e\u0123\u012bts temats, lai to izprastu un pareizi piem\u0113rotu.<\/p>\n\n\n\n

\u0160aj\u0101 rakst\u0101 m\u0113s sniegsim ievadu hipot\u0113\u017eu p\u0101rbaud\u0113, tostarp t\u0101s m\u0113r\u0137i, testu veidus, veicamos so\u013cus, bie\u017e\u0101k pie\u013caut\u0101s k\u013c\u016bdas un lab\u0101ko praksi. Neatkar\u012bgi no t\u0101, vai esat ies\u0101c\u0113js vai pieredz\u0113jis p\u0113tnieks, \u0161is raksts kalpos k\u0101 v\u0113rt\u012bgs ce\u013cvedis, lai apg\u016btu hipot\u0113\u017eu test\u0113\u0161anu sav\u0101 darb\u0101.<\/p>\n\n\n\n

Ievads hipot\u0113\u017eu p\u0101rbaud\u0113<\/strong><\/h2>\n\n\n\n

Hipot\u0113zes p\u0101rbaude ir statistikas instruments, ko parasti izmanto p\u0113tniec\u012bb\u0101, lai noteiktu, vai ir pietiekami daudz pier\u0101d\u012bjumu, lai apstiprin\u0101tu vai noraid\u012btu hipot\u0113zi. T\u0101 ietver hipot\u0113zes formul\u0113\u0161anu par popul\u0101cijas parametru, datu v\u0101k\u0161anu un datu anal\u012bzi, lai noteiktu hipot\u0113zes patiesuma varb\u016bt\u012bbu. T\u0101 ir b\u016btiska zin\u0101tnisk\u0101s metodes sast\u0101vda\u013ca, un to izmanto visda\u017e\u0101d\u0101kaj\u0101s jom\u0101s.<\/p>\n\n\n\n

Hipot\u0113\u017eu p\u0101rbaudes proces\u0101 parasti tiek izvirz\u012btas divas hipot\u0113zes: nulles hipot\u0113ze un alternat\u012bv\u0101 hipot\u0113ze. Nulles hipot\u0113ze ir apgalvojums, ka starp diviem main\u012bgajiem lielumiem nav b\u016btiskas at\u0161\u0137ir\u012bbas vai starp tiem nav saist\u012bbas, savuk\u0101rt alternat\u012bv\u0101 hipot\u0113ze liecina par saist\u012bbas vai at\u0161\u0137ir\u012bbas esam\u012bbu. P\u0113tnieki v\u0101c datus un veic statistisko anal\u012bzi, lai noteiktu, vai nulles hipot\u0113zi var noraid\u012bt par labu alternat\u012bvajai hipot\u0113zei.<\/p>\n\n\n\n

Hipot\u0113\u017eu p\u0101rbaude tiek izmantota, lai pie\u0146emtu l\u0113mumus, pamatojoties uz datiem, un ir svar\u012bgi izprast \u0161\u0101 procesa pamat\u0101 eso\u0161os pie\u0146\u0113mumus un ierobe\u017eojumus. Lai nodro\u0161in\u0101tu rezult\u0101tu precizit\u0101ti un ticam\u012bbu, ir b\u016btiski izv\u0113l\u0113ties atbilsto\u0161us statistiskos testus un izlases lielumu, un tas var b\u016bt sp\u0113c\u012bgs instruments p\u0113tniekiem, lai apstiprin\u0101tu savas teorijas un pie\u0146emtu uz pier\u0101d\u012bjumiem balst\u012btus l\u0113mumus.<\/p>\n\n\n\n

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Hipot\u0113\u017eu testu veidi<\/strong><\/h2>\n\n\n\n

Hipot\u0113\u017eu p\u0101rbaudi var iedal\u012bt div\u0101s kategorij\u0101s: vienas izlases hipot\u0113\u017eu p\u0101rbaude un divu izlases hipot\u0113\u017eu p\u0101rbaude. Apl\u016bkosim tuv\u0101k katru no \u0161\u012bm kategorij\u0101m:<\/p>\n\n\n\n

