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# Important Formulas in Statistics for Economics | Class 11

OR

### Chapter: Measures of Central Tendency: Arithmetic Mean

#### 1. Arithmetic Mean

i) Individual Series:

• Direct Method

Where,

N = Total Number of Items

• Short-cut Method

Where,

A = Assumed Mean

d = X – A (deviations of variables from assumed mean)

∑d = ∑(X – A) (sum of deviations of variables from assumed mean)

N = Total Number of Items

• Step Deviation Method

Where,

A = Assumed Mean

d = X – A (deviations of variables from assumed mean)

(Step Deviations; i.e., deviations divided by common factor)

C = Common Factor

N = Total Number of Items

ii) Discrete Series:

• Direct Method

Where,

∑fX = Sum of the product of variables with the respective frequencies

∑f = Total Number of Items

• Short-cut Method

Where,

A = Assumed Mean

d = X – A (deviations of variables from assumed mean)

∑fd = Sum of the product of deviations (d) with the respective frequencies

∑f = Total Number of Items

• Step Deviation Method

Where,

A = Assumed Mean

d = X – A (deviations of variables from assumed mean)

(Step Deviations; i.e., deviations divided by common factor)

C = Common Factor

∑f = Total Number of Items

iii) Continuous Series:

• Direct Method

Where,

∑fm = Sum of the product of mid-points with the respective frequencies

∑f = Total Number of Items

• Short-cut Method

Where,

A = Assumed Mean

d = m – A (deviations of mid-points from assumed mean)

∑fd = Sum of the product of deviations (d) with the respective frequencies

∑f = Total Number of Items

• Step Deviation Method

Where,

A = Assumed Mean

d = m – A (deviations of mid-points from assumed mean)

(Step Deviations; i.e., deviations divided by common factor)

C = Common Factor

∑f = Total Number of Items

#### 2. Charlier’s Accuracy Check

• For Short-cut Method

∑f(d + 1) = ∑fd + ∑f

• For Step Deviation Method

#### 3. Missing Value

i) Individual Series:

Where,

X1, X2, ………………… Xn-1 = Given Values

Xn = Missing Value

ii) Discrete Series:

iii) Continuous Series:

#### 4. Combined Mean

Where,

N1 = Number of Items of first distribution

N2 = Number of Items of second distribution

#### 6. Weighted Arithmetic Mean

Where,

∑WX = Sum of product of items and respective weights

∑W = Sum of the weights

### Chapter: Measures of Central Tendency: Median and Mode

#### 1. Median

Where,

N = Number of Items

• If the Number of Items is Even

ii) Discrete Series:

Where,

N = Total of Frequency

Find out the value of  Locate the cumulative frequency which is equal to higher than  and then find the value corresponding to this cf. This value will be the Median value of the series.

iii) Continuous Series:

Where,

l1 = lower limit of the median class

c.f. = cumulative frequency of the class preceding the median class

f = simple frequency of the median class

i = class size of the median group or class

#### 2. Quartiles

i) Individual Series:

Where,

N = Number of Items

ii) Discrete Series:

Where,

N = Cumulative Frequency

iii) Continuous Series:

#### 3. Mode

i) Individual Series:

Mode is the value which occurs the largest number of times.

ii) Discrete Series:

In the case of regular and homogeneous frequencies, and single maximum frequency, Mode is the value corresponding to the highest frequency. Otherwise, the grouping method is used.

iii) Continuous Series:

Where,

Z = Value of Mode

= lower limit of the modal class

= frequency of modal class

f_0      = frequency of pre-modal class

= frequency of the next higher class or post-modal class

i = size of the modal group

#### 4. Relationship between Mean, Median, and Mode

Mode = 3 Median – 2 Mean

### Chapter: Measures of Dispersion

#### 1. Range

Range(R) = Largest Item(L) – Smallest Item(S)

#### 2. Coefficient of Range

In Individual Series, the largest and smallest item is taken from the given observations.

In Discrete Series, the largest and smallest item is taken from the given frequencies.

In Continuous Series, the first method to calculate coefficient of range is to take the difference between the upper and lower limit of the highest and lowest class interval respectively. The second method is to take the difference between the mid-points of the highest class limit and lowest class limit.

