2.2 histograms & frequency distributions for quantative data Flashcards
frequency distribution for continuous quantitative data
we divide the data into class because they have no natural categories
classes
intervals of equal width that cover all values that observed in the data set
lower class limit
smallest value that appears in the class
upper class limit
largest value that can appear in the class
class width
difference between consecutive lower class limits
guidelines for choosing classes
every observation must fall into one of the classes, classes cant overlap, classes have to have equal width, there should be no gaps between classes even if there are no observations in a class, it needs to be included in the frequency districution
constructing a frequency distribution
- choose a class width 2. pick a lower class limit for the first class which should be a convenient # that is slightly less than the minimum data value, 3. compute the lower limit for the second class by adding the class width to the lower limit for the first class, 4. compute the lower limits for each of the remaining classes by adding the class width to the lower limit fo the preceding class. stop when the largest data value is included in a class 5. count the number of observations in each class and construct the frequency distribution
relative frequency distribution aka frequency distribution
frequency/ sum of all frequencies
histogram
a bar graph that displays the relative frequency distribution with its width equal to the class width
frequency vs relative frequency
the vertical axis for frequency is a whole number and for relative its a decimal
choosing the number of classes
not too little and not too much; too few lacks details and too much obscures the main features of the data
histograms on ti-84 plus
enter data in L1; press 2nd,Y=, then 1 to access plot 1 menu. select On and the histogram plot type; press zoom, 9 to view the plot
skewed to the right, or positively skewed
a histogram with a long right-hand tail
skewed to the left, or negatively skewed
histogram with a long left- hand tail
symmetric
if the histograms’ right have is a mirror image of its left half