Statistics-Class-9-Opt.Maths

Author:
AMBIK BARAL
Topic:
Statistics

Introduction

Quartile Deviation (Q.D.)
  • The difference between the upper quartile and the lower quartile is called INTERQUARTILE DEVIATION.
  • The semi-interquartile range of the data is known as Quartile Deviation(Q.D.)
  • Here, inter-quartile range
  • Semi- interquartile range
  • Coefficient of quartile deviation
For ungrouped data

User Guideline

Dear learner,
  • Click Green coloured buttons for table.
  • Click Cyan coloured buttons for solution steps.
  • To change data, click on check box named Ambik .
  • Again click check box .
  • Again click Green coloured buttons for table.
  • Again click Cyan coloured buttons for solution steps.
  • We can use this applet to check our answer steps and to teach our students.

Quartile Deviation - Individual Series

Quartile Deviation - Discrete Series

Mean Deviation The average of the absolute values of the deviation of each item from mean, median or mode is known as a mean deviation. It is also known as average deviation. It is denoted by M.D. Calculation of Mean Deviation For continuous series
  1. M.D. from mean
  2. M.D. from mean
  3. M.D. rom median
  4. M.D. from median
  5. Coefficient of M.D. from mean
  6. Coefficient of M.D. from median Where,

Mean Deviation From Mean - Individual Series

Mean Deviation From Median - Individual Series

Mean Deviation From Mean - Discrete Series

Mean Deviation From Median - Discrete Series

Standard deviation is the positive square root of the arithmetic mean of the square of deviations of given data taken from mean. It is also known as "Root mean square deviation". It is denoted by Greek letter (read as sigma). It is considered as the best measure of dispersion because:
  1. It's value is based on all the observations.
  2. Deviation of each term is taken from the central value.
  3. All algebraic sign are also considered
Calculation of Standard Deviation 1. Actual mean method: Standard Deviation , [For individual series] Standard deviation(σ), [For discrete series] 2. Direct method: Standard deviation [ For individual series ] Standard deviation(σ) [ For discrete series ] 3. Assumed mean method ( or short - cut method ) Standard deviation [ For discrete series ] Standard deviation(σ) , [ For continuous series ] where, , Coefficient of variation (C.V.) The relative measure of standard deviation is known as the coefficient of standard deviation and is defined by Coefficient of standard deviation If the coefficient of standard deviation is multiplied by 100, then it is known as coefficient of variation. Coefficient of variation is denoted by C.V. and is calculated as:    Greater the coefficient of variation, greater will be the variation and less will be the consistency or uniformity. Less the C.V., greater will be the consistency or uniformity. For the consistency or uniformity of distribution, we use the C.V. So, C.V. is used to compare given distributions. Variance: The square of standard deviation(σ) is called variation. It is given by       

S.D. AND C.V. - ACTUAL MEAN - INDIVIDUAL SERIES

S.D. AND C.V. - ACTUAL MEAN - DISCRETE SERIES

S.D. AND C.V. - DIRECT METHOD - INDIVIDUAL SERIES

S.D. AND C.V. - DIRECT METHOD -DISCRETE SERIES

S.D. AND C.V. - SHORT CUT METHOD - INDIVIDUAL SERIES

S.D. AND C.V. - SHORT CUT METHOD - DISCRETE SERIES

Finding the Interquartile Range

Practice finding the interquartile range of data sets with this interactive activity featuring visual hints and immediate feedback.

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