Viena parauga hipot\u0113\u017eu p\u0101rbaudes<\/strong><\/h3>\n\n\n\n

Vienas izlases hipot\u0113zes p\u0101rbaud\u0113 p\u0113tnieks v\u0101c datus no vienas popul\u0101cijas un sal\u012bdzina tos ar zin\u0101mu v\u0113rt\u012bbu vai hipot\u0113zi. Nulles hipot\u0113ze parasti paredz, ka starp popul\u0101cijas vid\u0113jiem r\u0101d\u012bt\u0101jiem un zin\u0101mo v\u0113rt\u012bbu vai hipot\u0113zi nav b\u016btiskas at\u0161\u0137ir\u012bbas. Tad p\u0113tnieks veic statistisko testu, lai noteiktu, vai nov\u0113rot\u0101 at\u0161\u0137ir\u012bba ir statistiski noz\u012bm\u012bga. Da\u017ei piem\u0113ri vienas izlases hipot\u0113zes p\u0101rbaudei ir \u0161\u0101di:<\/p>\n\n\n\n

Viena parauga t-tests:<\/strong> \u0160o testu izmanto, lai noteiktu, vai izlases vid\u0113jais lielums b\u016btiski at\u0161\u0137iras no hipot\u0113tisk\u0101 popul\u0101cijas vid\u0113j\u0101 lieluma.<\/p>\n\n\n\n

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Caur statstest.b-cdn.net<\/a><\/em><\/figcaption><\/figure>\n\n\n\n
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Viena parauga z-tests:<\/strong> \u0160o testu izmanto, lai noteiktu, vai izlases vid\u0113jais lielums b\u016btiski at\u0161\u0137iras no hipot\u0113tisk\u0101 popul\u0101cijas vid\u0113j\u0101 lieluma, ja ir zin\u0101ma popul\u0101cijas standartnovirze.<\/p>\n\n\n\n

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Caur statstest.b-cdn.net<\/a><\/em><\/figcaption><\/figure>\n\n\n\n
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Divu paraugu hipot\u0113\u017eu p\u0101rbaudes<\/strong><\/h3>\n\n\n\n

Divu izlases hipot\u0113\u017eu p\u0101rbaud\u0113 p\u0113tnieks v\u0101c datus no div\u0101m da\u017e\u0101d\u0101m popul\u0101cij\u0101m un sal\u012bdzina tos sav\u0101 starp\u0101. Nulles hipot\u0113ze parasti paredz, ka starp ab\u0101m popul\u0101cij\u0101m nav b\u016btiskas at\u0161\u0137ir\u012bbas, un p\u0113tnieks veic statistisko testu, lai noteiktu, vai nov\u0113rot\u0101 at\u0161\u0137ir\u012bba ir statistiski noz\u012bm\u012bga. Da\u017ei divu izlases hipot\u0113\u017eu testu piem\u0113ri ir \u0161\u0101di:<\/p>\n\n\n\n

Neatkar\u012bgu paraugu t-tests:<\/strong> <\/em>\u0160o testu izmanto, lai sal\u012bdzin\u0101tu divu neatkar\u012bgu paraugu vid\u0113jos lielumus un noteiktu, vai tie b\u016btiski at\u0161\u0137iras viens no otra.<\/p>\n\n\n\n

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Caur statstest.b-cdn.net<\/a><\/em><\/figcaption><\/figure>\n\n\n\n
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P\u0101ru paraugu t-tests: <\/strong>\u0160o testu izmanto, lai sal\u012bdzin\u0101tu divu radniec\u012bgu izlasju vid\u0113jos r\u0101d\u012bt\u0101jus, piem\u0113ram, vienas un t\u0101s pa\u0161as p\u0113t\u0101mo personu grupas pirmstesta un p\u0113cp\u0101rbaudes rezult\u0101tus.<\/p>\n\n\n\n

