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Statistics - Notes, Concept and All Important Formula

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=ni=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=ni=1fxiN, where N=ni=1fi

(iii) By short cut method :

Let di=xia

¯x=a+ΣfidiN, where a is assumed mean.

(iv) By step deviation method:

Let ui=dih=xiah

¯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=ni=1wixini=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(xiˉx)=0,Σfi(xiˉx)=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 :

The median of a series is the value of middle term of the series when the values are written in ascending order. Therefore median, divides an arranged series into two equal parts.

Formulae of median:

(i) For ungrouped distribution : Let n be the number of variate in a series then
Median=[(n+12)th term, (when n is odd ) Mean of (n2)th  and (n2+1)th terms, (when n is even) 

(ii) For ungrouped freq. dist. : First we prepare the cumulative frequency (c.f.) column and Find value of N then
Median=[(N+12)th term, (when N is odd ) Mean of (N2)th  and (N2+1)th  terms, (when N is even) 

(iii) For grouped freq. dist : Prepare c.f. column and find value of N2 then find the class which contain value of c.f. is equal or just greater to N/2, this is median class
 Median =+(N2F)f×h
where - lower limit of median class
f - freq. of median class
F - c . f. of the class preceding median class
h - Class interval of median class



3. MODE :

In a frequency distribution the mode is the value of that variate which have the maximum frequency.

Method for determining mode :
(i) For ungrouped dist.: The value of that variate which is repeated maximum number of times.
(ii) For ungrouped freq. dist. : The value of that variate which have maximum frequency.
(iii) For grouped freq. dist.: First we find the class which have maximum frequency, this is model calss
 Mode =+f0f12f0f1f2×h
where - lower limit of model class
f0 freq. of the model class
f1 freq. of the class preceding model class
f2 freq. of the class succeeding model class 
h - class interval of model class



4. RELATION BETWEEN MEAN, MEDIAN AND MODE :

In a moderately asymmetric distribution following is the relation between mean, median and mode of a distribution. It is known as impirical formula.
Mode =3 Median - 2 Mean

Note: (i) Median always lies between mean and mode
(ii) For a symmetric distribution the mean, median and mode coincide.



5. MEASURES OF DISPERSION :

The dispersion of a statistical distribution is the measure of deviation of its values about the their average (central) value. Generally the following measures of dispersion are commonly used.
(i) Range
(ii) Mean deviation
(iii) Variance and standard deviation

(i) Range : The difference between the greatest and least values of variate of a distribution, are called the range of that distribution. If the distribution is grouped distribution, then its range is the difference between upper limit of the maximum class and lower limit of the minimum class.

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 =ni=1|xiA|n (for ungrouped dist.)

Mean deviation =ni=1fi|xiA|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(xiˉx)2nσ2x=Σx2inˉx2=Σx2in(Σxin)2σ2d=Σd2in(Σdin)2, where di=xia

(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)=λ2Var(xi)

Var(axi+b)=a2Var(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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