STATISTICS
MEASURES OF CENTRAL TENDENCY:
An average value or a central value of a distribution is the value of variable which is representative of the entire distribution, this representative value are called the measures of central tendency. Generally there are following five measures of central tendency:
(a) Mathematical average
(i) Arithmetic mean. (ii) Geometric mean. (iii) Harmonic mean
(b) Positional average
(i) Median. (ii) Mode
1. ARITHMETIC MEAN/MEAN:
(i) For ungrouped dist.: If x1,x2,……xnx1,x2,……xn are n values of variate x then their mean ˉx is defined as
¯x=x1+x2+…..+xnn=n∑i=1xin
⇒Σxi=n¯x
(ii) For ungrouped and grouped freq. dist.: If x1,x2,….xn are values of variate with corresponding frequencies f1,f2,…fn then their mean is given by
¯x=f1x1+f2x2+…+fnxnf1+f2+…+fn=n∑i=1fxiN, where N=n∑i=1fi
(iii) By short cut method :
Let di=xi−a
∴¯x=a+ΣfidiN, where a is assumed mean.
(iv) By step deviation method:
Let ui=dih=xi−ah
∴¯x=a+(ΣfiiiN)h
(v) Weighted mean : If w1,w2,……wn are the weights assigned to the values x1,x2,……xn respectively then their weighted mean is defined as
Weighted mean =w1x1+w2x2+…..+wnxnw1+…..+wn=n∑i=1wixin∑i=1wi
(vi) Combined mean : If ¯x1 and ¯x2 be the means of two groups having n1 and n2 terms respectively then the mean (combined mean) of their composite group is given by combined mean
=n1¯x1+n2¯x2n1+n2
If there are more than two groups then,
combined mean =n1¯x1+n1¯x2+n3¯x3+…n1+n2+n3+…
(vii) Properties of Mean:
- Sum of deviations of variate about their mean is always zero i.e. Σ(xi−ˉx)=0,Σfi(xi−ˉx)=0
- Sum of square of deviations of variate about their mean is minimum i.e. Σ(xi−¯x)2 is minimum
- If ˉx is the mean of variate xi then mean of (xi+λ) is ˉx+λ, mean of (λx1)=λˉx, mean of (axi+b) is aˉx+b (where λ,a,b are constant)
- Mean is independent of change of assumed mean i.e. it is not effected by any change in assumed mean.
2. MEDIAN :
Formulae of median:
3. MODE :
4. RELATION BETWEEN MEAN, MEDIAN AND MODE :
5. MEASURES OF DISPERSION :
Also, coefficient of range = difference of extreme values sum of extreme values
(ii) Mean deviation (M.D.) : The mean deviation of a distribution is, the mean of absolute value of deviations of variate from their statistical average (Mean, Median, Mode).
If A is any statistical average of a distribution then mean deviation about A is defined as
Mean deviation =n∑i=1|xi−A|n (for ungrouped dist.)
Mean deviation =n∑i=1fi|xi−A|N (for freq. dist.)
Note :- It is minimum when taken about the median
Coefficient of Mean deviation = Mean deviation A
(where A is the central tendencyabout which Mean deviation is taken)
(iii) Variance and standard deviation : The variance of a distribution is, the mean of squares of deviation of variate from their mean. It is denoted by σ2 or var(x).
The positive square root of the variance are called the standard deviation. It is denoted by σ or S.D.
Hence standard deviation =+√ variance
Formulae for variance :
(i) for ungrouped dist. :
σ2x=Σ(xi−ˉx)2nσ2x=Σx2in−ˉx2=Σx2in−(Σxin)2σ2d=Σd2in−(Σdin)2, where di=xi−a
(ii) For freq. dist.:
σ2x=∑fi(xi−¯x)2N
σ2x=Σf1x2iN−(ˉx)2=Σfix2iN−(ΣfixiN)2σ2d=Σfid2iN−(ΣfidiN)2σ2u=h2[Σfiu2iN−(ΣfiuiN)2] where ui=dih
(iii) Coefficient of S.D. =σ¯x
Coefficient of variation =σ¯x×100 (in percentage)
Note :- σ2=σ2x=σ2d=h2σ2u
6. MATHEMATICAL PROPERTIES OF VARIANCE :
Var.(xi+λ)=Var(xi)
Var⋅(λxi)=λ2⋅Var(xi)
Var(axi+b)=a2⋅Var(xi)
where λ,a,b, are constant
If means of two series containing n1,n2 terms are ¯x1,¯x2 and their variance's are σ21,σ22 respectively and their combined mean is ˉx then the variance σ2 of their combined series is given by following formula
σ2=n1(σ21+d21)+n2(σ22+d22)(n1+n2) where di=¯x1−¯x,d2=¯x2−¯x
i.e. σ2=n1σ21+n2σ22n1+n2+n1n2(n1+n2)2(¯x1−¯x2)2
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