Att\u0113ls: <\/strong>https:\/\/statstest.b-cdn.net\/wp-content\/uploads\/2020\/10\/Paired-Samples-T-Test.jpg<\/p>\n\n\n\n

Kopum\u0101 vienas izlases hipot\u0113\u017eu testus izmanto, lai p\u0101rbaud\u012btu hipot\u0113zes par vienu popul\u0101ciju, bet divu izlases hipot\u0113\u017eu testus izmanto, lai sal\u012bdzin\u0101tu divas popul\u0101cijas. Piem\u0113rotais tests ir atkar\u012bgs no datu veida un p\u0113t\u0101m\u0101 jaut\u0101juma.<\/p>\n\n\n\n

Hipot\u0113\u017eu p\u0101rbaudes posmi<\/strong><\/h2>\n\n\n\n

Hipot\u0113zes p\u0101rbaude ietver virkni darb\u012bbu, kas pal\u012bdz p\u0113tniekiem noteikt, vai ir pietiekami daudz pier\u0101d\u012bjumu, lai hipot\u0113zi apstiprin\u0101tu vai noraid\u012btu. \u0160os so\u013cus kopum\u0101 var iedal\u012bt \u010detr\u0101s kategorij\u0101s:<\/p>\n\n\n\n

Hipot\u0113zes formul\u0113\u0161ana<\/strong><\/h3>\n\n\n\n

Pirmais hipot\u0113\u017eu p\u0101rbaudes solis ir formul\u0113t nulles hipot\u0113zi un alternat\u012bvo hipot\u0113zi. Nulles hipot\u0113ze parasti paredz, ka starp diviem main\u012bgajiem nav b\u016btiskas at\u0161\u0137ir\u012bbas, savuk\u0101rt alternat\u012bv\u0101 hipot\u0113ze liecina, ka past\u0101v sakar\u012bba vai at\u0161\u0137ir\u012bba. Pirms datu v\u0101k\u0161anas ir svar\u012bgi formul\u0113t skaidras un p\u0101rbaud\u0101mas hipot\u0113zes.<\/p>\n\n\n\n

Datu v\u0101k\u0161ana<\/strong><\/h3>\n\n\n\n

Otrais solis ir sav\u0101kt attiec\u012bgus datus, kurus var izmantot hipot\u0113\u017eu p\u0101rbaudei. Datu v\u0101k\u0161anas process ir r\u016bp\u012bgi j\u0101izstr\u0101d\u0101, lai nodro\u0161in\u0101tu, ka izlase ir reprezentat\u012bva attiec\u012bb\u0101 uz interes\u0113jo\u0161o popul\u0101ciju. Izlases lielumam j\u0101b\u016bt pietiekami lielam, lai ieg\u016btu statistiski pamatotus rezult\u0101tus.<\/p>\n\n\n\n

Datu anal\u012bze<\/strong><\/h3>\n\n\n\n

Tre\u0161ais solis ir datu anal\u012bze, izmantojot atbilsto\u0161us statistiskos testus. Testa izv\u0113le ir atkar\u012bga no datu rakstura un p\u0113t\u0101m\u0101 jaut\u0101juma. Statistisk\u0101s anal\u012bzes rezult\u0101ti sniegs inform\u0101ciju par to, vai nulles hipot\u0113zi var noraid\u012bt par labu alternat\u012bvajai hipot\u0113zei.<\/p>\n\n\n\n

Rezult\u0101tu interpret\u0113\u0161ana<\/strong><\/h3>\n\n\n\n

P\u0113d\u0113jais solis ir interpret\u0113t statistisk\u0101s anal\u012bzes rezult\u0101tus. P\u0113tniekam j\u0101nosaka, vai rezult\u0101ti ir statistiski noz\u012bm\u012bgi un vai tie apstiprina vai noraida hipot\u0113zi. P\u0113tniekam j\u0101\u0146em v\u0113r\u0101 ar\u012b p\u0113t\u012bjuma ierobe\u017eojumi un rezult\u0101tu iesp\u0113jam\u0101s sekas.<\/p>\n\n\n\n