#### 3. Quartile Deviation

Where,

Q3 = Upper Quartile (Size of  item)

Q1 = Lower Quartile (Size of  item)

#### 4. Coefficient of Quartile Deviation

Where,

Q3 = Upper Quartile (Size of  item)

Q1 = Lower Quartile (Size of  item)

#### 5. Mean Deviation

i) Individual Series:

• Mean Deviation from Mean

• Mean Deviation from Median

• Alternate Method

Where,

∑|D| = Sum of absolute deviations from Assumed Mean

A = Assumed Mean

∑fB = Number of Values from actual mean

∑fA = Number of values below actual mean including actual mean

N = Number of Observations

ii) Discrete Series:

• Mean Deviation from Mean

• Mean Deviation from Median

Where,

M = Median

iii) Continuous Series:

• Mean Deviation from Mean

• Mean Deviation from Median

Where,

M = Median

#### 6. Coefficient of Mean Deviation

• Coefficient of Mean Deviation from Mean

• Coefficient of Mean Deviation from Median

#### 7. Standard Deviation

Where,

σ = Standard Deviation

∑x2 = Sum total of the squares of deviations from the actual mean

N = Number of pairs of observations

Or

Where,

σ = Standard Deviation

∑X2 = Sum total of the squares of observations

= Actual Mean

N = Number of Observations

Where,

σ = Standard Deviation

∑d = Sum total of deviations from assumed mean

∑d2 =  Sum total of squares of deviations

N = Number of pairs of observations

ii) Discrete Series:

Where,

σ = Standard Deviation

∑fx2 = Sum total of the squared deviations multiplied by frequency

N = Number of pairs of observations

Or

Where,

σ = Standard Deviation

∑fx2 = Sum total of the squared deviations multiplied by frequency

= Actual Mean

N = Number of Observations

Or

Where,

σ = Standard Deviation

∑fd = Sum total of deviations multiplied by frequencies

∑d2 =  Sum total of the squared deviations multiplied by frequencies

N = Number of pairs of observations

Where,

σ = Standard Deviation

= Sum total of the squared step deviations multiplied by frequencies

=  Sum total of step deviations multiplied by frequencies

N = Number of pairs of observations

iii) Continuous Series:

σ =

OR

Where,

σ = Standard Deviation

= Actual Mean

∑fx2 = Sum total of the deviations of every mid-value of the class intervals multiplied by frequency

N = Number of pair of observations

σ =

σ = Standard Deviation

∑fd2 = Sum total of the squared deviations multiplied by frequency

∑fd = Sum total of deviations multiplied by frequency

N = Number of pair of observations

σ = Standard Deviation

= Sum total of the squared step deviations multiplied by frequency

= Sum total of step deviations multiplied by frequency

C = Common Factor

N = Number of pair of observations

#### 9. Combined Standard Deviation

Where,

= Combined Standard Deviation of two groups

=Standard Deviation of first group

= Standard Deviation of second group

= Combined Arithmetic Mean of two groups

= Arithmetic Mean of first group

= Arithmetic Mean of second group

= Number of Observations in the first group

= Number of Observations in the second group

Variance = σ2

#### 11. Coefficient of Variation

Where,

C.V. = Coefficient of Variation

σ = Standard Deviation

= Arithmetic Mean

### Chapter: Correlation

#### 2. Karl Pearson’s Coefficient of Correlation

Or,

Or,

Or,

Or,

Where,

N = Number of Pair of Observations

x = Deviation of X series from Mean

y = Deviation of Y series from Mean

= Standard Deviation of X series

= Standard Deviation of Y series

r = Coefficient of Correlation

Where,

N = Number of pair of observations

∑dx = Sum of deviations of X values from assumed mean

∑dy = Sum of deviations of Y values from assumed mean

∑dx2 = Sum of squared deviations of X values from assumed mean

∑dy2 = Sum of squared deviations of Y values from assumed mean

∑dxdy = Sum of the products of deviations dx and dy

Where,

N = Number of pair of observations

= Sum of deviations of X values from assumed mean

= Sum of deviations of Y values from assumed mean

= Sum of squared deviations of X values from assumed mean

= Sum of squared deviations of Y values from assumed mean

= Sum of the products of deviations  and

#### 3. Karl Pearson’s Coefficient of Correlation and Covariance

With Covariance formula, the formula for r (coefficient of correlation) can be written as:

Or,

Or,

Or,

#### 4. Spearman’s Rank Correlation Coefficient

• When ranks are not equal

Where,

rk = Coefficient of rank correlation

D = Rank differences

N = Number of variables

• When ranks are equal

Here,

m1, m2, ……. are the number of times a value has repeated in the given X, Y, …….. series respectively.

### Chapter: Index Number

#### 1. Unweighted or Simple Index Numbers

Where,

P01 = Index Number of the Current Year

∑p1 = Total of the current year’s price of all commodities

∑p0 = Total of the base year’s price of all commodities

#### 2. Weighted Index Numbers

Here,

P01 = Price Index of the current year

p0 = Price of goods at base year

q0 = Quantity of goods at base year

p1 = Price of goods at the current year

Here,

P01 = Price Index of the current year

p0 = Price of goods in the base year

q1 = Quantity of goods in the base year

p1 = Price of goods in the current year

Here,

P01 = Price Index of the current year

p0 = Price of goods in the base year

q1 = Quantity of goods in the base year

p1 = Price of goods in the current year

Fisher’s Method is considered the Ideal Method for Constructing Index Numbers.

#### 3. Methods of Constructing Consumer Price Index

• Aggregate Expenditure Method

• Family Budget Method