3. Мода және медиана
Статистикада қорытындылаушы көрсеткіштермен қатар өзгермелі белгілердің бөлінуін қосымша сипаттайтын құрылымдық орта шамалар да қолданылады. Оған мода мен медиана жатады.
Мода дегеніміз статистикалық қатарлардың ішінде ең жиі кездесетін белгінің үлкен шамасы, яғни өзгермелі сандық қатарда жиіліктің үлкен мәні жатқан белгі.
Егер статистикалық қатардың белгісі бүтін санмен берілсе , сол берілген белгінің ең үлкен жиілік мәні жатқан қатар мода болып саналады.
Егер статистикалық қатарлар белгілерінің ең үлкен жиілік мәні бірдей екі сандық көрсеткішпен берілсе, онда модалық белгі екеу болады. Ал жиілік мәндері бірдей бірнеше белгі берілетін болса , онда модалық көрсеткіш болмайды.
Қатар белгілері деңгей аралықты шамамен берілсе, онда еңбірінші ең үлкен жиілігі бар қатар анықталады, одан кейін модалық белгінің деңгей аралығының айырмасы есептеледі, ол модалық қатардың үлкен мәнінен кіші мәнін алғанға тең болады.
Статистикада мода Мо -әрпімен белгіленеді және деңгей аралықты қатар берілген болса, келесі формуламен анықталады:
f Mo –fMo-1
Mo=XMo+dMo ---------------------------------------------- ,мұндағы,
( f Mo –fMo-1 )+( f Mo –fMo+1 )
XMo- модалық қатардың деңгей аралығының кіші мәні;
dMo –модалық қатардың деңгей аралығының айырмасы;
f Mo –модалық қатардың жиілігі;
fMo-1—модалық қатардың алдыңғы қатар жиілігі;
fMo+1- модалық қатардан кейінгі қатар жиілігі.
Мысалы, келесідей мәліметтер негізінде моданы анықтау керек.
Күндік өндіру
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Тігіншілер саны
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Жиіліктің жиналған қосындысы (S)
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50-60
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20
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20
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60-70
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30
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50
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70-80
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60
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110
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80-90
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50
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160
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90-100
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40
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200
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Мода 70-80, яғни үшінші қатарда жатаыр. Себебі, бұл қатарда жиіліктің ең үлкен мәні жатыр.
60-30 30
Мо=70+10--------------------- =70+10 --------- = 77,5
(60-30)+(60-50) 40
Медиана дегеніміз статистикалық қатардың ортасында жатқан белгі. Ол қатарды тең етіп екіге бөледі және оның екі жағындағы белгілердің сандық бірліктері бірдей болады.
Медиана статистикада Ме- әрпімен белгіленеді. Егер қатардың белгісі бүтін санмен берілсе, медиананы анықтау үшін белгінің рет санына бірді қосып, шыққан қосындыны екіге бөлеміз, ол келесі формуламен анықталады:
![](data:image/png;base64,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) , мұндағы, n-қатар саны![](data:image/png;base64,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)
Егер қатар белгісі бүтін санмен және жиілікпен берілсе, медиананы есептеу үшін жиіліктің жинақталған қосындысын тең екіге бөліп, шыққан көрсеткішке ½-ді қосамыз.
f Me 1
Me= ------------ + -----.
2 2
Егер қатар белгісі деңгей аралықты шамамен берілсе, онда алдымен ![](data:image/png;base64,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) медианалық қатарды анықтаймыз. Ол үшін әрбір жиілікке келесісін қоса отырып, жинақталған жиілік қосындысын есептейміз.
Деңгей аралықты қатардан медиананы есептеу үшін келесі формула қолданылады:
![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAASAAAAIACAIAAACtpSZ8AAAFn0lEQVR4nO3TMQ0AMAzAsB3lT7lDEU2abAR5Mrt7gMa8DoCfGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg5DBIGQwCBkMQgaDkMEgZDAIGQxCBoOQwSBkMAgZDEIGg9AFv7YK/kzIBpMAAAAASUVORK5CYII=) , мұндағы,
XMе- медианалық қатардың деңгей аралығының кіші мәні;
dMе –медианалық қатардың деңгей аралығының айырмасы;
S –медианалық қатардың қосындысы;
S Mе-1—медианалық қатардың алдыңғы қатардағы жинақталған жиілік қосындысы.
Мысалы, жоғарыда берілген мәліметтер бойынша медиананы есептеуге болады. Мұнда медиана үшінші қатарда жатыр.
200/2-50 50
Ме=70+10------------------------- =70+10------ =78,3
60 60
Достарыңызбен бөлісу: |