Bie\u017e\u0101k sastopam\u0101s k\u013c\u016bdas hipot\u0113\u017eu p\u0101rbaud\u0113<\/strong><\/h2>\n\n\n\n

Hipot\u0113zes p\u0101rbaude ir statistikas metode, ko izmanto, lai noteiktu, vai ir pietiekami daudz pier\u0101d\u012bjumu, lai apstiprin\u0101tu vai noraid\u012btu konkr\u0113tu hipot\u0113zi par popul\u0101cijas parametru, pamatojoties uz datu izlasi. Hipot\u0113\u017eu p\u0101rbaud\u0113 var rasties divu veidu k\u013c\u016bdas:<\/p>\n\n\n\n

I tipa k\u013c\u016bda: <\/strong>Tas notiek, ja p\u0113tnieks noraida nulles hipot\u0113zi, lai gan t\u0101 ir patiesa. I tipa k\u013c\u016bdu sauc ar\u012b par viltus pozit\u012bvu rezult\u0101tu.<\/p>\n\n\n\n

II tipa k\u013c\u016bda:<\/strong> <\/em>Tas notiek tad, ja p\u0113tniekam neizdodas noraid\u012bt nulles hipot\u0113zi, lai gan t\u0101 ir nepatiesa. II tipa k\u013c\u016bdu sauc ar\u012b par viltus negat\u012bvu k\u013c\u016bdu.<\/p>\n\n\n\n

Lai mazin\u0101tu \u0161\u012bs k\u013c\u016bdas, ir svar\u012bgi r\u016bp\u012bgi izstr\u0101d\u0101t un veikt p\u0113t\u012bjumu, izv\u0113l\u0113ties atbilsto\u0161us statistiskos testus un pareizi interpret\u0113t rezult\u0101tus. P\u0113tniekiem ar\u012b j\u0101apzin\u0101s sava p\u0113t\u012bjuma ierobe\u017eojumi un, izdarot secin\u0101jumus, j\u0101\u0146em v\u0113r\u0101 iesp\u0113jamie k\u013c\u016bdu avoti.<\/p>\n\n\n\n

Nulles un alternat\u012bv\u0101s hipot\u0113zes<\/strong><\/h2>\n\n\n\n

Hipot\u0113\u017eu p\u0101rbaud\u0113 ir divu veidu hipot\u0113zes: nulles hipot\u0113ze un alternat\u012bv\u0101 hipot\u0113ze.<\/p>\n\n\n\n

Nulles hipot\u0113ze<\/strong><\/h3>\n\n\n\n

Nulles hipot\u0113ze (H0) ir apgalvojums, kas paredz, ka starp diviem main\u012bgajiem nav b\u016btiskas at\u0161\u0137ir\u012bbas vai saist\u012bbas. T\u0101 ir noklus\u0113juma hipot\u0113ze, kas tiek uzskat\u012bta par patiesu, kam\u0113r nav pietiekamu pier\u0101d\u012bjumu, lai to noraid\u012btu. Nulles hipot\u0113zi bie\u017ei raksta k\u0101 apgalvojumu par vienl\u012bdz\u012bbu, piem\u0113ram, \"A grupas vid\u0113jais r\u0101d\u012bt\u0101js ir vien\u0101ds ar B grupas vid\u0113jo r\u0101d\u012bt\u0101ju\".<\/p>\n\n\n\n

