10.17: Chapter Exercises
- Page ID
- 136726
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)Exercise 1: Plotting Temperatures
Create a data file named tempF.dat that stores the following data. The first column is time of day and the second column is temperature in degrees Fahrenheit.
8 55 10 70 12 78 14 76 16 70 18 63 20 55
Write a script named plotRoomTemp.m that reads the data from the file, converts the temperatures to degrees Celsius, and plots both Fahrenheit and Celsius temperatures versus time. Add a legend, x-axis label, y-axis label, and title.
Exercise 2: Average High Temperatures with Subplots
A file named avghighs.dat stores average high temperatures for three locations. Each row begins with a location number followed by the 12 monthly temperatures.
432 33 37 42 45 53 72 82 79 66 55 46 41 777 29 33 41 46 52 66 77 88 68 55 48 39 567 55 62 68 72 75 79 83 89 85 80 77 65
Write a script named plotAvgHighs.m that reads the file and plots the temperatures for the three locations separately in one figure window using subplot. Use a for loop. Label the axes and add a title to each subplot using the location number.
Exercise 3: Random Line Thickness
Write a script named plotXYLine.m that draws the line y = x between x = 2 and x = 5. The line thickness should be a random integer between 1 and 10.
Exercise 4: Pizza Lovers
Survey a few friends and ask whether they prefer cheese, pepperoni, or mushroom pizza. Write a script named pizzaLovers.m that creates two plots side by side using subplot:
1. A pie chart showing the percentage of people who prefer each type. Label the slices.
2. A histogram or bar chart showing the number of people who prefer each type.
Exercise 5: Draw a Circle Function
For a circle of radius R centered at the origin, the following equations describe the x and y coordinates:
x = R cos(theta), y = R sin(theta), 0 <= theta <= 2*pi
Write a function named drawCircle.m that takes five inputs: radius R, color, line thickness, x-coordinate of the center, and y-coordinate of the center. The function should plot the circle and should not return any output. For example, drawCircle(1, 'k', 5, 0, 0)
Exercise 6: Olympic Rings
Write a script named Olympic.m that calls your drawCircle function five times to create a simplified Olympic rings logo. Use different colors and center locations for the five circles.
Exercise 7: Monthly Temperature Bar Plot
The following data represents average temperatures from January to December of 1999 in three countries:
USA = [-6.3, -4.3, 0.1, 5.9, 12.1, 17.1, 19.9, 18.9, 14.4, 7.7, 0.4, -4.8]; CAN = [-24.6, -23.3, -18.7, -9.8, -0.3, 7.2, 11.1, 9.5, 3.5, -4.4, -14.5, -21.5]; GBR = [3.0, 3.0, 4.7, 6.7, 9.8, 12.8, 14.4, 14.3, 12.2, 9.5, 5.5, 3.9];
Use a bar plot to display the data. Add a title, legend, x-axis label, and y-axis label. Use month numbers or month names for the x-axis.
Mini Project: Visualizing Experimental Data
For this mini project, collect or create a small data set from an engineering or science context. Examples include temperature over time, distance traveled over time, light intensity versus distance, or survey results. Create at least three different visualizations of the data. At least one plot should include proper labels, a title, and a legend. At least one plot should use either subplot, errorbar, histogram, or a 3D plotting function.
In a short paragraph, explain which plot is the most useful and why. Remember: the best plot is the one that helps the audience understand the data most clearly.