CH2

CH2

1. Terms

   • Frequency (count)
   • Relative Frequency (proportion of the frequency of the total)
   • Cumulative frequency

2. Side Notes:

   • Data is an observations of each individual for a group
   • Understanding the type of data is important to understand how to express the data (descriptive statistic)
   • Visual representations of the distribution helps people understand how the data is distributed and how the data behaves

3. Types of Data:

   • Categorical/Qualitative universiate data
   • Numerical/Quantitative univariate data
     • Discrete data: can only be distinct/separate values
     • Continuous data: can take any value in some intervals
   • Both Numerical and Categorical data can be:
     • Univariate data set
     • Bivariate data set
     • Multivariate data set

4. Histogram

   • Steps:
     • Step 1: Draw a horizontal axis and place tick marks corresponding to the class boundaries
     • Step 2: Draw a vertical axis and place tick marks corresponding to frequency. Label each axis
     • Step 3: Draw a rectangle above each class with height equal to frequency
   • Side Notes:
     • A histogram is a graphical representation of a distribution, a plot of frequency or relative frequency versus class interval
     • A histogram tells us about the shape, center and variability of the distribution, and allows us to quickly identify any outliers.
     • Histogram should not be used to answer questions alone
     • If the histogram has unequal class widths, then do not use the frequency or relative frequency for the y-axis
     • To fix this issue set the area of each rectangle equal to the relative frequency
     • The reason why we fix a histogram that has unequal widths because we want to use the distribution (cant be created with unequal widths histogram) and identify the shape
   • Types of distribution
     • Unimodal
     • Biomodal
     • Multimodal
     • Symmetrical
     • Unsymmetrical/Skewed
       • Positively/Right Skewed
       • Negative/Left skewed