The exact value within +-2 SD in Standard normal curve
Ans. c (95.4) (Ref. Methods in Bio-statistics, by B. K. Mahajan 6th edition, p. 79; Park PSM 22nd/pg.792)NORMAL DISTRIBUTION# When large number of observations of any variable such as height, blood pressure and pulse rate are taken at random to make it a representative sample, a frequency distribution table is prepared. Then some observations are above the mean and other below the mean. Normally almost half of the observations lie above and half below the mean and all observations are symmetrically distributed on each side of the mean.# A distribution of this shape is called normal distribution.# When no. of observations are very large and group interval is very small, the frequency polygon tends to lose its angulations giving place to a smooth curve known as frequency curve. Such a frequency curve drawn for normal distribution is called as normal curve (Gaussian curve).Important characteristics of normal curve are:# Shape of the distribution resembles a bell and is symmetric around midpoint.# At the center of the distribution, which is peaked, all the three measures of central tendency, namely, mean, mode & median coincide.# Normal curve never touches the baseline.# The area under the curve between any two points which correspond to the number of observations between any two values of the variate can be found out in terms of a relationship between the mean and the standard deviations.# Mean +-1 S.D. covers 68.27% of the observations.# Mean +- 2 S.D. covers 95.45% of the observations.# Mean +- 3 S.D. covers 99.73% of the observations.# Mean +- 1.96 S.D. covers 95% of the observations.# Mean +- 2.68 S.D. covers 99% of the observations.Statistical distributionMeasures of central tendencyMean = (sum of values) / (total number of values).Median = middle value of a list of data sorted from least to greatest.Mode = most common value.If there is an even number of values, the median will be the average of the middle two valuesMeasures of dispersionStandard deviation = how much variability exists from the mean in a set of values.Standard error of the mean = an estimation of how much variability exists between the sample mean and the true population mean.s= SD; n = sample sizeSEM = s/'h.SEM |as n |Normal distributionGaussian, also called bell-shaped. Mean = median = modeNormal diributions BimodalSuggests two different populations (e.g., metabolic palymorphism such as fast vs. slow acetylators; suicide rate by age).Positive skewTypically, mean > median > mode Asymmetry with longer tail on night.Negative skewTypically, mean < median < mode Asymmetry with longer tail on left.Statistical hypotheses Null (H0) Alternative (H})Hypothesis of no difference (e.g., there is no association between the disease and the risk factor in the population). Hypothesis of some difference (e.g., there is some association between the disease and the risk factor in the population).
98.8
97.6
95.4
94
Biostatistics