1. Descriptive Statistics  Individuals – are the objects described by a set of data. Individuals may be people, but they may also be animals or things.  Variable – a characteristic of an individual. A variable can take different values for different individuals.  Categorical (Qualitative) variable – places an individual into one of several groups or categories. {Gender, Blood Type}  Quantitative variable – takes numerical values for which arithmetic operations such as adding and averaging make sense. {Height, Income, Time, etc.}  Consider: #1.18 (p. 19), #1.21 (p.20)  Consider: #1.18 (p. 19), #1.21 (p.20)

2. Quantitative Variables  Discrete Variables – There is a gap between possible values.  Counts (no. of days, no. of people, etc.)  Age in years  Continuous Variables – Variables that can take on values in an interval.  Survival time, amount of rain in a month, distance, etc.

3. Graphical Procedures  Categorical (Qualitative) Data  Bar Chart  Pie Chart  Quantitative Data  Histogram  Stem-and-leaf plot (Stemplot)  Dotplot  These plots describe the distribution of a variable.

4. Length of Stay 51159 37212 418913 282413 1610 569

5. Fifth-grade IQ Scores 145101123106117102 1391429412490108 126134100115103110 122124136133114128 125112109116139114 130109131102101112 96134117127122114 110113110117105102 118811271099782 11811312413789101

6. Distribution The distribution of a variable tells us what values it takes and how often it takes these values The distribution of a variable tells us what values it takes and how often it takes these values  Categorical Data  Table or Bar Chart  Quantitative Data  Frequency Table  Histogram  Stem-and-leaf plot

7. Describing a distribution  Skewness  Symmetric  Skewed to the right (positively skewed)  Skewed to the left (negatively skewed)  Center/Spread  No of peaks (modes)  Unimodal, Bimodal, Multimodal.  Outliers  Extreme values.

8. Homework Chapter 1 : (pp. 19-23) # 1, 2, 5, 7, 10, 11, 12, 13, 16, 23, 28. Chapter 2 : (pp. 33-37) # 5, 6, 15. (pp. 44-49) # 27, 31, 40.