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 Weibull Poisson Power log normal BinomialChi squareLog normalNormal