Denominator in specificity is

Ans. is 'd' i.e., True negative plus false positive Skewed distribution (deviation) o Skewed distribution means data is assymmetrically distributed around the mean with either large number of low values & less high values, or large number of high values & less number of low values, o So, the distribution curve has a tail towards the values which are in lower number. o Depending upon the values (high or low) skewed distribution can be divided into two types - Negative skewed (left handed) distribution Large number of high values (right sided values) with less no. of low values (left sided values). So, the tail is on left side. Called negative skewed because tail is in negative direction (left side). Mode > median > mean Positive skewed (right handed) distribution Large number of low values (left sided values) with few high values (right sided values). So, the tail is on right side. Called positived skewed because tail is in positive direction (right side). Mean > median > mode o In this question median (140 mm Hg) is greater than the mean (130 mm of Hg) - negatively skewed (left handed) dispersion. Normal distribution Positively skewed (rt. Handed) distribution Negatively skewed (left handed) deviation y No tail y Bell shaped curve : Gaussian distribution y Mean = Median = Mode y Tail is towards right side y Large no of low scores, small no of high scores y Mean > Median > Mode y Tail is towards left side y Large no of high scores, small no of low scores y Mode > Median > Mean o Sidedness of the skewed distribution is towards the side of tail. For example right sided skewed deviation means the tail is towards the right. o Facts to remember the relation between mean, media & mode (see above figure) :- Mean is right of the median under right skew, and left of the median under left skew. Mode is left of the median under right skew, and right of the median under left skew.