1. 1Feb 13, 2006BUS304 – Review chapter 1-3 Descriptive statistics1 Review of Chapter 1-3 Descriptive Statistics  Descriptive Statistics  Ways to collect, describe, and present data  Collect data  Population vs. Sample  Statistical Sampling Technique a) Simple random b) Stratified c) Systematic d) Cluster  Data Types  Primary vs. Secondary  Qualitative vs. Quantitative  Measure levels: a) Nominal (group, compare, mode) b) Ordinal (everything you can do for level a, + sort, median) c) Interval (everything you can do for level b, + subtraction, zero ≠ nothing) d) Ratio (everything you can do for level c, + division, zero = nothing)

2. 2Feb 13, 2006BUS304 – Review chapter 1-3 Descriptive statistics2 Graphical Presentation Data Type start Bar ChartPie Chart or Frequency Relative Frequency or Qualitative Categorical (Nominal, Ordinal) Quantitative (Discrete/continuous, Interval/Ratio) Data class Bar ChartLine Chart Frequency Relative Frequency Histogram Limited Categories Continuous Range Scatter Chart Two sets of continuous variables – relationship

3. 3 Procedures to create a histogram  Create a frequency table  Identify the range of data: Range = Rounded maximum - Rounded minimum  Identify the width of each category: Width = Range / Number of bars  Write down the lower and upper bound for each bar Lower limitUpper limitFrequency Rounded min=lower limit + widthCount numbers =upper limit of above category=lower limit + widthCount numbers …… =upper limit of above category=lower limit + width = rounded maxCount numbers Remember to verify the total frequency = sample size

4. 4Feb 13, 2006BUS304 – Review chapter 1-3 Descriptive statistics4 Numerical Characterization  Measure of central tendency: Mean MedianMode  Measure of Variation RangeVariance Standard Deviation  Other Location Related Measures (find location first)  Percentiles/Quartiles (Calculate location first, then go find the value)  Interquartile range

5. 5 Probability Theory  Key concepts  Experiments and events Identify elementary events and sample space  Relationship among events: Complement Events, P(E 1 ) =1- P(E 2 ) Mutually Exclusive Events, P(E 1 and E 2 ) = 0 Conditional Probabilities, P(E 1 | E 2 ) = P(E 1 and E 2 ) / P(E 2 ) Independent Events. P(E 1 and E 2 ) = P(E 1 )*P(E 2 )  Mean (expected value) and SD of a random variable Mean – weighted average of all possible values (weights are the probs). Variance – weighted average of the squared deviation from the expected value.