Year Tea (L per person) Coffee
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
Answer:
R code with output
tea=c(42.4,42.12,47.61,60.86,55.58,50.61,49.89,56.77,62.53,68.31,69.88,72.99,71.36,90.78,74.7,67.15,67.03,87.83,93.4,78.9,111.32,98.39,105.25)coffee=c(95.85,97.28,87.62,92.04,99.21,95.63,97.42,93.93,95.67,99.27,101.31,101.68,104.02,106.09,105.8,102.15,101.15,104.05,102.7,105.28,106.3,104.96,103.57)
year=c(1994:2016) mean(tea)median(tea)mfv1(tea)range(tea)mean(coffee)median(coffee)mfv1(coffee)
summary(tea)summary(coffee)IQRtea=83.36-56.18=27.18IQRcoffee=104.00-96.56=7.44sd(tea)sd(coffee)
range(coffee)hist(coffee)hist(tea)boxplot(coffee)boxplot(tea)plot(coffee,tea)
plot(year,coffee)plot(year,tea)m=lm(coffee~tea)summary(m)cor(coffee,tea)
The measure of central tendency are mean, median , mode(mfv-mostfrequent observation) etc..
Measure of spread is range
range(tea) =111.32-42.12
=69.2
range(coffee)=106.30-87.62
=18.68
Here the model interval length is 5 units.
Here the model interval length is taken as 10 units.
Box plot of coffee
From the plot it is clear that the distribution is negativelyskewed and there is no outliers in the data.
Box plot of tea
From the plot we can infer that the distribution is positivelyskewed and there is no outliers in the model.
The correlation between Coffee and tea is0.769, which implies there is positive linearrelationship exist between the variable tea and coffee.
The obtained model is:
coffee=86.3200+0.1954*tea
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