Alternat\u012bv\u0101 hipot\u0113ze<\/strong><\/h3>\n\n\n\n

Alternat\u012bv\u0101 hipot\u0113ze (Ha) ir apgalvojums, kas liecina, ka starp diviem main\u012bgajiem past\u0101v b\u016btiska at\u0161\u0137ir\u012bba vai saist\u012bba. T\u0101 ir hipot\u0113ze, kuru p\u0113tnieks ir ieinteres\u0113ts p\u0101rbaud\u012bt. Alternat\u012bvo hipot\u0113zi bie\u017ei raksta k\u0101 apgalvojumu par nevienl\u012bdz\u012bbu, piem\u0113ram, \"A grupas vid\u0113jais lielums nav vien\u0101ds ar B grupas vid\u0113jo lielumu\".<\/p>\n\n\n\n

Nulles un alternat\u012bv\u0101 hipot\u0113ze ir savstarp\u0113ji papildino\u0161as un savstarp\u0113ji izsl\u0113dzo\u0161as. Ja nulles hipot\u0113ze tiek noraid\u012bta, tiek pie\u0146emta alternat\u012bv\u0101 hipot\u0113ze. Ja nulles hipot\u0113zi nevar noraid\u012bt, alternat\u012bv\u0101 hipot\u0113ze netiek apstiprin\u0101ta.<\/p>\n\n\n\n

Ir svar\u012bgi atz\u012bm\u0113t, ka nulles hipot\u0113ze ne vienm\u0113r ir patiesa. Tas ir vienk\u0101r\u0161i apgalvojums, kas paredz, ka starp p\u0113t\u0101majiem main\u012bgajiem nav b\u016btiskas at\u0161\u0137ir\u012bbas vai saist\u012bbas. Hipot\u0113\u017eu p\u0101rbaudes m\u0113r\u0137is ir noteikt, vai ir pietiekami pier\u0101d\u012bjumi, lai noraid\u012btu nulles hipot\u0113zi par labu alternat\u012bvajai hipot\u0113zei.<\/p>\n\n\n\n

Noz\u012bm\u012bguma l\u012bmenis un P v\u0113rt\u012bba<\/strong><\/h2>\n\n\n\n

Hipot\u0113\u017eu p\u0101rbaud\u0113 noz\u012bm\u012bguma l\u012bmenis (alfa) ir I tipa k\u013c\u016bdas varb\u016bt\u012bba, proti, nulles hipot\u0113zes noraid\u012b\u0161ana, ja t\u0101 paties\u012bb\u0101 ir patiesa. Zin\u0101tniskaj\u0101 p\u0113tniec\u012bb\u0101 visbie\u017e\u0101k izmantotais noz\u012bm\u012bguma l\u012bmenis ir 0,05, kas noz\u012bm\u0113, ka past\u0101v 5% iesp\u0113ja pie\u013caut I tipa k\u013c\u016bdu.<\/p>\n\n\n\n

P v\u0113rt\u012bba ir statistisks r\u0101d\u012bt\u0101js, kas nor\u0101da nov\u0113roto rezult\u0101tu vai v\u0113l ekstr\u0113m\u0101ku rezult\u0101tu ieg\u016b\u0161anas varb\u016bt\u012bbu, ja nulles hipot\u0113ze ir patiesa. Tas ir pier\u0101d\u012bjumu sp\u0113ka m\u0113rs pret nulles hipot\u0113zi. Neliela p v\u0113rt\u012bba (parasti maz\u0101ka par izv\u0113l\u0113to noz\u012bm\u012bguma l\u012bmeni 0,05) liecina, ka ir sp\u0113c\u012bgi pier\u0101d\u012bjumi pret nulles hipot\u0113zi, savuk\u0101rt liela p v\u0113rt\u012bba liecina, ka nav pietiekami daudz pier\u0101d\u012bjumu, lai noraid\u012btu nulles hipot\u0113zi.<\/p>\n\n\n\n

