Year | Tea
(L per person) | Coffee
(L per person) |
|---|
1994 | 42.4 | 95.85 |
1995 | 42.12 | 97.28 |
1996 | 47.61 | 87.62 |
1997 | 60.86 | 92.04 |
1998 | 55.58 | 99.21 |
1999 | 50.61 | 95.63 |
2000 | 49.89 | 97.42 |
2001 | 56.77 | 93.93 |
2002 | 62.53 | 95.67 |
2003 | 68.31 | 99.25 |
2004 | 69.88 | 101.31 |
2005 | 72.99 | 101.68 |
2006 | 71.36 | 104.02 |
2007 | 90.78 | 106.09 |
2008 | 74.7 | 105.8 |
2009 | 67.15 | 102.15 |
2010 | 67.03 | 101.15 |
2011 | 87.83 | 104.05 |
2012 | 93.4 | 102.7 |
2013 | 78.9 | 105.28 |
2014 | 111.32 | 106.3 |
2015 | 98.39 | 104.96 |
2016 | 105.25 | 103.57 |
By using the definition and discussing what is relevant to thesituation, interpret each of the following for both the coffee andtea data. Also, compare each for coffee and tea. Be sure to includethe relevant information (state the value of or, in the case of thedistribution, include the graphs) with each component.
- Mean
- Median
- Modal Interval
- Range
- IQR
- Standard Deviation
- Distribution of histogram and box plot
- Slope of each linear model
- Y-intercept of Coffee vs. Tea
- Correlation coefficient for each linear model
- Relevant interpolations or extrapolations
- Correlation type (from Activity 5) for coffee and tea
