辅导BIST 515、csv数据讲解、辅导C/C++编程、讲解C/C++程序语言留学生

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BIST 515: Introduction to Statistical Software Homework 3

Due date: Wednesday, October 3

1. (27 total points) The National Football League (NFL) players go through a number of evaluations

during the combine so that NFL teams can assess their ability.

The nfl.csv data file is available on the canvas, and it contains information on some of the players who

participated in 2014. The columns in the data file represent the following information:

Player: Name of player being evaluated

College: College that the player attended

Position: The position of the player where DB = defensive back, LB = linebacker, OL = offensive

linemen, RB = running back, S = safety, TE = tight end, WO = wide receiver; players who

played other positions were excluded from the data file

OverallGrade: The overall grade of the player based on the evaluations

Height: Height in inches

ArmLength: Arm length in inches

Weight: Weight in pounds

Dash40: 40-yard dash time in seconds

BenchPress: Number of bench press repetitions of 225 pounds

VerticalJump: Vertical jump in inches

BroadJump: Broad jump in inches

Cone3Drill: 3-cone drill time in seconds

Shuttle20: 20-yard shuttle run in seconds

(a) (3 points) Construct side-by-side box plots of the 40-yard dash times for each position (y-axis is

40-yard dash). Use a yellow fill color for the boxes and appropriate labels (different from the default)

for axes. Note that a formula argument will be needed (rather than x) to construct the plot with the

current form of the data frame.

(b) (3 points) Construct side-by-side dot plots of the 40-yard dash times for each position (y-axis is

40-yard dash). Use red open circles for the plotting symbols and appropriate labels (different from the

default) for axes.

(c) (3 points) Combine the plots in 1(a) and 1(b) into one 1×2 grid. Make sure the y-axes on the two

plots are aligned, all x-axis labels appear, and y-axis labels are appropriately positioned. Include one

overall plot title that is appropriately positioned.

(d) (3 points) Overlay the plots in 1(a) and 1(b) onto one plot.

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(e) (3 points) Why is the default ordering for the positions given as “DB”, “LB”, . . . ,“WO”in the plots?

How could this ordering be changed and still use the same position labels?

(f) (6 points) Construct a scatter plot of the 40-yard dash times vs. the bench press weight. In your

plot, include the following:

i. Vary the the plotting symbols and their color by the position with the following assignments:

The specific color names are DB = black, LB = red, OL = blue, RB = darkgreen, S = purple, TE =

orange, and WO = gray.

ii. Gridlines

iii. Y and X-axis labels of “40-yard dash (seconds)” and “Bench press repetitions”, respectively.

iv. The name of the player with the largest bench press value next to its corresponding plotting point.

(g) (6 points) Construct a function that produces a scatter plot like in part 1(f) again, but now for

any two numerical variables in the data set. The function should not need any changes to its code for

any plot. Below are further details regarding this function and its produced plot:

i. A call to the function should be of this form:

myplot(xvar, yvar, xlab, ylab)

where myplot is the name of the function, xvar is the variable for the x-axis, yvar is the variable for

the y-axis, xlab is the x-axis label, and ylab is the y-axis label.

ii. Make sure that appropriate title and axis labels are included on the plot (I used the paste() function

to merge the axis labels into a title).

iii. Remove any labeling of points by a corresponding player name.

iv. Run the function for Dash40 vs. BenchPress and Height vs. Weight.

2. (13 total points) Suppose Z ~ N(0, 1). Complete the following using R.

(a) (3 points) Find P(0 < Z < 1.96).

(b) (3 points) Plot the probability density function.

(c) (4 points) Shade in P(0 < Z < 1.96) on the plot from part 2(b). I recommend completing a web

search for the polygon() function to determine how to complete this problem.

(d) (3 points) Plot the cumulative density function.


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