Ja p v\u0113rt\u012bba ir maz\u0101ka par noz\u012bm\u012bguma l\u012bmeni (p alfa), tad nulles hipot\u0113ze netiek noraid\u012bta un alternat\u012bv\u0101 hipot\u0113ze netiek apstiprin\u0101ta.<\/p>\n\n\n\n

Ja v\u0113laties viegli saprotamu kopsavilkumu par noz\u012bm\u012bguma l\u012bmeni, to atrad\u012bsiet \u0161aj\u0101 rakst\u0101: Viegli saprotams kopsavilkums par noz\u012bm\u012bguma l\u012bmeni<\/a>.<\/p>\n\n\n\n

Ir svar\u012bgi atz\u012bm\u0113t, ka statistisk\u0101 noz\u012bm\u012bba ne vienm\u0113r noz\u012bm\u0113 praktisko noz\u012bm\u012bgumu vai svar\u012bgumu. Neliela at\u0161\u0137ir\u012bba vai saist\u012bba starp main\u012bgajiem var b\u016bt statistiski noz\u012bm\u012bga, bet var neb\u016bt praktiski noz\u012bm\u012bga. Turkl\u0101t statistisk\u0101 noz\u012bm\u012bba cita starp\u0101 ir atkar\u012bga no izlases lieluma un efekta lieluma, un t\u0101 j\u0101interpret\u0113 p\u0113t\u012bjuma pl\u0101na un p\u0113t\u012bjuma jaut\u0101juma kontekst\u0101.<\/p>\n\n\n\n

Jaudas anal\u012bze hipot\u0113\u017eu p\u0101rbaudei<\/strong><\/h2>\n\n\n\n

Jaudas anal\u012bze ir statistikas metode, ko izmanto hipot\u0113\u017eu p\u0101rbaud\u0113, lai noteiktu izlases lielumu, kas nepiecie\u0161ams, lai ar noteiktu ticam\u012bbas pak\u0101pi atkl\u0101tu konkr\u0113tu ietekmes lielumu. Statistisk\u0101 testa jauda ir varb\u016bt\u012bba pareizi noraid\u012bt nulles hipot\u0113zi, ja t\u0101 ir nepatiesa, vai varb\u016bt\u012bba izvair\u012bties no II tipa k\u013c\u016bdas.<\/p>\n\n\n\n

Jaudas anal\u012bze ir svar\u012bga, jo t\u0101 pal\u012bdz p\u0113tniekiem noteikt atbilsto\u0161u izlases lielumu, kas nepiecie\u0161ams, lai sasniegtu v\u0113lamo jaudas l\u012bmeni. P\u0113t\u012bjum\u0101 ar mazu jaudu var neizdoties atkl\u0101t patieso ietekmi, kas noved pie II tipa k\u013c\u016bdas, savuk\u0101rt p\u0113t\u012bjum\u0101 ar lielu jaudu ir liel\u0101ka iesp\u0113ja atkl\u0101t patieso ietekmi, kas \u013cauj ieg\u016bt prec\u012bz\u0101kus un ticam\u0101kus rezult\u0101tus.<\/p>\n\n\n\n

Lai veiktu jaudas anal\u012bzi, p\u0113tniekiem ir j\u0101nor\u0101da v\u0113lamais jaudas l\u012bmenis, noz\u012bm\u012bguma l\u012bmenis, ietekmes lielums un izlases lielums. Efekta lielums ir p\u0113t\u0101mo main\u012bgo lieluma starp\u012bbas vai sakar\u012bbas lieluma m\u0113rs, un to parasti apr\u0113\u0137ina, pamatojoties uz iepriek\u0161\u0113jiem p\u0113t\u012bjumiem vai izm\u0113\u0123in\u0101juma p\u0113t\u012bjumiem. P\u0113c tam, veicot ietekmes anal\u012bzi, var noteikt vajadz\u012bgo izlases lielumu, lai sasniegtu v\u0113lamo ietekmes l\u012bmeni.<\/p>\n\n\n\n

