1. Welcome to MM305 Unit 2 Seminar Dr. Bob Statistical Foundations for Quantitative Analysis

2. Statistical Thinking in Business Data in the business environment Common vs. special causes of variation Sources and types of data Cross-sectional vs. Longitudinal (time series) Levels of measurement Populations, Samples and Statistics Population – Parameters Sample - Statistics Using Excel effectively in this course See pages 30 - 43

3. Descriptive Statistics Graphical Frequency distributions and histograms Numerical Measures of central tendency Measures of dispersion Coefficient of variation Measures of shape Data profiles Percentiles (college admission tests) Correlation How two variables co-relate

4. Excel Insert Tab – Charts Group

5. Excel Procedures to Create Graphs Histograms -- Data Analysis Histogram Bar graphs -- Chart Wizard Column Pareto chart -- Data Analysis Histogram {Check Pareto} Circle graphs (or Pie chart) -- Chart Wizard Pie Time series graph -- Chart Wizard Line {Time on the X axis} Stem-and-leaf plot -- PHStat2 Descriptive Statistics Scatter Plot -- Chart Wizard Scatter

6. Excel Support Excel statistical functions http://office.microsoft.com/en- us/excel/HP100791861033.aspx http://office.microsoft.com/en- us/excel/HP100791861033.aspx Analysis Toolpak tools Excel Add-In PHStat tools and procedures www.drboblockwood.com

7. Excel Descriptive Statistics Tool

8. Facebook Survey Results

9. Measures of Central Tendency Mode Most frequently occurring score Median The middle score in a distribution Mean The arithmetic average:

10. Measures of Dispersion Range: difference between the maximum and minimum observation Deviation: the difference between a data value and the mean of the distribution (x – mean) Variance: in a population it is the mean squared deviation Standard Deviation: the square root of the variance, best understood with Empirical Rule (see page 95)

11. Coefficient of Variation  CV = Standard Deviation / Mean CV is dimensionless, and therefore is useful when comparing data sets that are scaled differently.

12. Correlation: the relationship between two variables, x and y. Scatter Plot or Diagram The x variable is on the horizontal axis The y variable is on the vertical axis The scatter plot is location for each x,y pair. Types of Relationships Positive: both x and y move in the same direction Negative: x and y move in opposite directions Zero: no pattern of movement in x and y

13. Scatter Plot (Diagram)

14. Correlation Coefficient