# IMC Exam 2 1-4

 The flashcards below were created by user eriklnelson on FreezingBlue Flashcards. examples of non-random sampling quota samplingpanellingpostal and telephone surveys continuous data data that can take any value whatsoever discrete data data that can only take on specific values, such as money, which changes value in whole units categorical data data classified into a number of distinct categories ordinal data data that has been classified into a number of distinct ranked categories frequency distribution & relative f d group the data into bands of specific values and display the frequency of occurrence of each band-relative show proportions or percentages rather than frequencies cumulative f d & relative cum f d can be used to show the number of items with a value less than or equal to a given figure.relative show the proportion or % with a value less than or equal to a given figure lorenz curve visual comparison of the 2 cumulative frequency distributions histogram displays the number or % of items falling within a given band through the AREA of a bar arithmetic mean-not necessarily an observed value-greatly affected by extremes Population-for raw data fi = 1 for each item-for grouped data, use the midpoints-for sample standard deviation, devide by (n-1) rather than n Geometric mean-useful for COMPOUNDING relationships-UNDERSTATES the mean compared to the arithmetic mean value =  value =  value = formulas for median, range and intertquartile range = median -UNAFFECTED by extremes range = highest - lowest -considers ONLY EXTREMES interquartile range = -UNAFFECTED by extremes mode most frequently occurring item-must be observed value-UNAFFECTED by extremes perfect symmetrical population mean = median = mode positively skewed distribution mode