Jaudas anal\u012bzi var izmantot ar\u012b retrospekt\u012bvi, lai noteiktu pabeigta p\u0113t\u012bjuma jaudu, pamatojoties uz izlases lielumu, efekta lielumu un noz\u012bm\u012bguma l\u012bmeni. Tas var pal\u012bdz\u0113t p\u0113tniekiem nov\u0113rt\u0113t savu secin\u0101jumu sp\u0113ku un noteikt, vai ir nepiecie\u0161ami papildu p\u0113t\u012bjumi.<\/p>\n\n\n\n

Kopum\u0101 jaudas anal\u012bze ir svar\u012bgs hipot\u0113\u017eu test\u0113\u0161anas instruments, jo pal\u012bdz p\u0113tniekiem izstr\u0101d\u0101t p\u0113t\u012bjumus, kas ir pietiekami jaud\u012bgi, lai noteiktu patieso ietekmi un izvair\u012btos no II tipa k\u013c\u016bd\u0101m.<\/p>\n\n\n\n

Bajesa hipot\u0113\u017eu p\u0101rbaude<\/strong><\/h2>\n\n\n\n

Bejas hipot\u0113\u017eu p\u0101rbaude ir statistikas metode, kas \u013cauj p\u0113tniekiem nov\u0113rt\u0113t pier\u0101d\u012bjumus par un pret konkur\u0113jo\u0161\u0101m hipot\u0113z\u0113m, pamatojoties uz nov\u0113roto datu varb\u016bt\u012bbu katras hipot\u0113zes gad\u012bjum\u0101, k\u0101 ar\u012b katras hipot\u0113zes iepriek\u0161\u0113jo varb\u016bt\u012bbu. At\u0161\u0137ir\u012bb\u0101 no klasisk\u0101s hipot\u0113\u017eu test\u0113\u0161anas, kas koncentr\u0113jas uz nulles hipot\u0113\u017eu noraid\u012b\u0161anu, pamatojoties uz p-v\u0113rt\u012bb\u0101m, Bejas hipot\u0113\u017eu test\u0113\u0161ana nodro\u0161ina nians\u0113t\u0101ku un informat\u012bv\u0101ku pieeju hipot\u0113\u017eu test\u0113\u0161anai, \u013caujot p\u0113tniekiem kvantitat\u012bvi noteikt pier\u0101d\u012bjumu sp\u0113ku par un pret katru hipot\u0113zi.<\/p>\n\n\n\n

Bajesa hipot\u0113\u017eu p\u0101rbaud\u0113 p\u0113tnieki s\u0101k ar iepriek\u0161\u0113ju varb\u016bt\u012bbas sadal\u012bjumu katrai hipot\u0113zei, pamatojoties uz eso\u0161aj\u0101m zin\u0101\u0161an\u0101m vai uzskatiem. P\u0113c tam vi\u0146i atjaunina iepriek\u0161\u0113jo varb\u016bt\u012bbas sadal\u012bjumu, pamatojoties uz nov\u0113roto datu varb\u016bt\u012bbu katrai hipot\u0113zei, izmantojot Bejas teor\u0113mu. Rezult\u0101t\u0101 ieg\u016btais posteriorais varb\u016bt\u012bbas sadal\u012bjums atspogu\u013co katras hipot\u0113zes varb\u016bt\u012bbu, \u0146emot v\u0113r\u0101 nov\u0113rotos datus.<\/p>\n\n\n\n

Vienas hipot\u0113zes pier\u0101d\u012bjumu stiprumu sal\u012bdzin\u0101jum\u0101 ar citu hipot\u0113zi var kvantitat\u012bvi noteikt, apr\u0113\u0137inot Bajesa koeficientu, kas ir nov\u0113roto datu varb\u016bt\u012bbas attiec\u012bba starp vienu hipot\u0113zi un citu hipot\u0113zi, kas sv\u0113rta ar to iepriek\u0161\u0113j\u0101m varb\u016bt\u012bb\u0101m. Bajesa koeficients, kas liel\u0101ks par 1, nor\u0101da uz pier\u0101d\u012bjumiem par labu vienai hipot\u0113zei, bet Bajesa koeficients, kas maz\u0101ks par 1, nor\u0101da uz pier\u0101d\u012bjumiem par labu otrai hipot\u0113zei.<\/p>\n\n\n\n

