Essay About Central Tendency Measure And Large Number Of Data

Nestle Case
Name: Mohammad Abdul Razek Mohammad MashalyQ1:The central tendency measure:It is the measure to summarize a large number of data with one value which is the central value.The dispersion measures:It is the measures which measure the distance between data (observations) and the central point.The first quartile:It is the value on a distance 25% from the beginning after arranging the data in an ascending order.The continuous random variable:It is measurable variable whose value is changing in a short time and contains many values within interval, such as the weights and heights of some students or the ages of them.The discrete variables:It is countable variable whose value isn’t changing in short period and has no interval such as no. of absence dates or no. of child in our family.The third quartile:It is the value on a distance 75% from the beginning after arranging the data in an ascending order.Q2:(False) because in the skewed data there should be extreme values so the best central measure is the median because Mean is affected by extreme values and the best dispersion measure is the inter-quartile range because it excludes the extreme values.(False) because in the standard deviation we avoided the negative sign by squaring the values then having the square root of the sum as follow:S= √)*∑ (Xi-)2[pic 1][pic 2](False) we always depend on the value of the coefficient variation in the relative dispersion measure in comparing the homogeneity between different groups because in the Variance we may have different unit measure and there will be difference in Mean values. (False) The first quartile is the value on a distance 25% from the beginning after arranging the data in an ascending order.(False) the data is skewed to the right because the mean is taking all values including the extreme values into consideration so if it is greater than the median with big difference then it should be skewed to the right.(False) The first quartile is the value on a distance 25% from the beginning after arranging the data in an ascending order.(False) dispersion measures are for quantitative data only and not for descriptive data.(False) if the data doesn’t contain any extreme value then we have to apply stem and leaf first to check if it is skewed or symmetric.Q3:Symmetric data.The mode can assume more than one value, the Mean calculated for quantitative data only.The absolute dispersion measure is to measure the distance between data (observations) and the central point but the relative dispersion measure is to compare the homogeneity between different groups.The four sampling techniques are:Simple random sample. (if the individuals in the population are equally likely)Stratified random sample. (if the population are divided to different groups which are homogenous inside each and heterogeneous between them)  Systematic random sample.(if the variables are periodic)Cluster random sample. (if the population understudy is huge or extended)In the symmetric data all measures are too close in its values but in the skewed data they have different values and depend on the range of the data and they are as below:Because of: The difference in measure unit.The difference in Mean values.The Box-Plot role is to check if there is any extreme value or not, but the role of Stem-and-Leaf is to determine if the data is symmetric or skewed.