STAT 22500 Lecture 1: Makeup Exam Form

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violetskunk495

5 Jul 2016

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Day and date of regularly scheduled exam: ____________________________________ Reason for missing the regularly scheduled exam: _______________________________ (please note that it is your responsibility to show documentation for this reason to your own instructor. Your exam will not be graded until you have done this. ) Please write down a list of times you are available for taking the make-up exam in the week following the regular exam. Start with the day following the regular exam. The more available times you provide, the more likely we are to be able to accommodate your schedule.

Related Questions

Researchers measured the blood pressures of 22 students in

two situations: when the students were relaxed and when the students were taking an

important examination. The file

systolic.txt

lists the systolic and diastolic pressures for

each student in each situation. Dataset is available at

systolic_url = "https://mcs.utm.utoronto.ca/~nosedal/data/systolic.txt"

Use R

to answer each of the following questions. You have to show

all your work

to get

full credit.

Answers, even if correct, with no justifications will not receive any

marks

Using R

, compute the change in systolic pressure by subtracting systolic pressure when

relaxed from systolic pressure during the exam; call this variable

Using R

, repeat part a) for diastolic pressure. Call the resulting variable

Using R

, make a scatterplot of

versus

, fit a regression line to the data and add

this line to your plot. Use: 2 c) your last name as the main title for your plot. (In my

case it would be: 2 c) Nosedal).

Important note. Use

as your response variable and label horizontal and vertical axes.

d) What is the fitted regression model? Provide slope and y-intercept

, make a residual plot from the regression in part c). Does this plot call into

question the use of a linear model? Why?

Note. Use:

2 e) your last name

as the main title for your plot. (In my case it would

be:

2 e) Nosedal

f) Note the outlier in the residual plot (and on the scatterplot from part c)).

Using

, delete the outlier from the data set. Then repeat parts c) and e). Note. Use:

2 f )

your last name

as the main title for your plots. (In my case it would be:

2 f ) Nosedal

g) What is the fitted regression model (after the outlier has been removed)? Provide slope

Happy Clown Carnival Company is scheduled to appear in a city on a particular Saturday. The profits that will be obtained depend heavily upon the weather. If the weather is rainy, the carnival loses $15,000; if it is not rainy, the carnival makes a profit of $5,000. Historically, the probability of rain on any given day is 10%.

The carnival has to set up equipment for its show, but it can cancel the show prior to setting up its equipment. Cancelling the show results in a loss of $1,000, regardless of the weather. However, for an additional $250 cost, the carnival can postpone its setup decision until the Friday before the scheduled performance. At that time, the carnival can obtain the local weather forecast for Saturday’s weather.

The Weather Bureau has compiled data on its past forecasts. When it was rainy, the Weather Bureau had predicted rain 74% of the time. When it was not rainy, the Weather Bureau had predicted no rain 86% of the time.

(a) Set up the decision tree and determine the decision (SETUP or CANCEL) that maximizes the expected profit without waiting for a weather forecast on the blank page provided. Leave enough space to add to this tree in part (d).(15 pts for correct tree, 12 pts for decision and backup calculations.)

(b) Determine the Expected Value of Perfect Information (EVPI) for the situation depicted in your decision tree from (a).(7 pts.)

(c) Append to your decision tree in (a) a decision tree diagram that includes waiting for the results of the weather forecast. Be sure to clearly label the branches and nodes. (15 pts.)

(d) Determine the two posterior probability distributions for Saturday’s actual weather given the weather forecasts on Friday and put your results in the appropriate places on your tree in (c). (Hint: Bayes. ). (15 pts.)

(e) . Calculate the Expected Values at each appropriate node for the part of the tree diagram you added in (c). (30 pts.)

(f) Based on your results in (e), what is your optimal decision strategy? (5 pts.)

(g) Calculate the Expected Value of Sample Information (EVSI) and the efficiency of sample information for this situation. Also calculate the Expected Net Gain of Sample Information. (ENGSI is the amount you expect to gain from the sample information after accounting for what it cost you to get that information.) (5 pts.) Use this page for your decision tree. Please write clearly enough so I can tell what your answers are.

silveralligator782

7. Write a class MetroLine in which you define a new type MetroLine (10 points) A MetroLine is defined to have the following private properties: • A String representing the colour of the line (e.g. blue, red, green, etc. No numbers. It's Montreal, not Manhattan!) • A collection of MetroStation This collection can be either a built in array, an ArrayList, or any other kind of collection you feel would satisfy the requirements of the class. The collection must be able to define an ordering from "beginning" to "end" of the MetroLine. It does not matter which part you consider the beginning and which part is the "end" as long as it is consistent. (We recommend using ArrayList but you are free to do otherwise if you feel it will be casier.) A MetroLine should have the following methods defined: • A constructor which takes nothing as input and performs any initialization necessary to maintain your collection of stations. • A method addstation which takes as input a MetroStation and adds it to the end of your collection. The method can assume the station is not already part of the collection and should return void. Note that the order the MetroStations are added is the same as the path the trains will travel on (or it could be the reverse path as well). • A method hasStation which takes as input a MetroStation and returns a boolean representing whether the metro line has a MetroStation with the same name or not. A method get LineColour which returns the colour of the line. • A method get First Stop which returns the MetroStation representing the first stop of the metro line. If there is no such station (ic, if the collection of MetroStation is empty), your method should return null. • A method get PriorStop which takes as input a MetroStation and returns the stop prior to the MetroStation passed as input. You may assume that the MetroStation passed as input is indeed in the collection of MetroStations If the current station is the first stop on the MetroLine then this method should return null. You may assume that there are no "loops" in the MetroLine That is, no station is present on the same line twice. A method getNext Stop which takes as input a MetroStation and returns the stop after the MetroStation passed as input. You may assume that the Metrostation passed as input is indeed in the collection of Metrostations. If the current station is the last stop on the MetroLine, then this method should return null. You may assume that there are no "loops" in the MetroLine That is, no station is present on the same line twice. For the above methods, you may assume that there is no aliasing issue. That is to say, you can use == to compare the references, or if you are using a type such as ArrayList to maintain your list of stations, you can use the indexOf or contains method defined on an ArrayList.

STAT 22500 Lecture 1: Makeup Exam Form

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