In this exercise you will learn to plot data using the ggplot2 package. To answer the questions below, use 4.1 Categorical vs. Categorical from Data Visualization with R.
## # A tibble: 22,230 x 8
## # Groups: symbol [3]
## symbol date open high low close volume adjusted
## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AAPL 1990-01-02 1.26 1.34 1.25 1.33 45799600 1.08
## 2 AAPL 1990-01-03 1.36 1.36 1.34 1.34 51998800 1.09
## 3 AAPL 1990-01-04 1.37 1.38 1.33 1.34 55378400 1.10
## 4 AAPL 1990-01-05 1.35 1.37 1.32 1.35 30828000 1.10
## 5 AAPL 1990-01-08 1.34 1.36 1.32 1.36 25393200 1.11
## 6 AAPL 1990-01-09 1.36 1.36 1.32 1.34 21534800 1.10
## 7 AAPL 1990-01-10 1.34 1.34 1.28 1.29 49929600 1.05
## 8 AAPL 1990-01-11 1.29 1.29 1.23 1.23 52763200 1.00
## 9 AAPL 1990-01-12 1.22 1.24 1.21 1.23 42974400 1.00
## 10 AAPL 1990-01-15 1.23 1.28 1.22 1.22 40434800 0.997
## # … with 22,220 more rows
## # A tibble: 90 x 3
## # Groups: symbol [3]
## symbol yearly.returns year
## <chr> <dbl> <dbl>
## 1 AAPL 0.169 1990
## 2 AAPL 0.323 1991
## 3 AAPL 0.0691 1992
## 4 AAPL -0.504 1993
## 5 AAPL 0.352 1994
## 6 AAPL -0.173 1995
## 7 AAPL -0.345 1996
## 8 AAPL -0.371 1997
## 9 AAPL 2.12 1998
## 10 AAPL 1.51 1999
## # … with 80 more rows
Hint: See the code in 4.3.1 Bar chart (on summary statistics).
Hint: See the code in 4.3.1 Bar chart (on summary statistics).
Hint: See the code in 4.3.1 Bar chart (on summary statistics).
Hint: See the code in 4.3.2 Grouped kernel density plots.
Hint: Google how to interpret density plots.
IBM has the highest chance of loosing big when things go wrong. Because it has the highest return it means it will have the highest loss.
Hint: See the code in 4.3.3 Box plots.
I would choose to use IBM for many reasons. One, IBM is the highest of returns.Seeing that the return is the highest but not by much, there would not be a crazy difference if I went with another stock. Compared to Apple of Microsoft there is not much risk taken. Overall, I would be taking the the highest risk and highest return.
Hint: Use message, echo and results in the global chunk options. Refer to the RMarkdown Reference Guide.