Day 01: STA205 - Introduction to Statistical Methods

Later:

• Statistics as numbers ("descriptive statistics")

  Definition 1: Statistics are numbers calculated from a collection of data

  "Data": items of information, either numerical or non-numerical (quantitative versus qualitative)

  Examples of statistics:

  • baseball "averages"
  • percent, proportion of NKU students that graduated from the same high school as one of their parents
  • average height of NKU students
  • percentages of students preferring each type of soft drinks offered on NKU campus

• Statistics as science ("inferential statistics")

  Definition 2: Statistics is a science that deals with the collection and summary of information that is then used to make interpretations, decisions, estimates, predictions, etc.

  Examples:

  • Polio Vaccine example from text
  • Calling elections before most voters have even voted
  • Heights of NKU students

• Section 2.1: Two types of data
  1. Qualitative data -- categorical
     • Yes, No, Maybe
     • Pepsi, Coke, RC, 7-Up -- the uncola
  2. Quantitative data -- numerical data that "measures" some quantity
     • ages of students as freshmen
     • number of people in a line at the supermarket
     • time it takes to complete an exam

• Section 2.3: Histograms (2.2 is barcharts, for qualitative data)
  • Histograms communicate the relative importance of different intervals of the measured data
  • Construction:
    1. range of the data broken into convenient, non-overlapping "intervals" of equal width
    2. count how many values are in each interval -- the "frequency" of an interval
    3. On a set of axes, rectangles are drawn above the intervals to a height equal to the frequency.
  • Examples:
    • NKU student heights
    • Example from StatCrunch