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NORMAL DISTRIBUTION

mahlah avatar
mahlah
24 diapositives · 385 Views · Sep 14, 2014

This article explores the concepts of normal distribution and variability in biological data. It covers the characteristics of the normal curve, including its bell shape, symmetry, and how it relates to mean and standard deviation. We discuss types of variability, including biological, individual, and sampling variability, as well as measures such as range, mean deviation, and standard deviation. The article also highlights the importance of these measures in understanding data dispersion, determining variability limits, and analyzing differences in biological research.

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  1. NORMAL DISTRIBUTION • Normal curve • Smooth, Bell shaped, bilaterally symmetrical curve • Total area is =1 • Mean is 0 • Standard deviation=1 • Mean, median, mode coincide. • Area between X±1 SD=68.3% • X±2SD=95.5% • X±3SD=99.9%

  2. Normal distribution

  3. NORMAL DISTRIBUTION

  4. POSITIVELY SKEWED

  5. NEGATIVELY SKEWED

  6. VARIABILITY • Biological data are variable • Two measurements in man are variable • Cure rate are not equal but variable • Height of students in same age group is not same but variable • Height of students in one area is not same as compared to other place but variable • Variability is essentially a normal character • It is a biological phenomenon.

  7. TYPES OF VARIABILITY • Biological variability • That occurs within certain accepted biological limits. It occurs by chance. • Individual variability • Periodical variability • Class, group or category variability • Sampling variability or sampling error

  8. REAL VARIABILITY • When the difference between two readings or observations or values of classes or samples is more than the defined limits in the universe, it is said to be real variability. The cause is external factors. e.g. significant difference in cure rates may be due to a better drug but not due to a chance.

  9. Experimental variability • Errors or differences due to materials, methods, procedures employed in the study or defects in the techniques involved in the experiment. • Observer error • Instrumental error • Sampling error.

  10. MEASURES OF VARIABILITY • How individual observations are dispersed around the mean of a large series. • Measures of variability of individual observations. • Range • Mean deviation • Standard deviation • Coefficient of variation

  11. Measures of variability of sample • Standard error of mean • Standard error of difference between two means • Standard error of proportion • Standard error of difference between two proportions • Standard error of correlation coefficient • Standard error of regression coefficient.

  12. RANGE • Range defines the normal limits of a biological characteristic. • It is the simplest measure of dispersion • Usually employed as a measure of variability in medical practice • It indicates the distance between the lowest and highest. • It ignores all observations except two extreme values on which it is based. • Normal range covers observations falling in 95% confidence limits.

  13. examples Observ. Range Mean SD Age mrge 9-18 14.16 1.13 Menst.cycle 21-35 28 2.00 Pulse rate 55-90 72 3.5 Wt. at birth 1.8-4.5 3.05 .39 Syst.BP 90-150 115 12.00

  14. MEAN DEVIATION • It the average of the deviations from the arithmetic mean. • M.D=∑ (X-¯X) • n • Example: • 83,75,81,79,71,90,75,95,77,94.

  15. MEAN DEVIATION

  16. STANDARD DEVIATION • Most frequently used measure of deviation • “Root – means—square--deviation” • Calculate the mean • Find the difference of each observation from the mean • Square the differences of observations from the mean • Add the squared values to get sum of squares • Divide this sum by number of observations to get mean –squared deviation, called variance • Find the square root of this variance to get root mean squared deviation.

  17. USES OF S.D. 1. Summarizes the deviations of a large distribution from mean in one figure used as a unit of variation 2. Indicates whether the variation of difference of an individual from the mean is by chance i.e. natural or real i.e. defines the limits of variability 3. Helps in finding standard error which determines whether the difference b/w means of two similar samples is by chance or real. 4. Find suitable size of sample

  18. SD • Calculate SD from following weights of students. • 40,45,50,55,60,65,70,75,80 • Mean = 540/ 9=60 Kg • Calculate mean from every observation

  19. SD

  20. COEFFICIENT OF VARIATION • Used to compare relative variability • Used to compare variability of one of one character into two groups having different magnitude of values • CV= SD X 100 mean

  21. CV • Persons Mean Ht SD Adults 160Cm 10Cm Children 60 Cm 5 Cm CV of adults=10/160 X 100=6.25% CV of children = 5/60 X 100=8.33%

  22. SD • 142.5 3 162.5 136 • 145 8 165 93 • 147.5 15 167.5 42 • 150 45 170 16 • 152.5 90 172.5 6 • 155 155 175 2 • 157.5 194 M=160 • 160 (M) 195 SD=5

  23. SD