Bejas hipot\u0113\u017eu p\u0101rbaudei ir vair\u0101kas priek\u0161roc\u012bbas sal\u012bdzin\u0101jum\u0101 ar klasisko hipot\u0113\u017eu p\u0101rbaudi. Pirmk\u0101rt, t\u0101 \u013cauj p\u0113tniekiem atjaunin\u0101t savus iepriek\u0161\u0113jos uzskatus, pamatojoties uz nov\u0113rotajiem datiem, kas var novest pie prec\u012bz\u0101kiem un uzticam\u0101kiem secin\u0101jumiem. Otrk\u0101rt, t\u0101 nodro\u0161ina informat\u012bv\u0101ku pier\u0101d\u012bjumu m\u0113r\u012bjumu nek\u0101 p-v\u0113rt\u012bbas, kas tikai nor\u0101da, vai nov\u0113rotie dati ir statistiski noz\u012bm\u012bgi iepriek\u0161 noteikt\u0101 l\u012bmen\u012b. Visbeidzot, t\u0101 var piel\u0101got sare\u017e\u0123\u012btus mode\u013cus ar vair\u0101kiem parametriem un hipot\u0113z\u0113m, kurus var b\u016bt gr\u016bti analiz\u0113t, izmantojot klasisk\u0101s metodes.<\/p>\n\n\n\n

Kopum\u0101 Bejas hipot\u0113\u017eu p\u0101rbaude ir sp\u0113c\u012bga un elast\u012bga statistikas metode, kas var pal\u012bdz\u0113t p\u0113tniekiem pie\u0146emt pamatot\u0101kus l\u0113mumus un izdar\u012bt prec\u012bz\u0101kus secin\u0101jumus par ieg\u016btajiem datiem.<\/p>\n\n\n\n

Izveidojiet zin\u0101tniski prec\u012bzu infografiku da\u017eu min\u016b\u0161u laik\u0101<\/strong><\/h2>\n\n\n\n

Mind the Graph<\/a> platforma ir jaud\u012bgs r\u012bks, kas pal\u012bdz zin\u0101tniekiem viegli izveidot zin\u0101tniski prec\u012bzu infografiku. Pateicoties intuit\u012bvajam interfeisam, piel\u0101gojam\u0101m veidn\u0113m un pla\u0161ai zin\u0101tnisko ilustr\u0101ciju un ikonu bibliot\u0113kai, Mind the Graph \u013cauj p\u0113tniekiem viegli izveidot profesion\u0101la izskata grafikas, kas efekt\u012bvi inform\u0113 pla\u0161\u0101ku auditoriju par vi\u0146u atkl\u0101jumiem.<\/p>\n\n\n\n

<\/div>\n\n\n
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\"\"<\/a><\/figure><\/div>\n\n\n
<\/div>","protected":false},"excerpt":{"rendered":"

Uzziniet vair\u0101k par hipot\u0113\u017eu p\u0101rbaudi. Testu veidi, bie\u017e\u0101k sastopam\u0101s k\u013c\u016bdas, lab\u0101k\u0101 prakse un daudz kas cits. Ide\u0101li piem\u0113rots visiem p\u0113tniekiem.<\/p>","protected":false},"author":35,"featured_media":29081,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[978,974,961],"tags":[],"yoast_head":"\nHypothesis Testing: Principles and Methods<\/title>\n<meta name=\"description\" content=\"Learn about hypothesis testing. The types of tests, common errors, best practices, and more. 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