Construction Engineering 221

1
Construction Engineering 221

• Probability and statistics

2
Data description

• Random sample- every member of the population has
  an equal chance of being selected into the
  sample. Hard to do (unlisted phone s, no
  permanent address)
• Can use random number generator
• Non-random is OK if biases are known and reported

3
Data description

• Data from the sample represent an array (rows and
  columns) in raw form- how it might look on an
  Excel spreadsheet
• Can organize the data in various ways to simple
  the array and make it more readable
• Classification- like letter grades, use class
  intervals to combine similar scores

4
Data description

• Class boundaries separate one class from another
• Edges of boundaries are class limits, and
  represent the data where most information is
  lost
• Class size, interval, and boundary are arbitrary
• Class mark is the midpoint of the class limits

5
Data description

• Class frequencies are the number of scores within
  each class
• The list of frequencies forms a distribution that
  typically assumes one of several standard forms
  (Normal, Chi Square, Poisson, Binomial)
• Cumulative distribution is a representation of
  number of scores below. When divided by total,
  the number represents a percentile rank

6
Data description

• Histogram is a common graphical representation of
  a frequency distribution
• Frequency polygon connects the midpoints of the
  histogram class limits and represents data
  distribution as a line
• Ogive- cumulative distributions- normal
  distribution will have an S-shaped ogive

7
Data description

• Common engineering distributions

Binomial
Chi square
Log normal
Normal
Weibull
Power log normal
Poisson