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ThiQar college of Medicine Family & Community medicine dept. Biostatistics Lecture Third stage by: Dr. Muslim N. Saeed December 15th ,2016 Mathematical Presentation of Data Measures of Dispersion Quintiles, Centiles & Quartiles A quintile is a value below which a certain proportion of observations occurred in the ordered set of data values. A centiles are values, in a series of observations, arranged in ascending order of magnitude, which divide the distribution into 100 equal parts (10th Percentile, 3rd, 97th, and the 50th (median) percentile). 3 Quintiles, Centiles & Quartiles Quartiles are the observations in an array that divide the distribution into four equal parts. lower Quartile: the value below which 25% of observations lie in an ordered array 2nd quartile = Median = 50th percentile Upper Quartile = 75th percentile Interquartile Range: is the middle 50% of all observations 4 Distance travelled in Miles Villages Distance travelled in miles Village (1) 6.5 6.6 6.7 6.8 7.1 7.3 7.4 7.7 7.7 7.7 Village (2) 4.2 5.4 5.8 6.2 6.7 7.7 7.7 8.5 9.3 10 Measures of Central Tendency Village (1) Village (2) Mean 7.15 7.15 Median 7.2 7.2 Mode 7.7 7.7 Dot plots of Distance Travelled Village (1) Village (2) Even though the measures of center tendency are all the same, it is obvious from the dot plots of each group of data that there are some differences in the ‘spread’ (or variation) of the data Consider these means for weekly candy bar consumption Mean = {12, 2, 0, 14, 10, 9, 5, 4} = (12+2+0+14+10+9+5+4)/8 =7 Mean = {7, 8, 6, 7, 7, 6, 8, 7} = (7+8+6+7+7+6+8+7)/8 =7 Measures of Dispersion As well as measures of central tendency we need measures of how variable the data are. Dispersion is a key concept in statistical thinking. The basic question being asked is how much do the scores deviate around the Mean? Measures of Dispersion; These are The range The Variance Standard Deviation Standard Error Coefficient of Variation Measures of Dispersion; The Range The range is an important measurement Range Highest Value Lowest Value However, they do not give much indication of the spread of observations about the mean Simple to calculate Easy to understand It neglect all values in the center and depend on the extreme value, extreme value are dependent on sample size It is not based on all observations It is not amenable for further mathematic treatment should be used in conjunction with other measures of variability Variance: The mean sum of squares of the deviation from the mean. e.g. if the data is: 1,2,3,4,5. The mean for these data=3 the difference of each value in the set from the mean: 1-3= -2 2-3= -1 3-3= 0 4-3= 1 5-3= 2 The summation of the differences =zero Summation of square of the differences is not zero The Variance Variance can never be a negative value All observations considered are The problem with the Another formula for the variance variance is the squared unit The standard deviation is the square root of the variance The standard deviation measured the variability between observations in the sample or the population from the mean of that sample or that population. The unit is not squared SD is the most widely used measure of dispersion Standard Error of the mean(SE) It measures the variability or dispersion of the sample mean from population mean It is used to estimate the population mean, and to estimate differences between populations means SE=SD/√ n Coefficient of variation (CV): It expresses the SD as a percentage of the mean CV= (S /mean) x 100 (mean of the sample) It has no unit It is used to compare dispersion in two sets of data especially when the units are different It measures relative rather than absolute variation It takes in consideration all values in the set Exercise A sample of 11 patients admitted to a psychiatric ward experienced the following lengths of stay, calculate measures of dispersion. No. Length No. length 1 29 7 28 2 14 8 14 3 11 9 18 4 24 10 22 5 14 11 14 6 14 total