http://www.youtube.com/watch?v=tdKiP41L0Ec http://www.youtube.com/watch?v=Em8ztYfQ32s Appeal to fear: https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/32/Appeal-to-Fear Appeal to emotion: https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/29/Appeal-to-Emotion Appeal to anger: https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/20/Appeal-to-Anger Appeal to pity: https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/39/Appeal-to-Pity Appeal to spite: https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/211/Appeal-to-Spite Straw Man: https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/169/Strawman-Fallacy Red Herring: https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/150/Red-Herring Ad Hominem (abusive): https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/1/Ad-Hominem-Abusive Ad Hominem (guilt by association): https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacies/10/Ad-Hominem-Guilt-byAssociation Name ID Homework Guidelines · Share screen shot on your response · Share the code and the plots · Put your name and id number · Clear mark question number · Upload Word document · Insert Cover page Questions Attempted HW02 Cover Sheet Identify all questions that you attempted in this template Q1 Textbook Theory Questions 1. For each of parts (a) through (d), indicate whether we would generally expect the performance of a flexible statistical learning method to be better or worse than an inflexible method. Justify your answer. (a) The sample size n is extremely large, and the number of predictors p is small. (b) The number of predictors p is extremely large, and the number of observations n is small. (c) The relationship between the predictors and response is highly non-linear. (d) The variance of the error terms, i.e. σ2 = Var(), is extremely high 5. What are the advantages and disadvantages of a very flexible (versus a less flexible) approach for regression or classification? Under what circumstances might a more flexible approach be preferred to a less flexible approach? When might a less flexible approach be preferred? 6. Describe the differences between a parametric and a non-parametric statistical learning approach. What are the advantages of a parametric approach to regression or classification (as opposed to a nonparametric approach)? What are its disadvantages? Q2 Textbook Applied Questions – Attempt with Python 8. Exploratory Data Analysis: College data set: College.csv. It contains a number of variables for 777 different universities and colleges in the US. Do all the exercises in Python: 8a. Read the csv file with pandas 8b.Fix the first row as row headers 8c. i. produce a numerical summary of the variables in the data set. ii. produce a scatterplot matrix of the first ten columns or variables of the data. iii. produce side-by-side boxplots of Outstate versus Private iv. Create a new qualitative var ...

1. http://www.youtube.com/watch?v=tdKiP41L0Ec
http://www.youtube.com/watch?v=Em8ztYfQ32s
Appeal to fear:
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/32/Appeal-to-Fear Appeal to emotion:
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/29/Appeal-to-Emotion Appeal to anger:
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/20/Appeal-to-Anger Appeal to pity:
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/39/Appeal-to-Pity Appeal to spite:
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/211/Appeal-to-Spite Straw Man:
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/169/Strawman-Fallacy Red Herring:
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/150/Red-Herring Ad Hominem (abusive):
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/1/Ad-Hominem-Abusive Ad Hominem (guilt by association):
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/10/Ad-Hominem-Guilt-byAssociation
Name ID
Homework
Guidelines
· Share screen shot on your response
· Share the code and the plots
· Put your name and id number
· Clear mark question number
· Upload Word document
· Insert Cover page Questions Attempted

2. HW02 Cover Sheet
Identify all questions that you attempted in this template
Q1 Textbook Theory Questions
1. For each of parts (a) through (d), indicate whether we would
generally expect the performance of a flexible statistical
learning method to be better or worse than an inflexible method.
Justify your answer.
(a) The sample size n is extremely large, and the number of
predictors p is small.
(b) The number of predictors p is extremely large, and the
number of observations n is small.
(c) The relationship between the predictors and response is
highly non-linear.
(d) The variance of the error terms, i.e. σ2 = Var(), is extremely
high
5. What are the advantages and disadvantages of a very flexible
(versus a less flexible) approach for regression or
classification? Under what circumstances might a more flexible
approach be preferred to a less flexible approach? When might a
less flexible approach be preferred?
6. Describe the differences between a parametric and a non-
parametric statistical learning approach. What are the
advantages of a parametric approach to regression or
classification (as opposed to a nonparametric approach)? What
are its disadvantages?
Q2 Textbook Applied Questions – Attempt with Python
8. Exploratory Data Analysis: College data set: College.csv. It
contains a number of variables for 777 different universities and
colleges in the US. Do all the exercises in Python:
8a. Read the csv file with pandas
8b.Fix the first row as row headers
8c.
i. produce a numerical summary of the variables in the data set.

3. ii. produce a scatterplot matrix of the first ten columns or
variables of the data.
iii. produce side-by-side boxplots of Outstate versus Private
iv. Create a new qualitative variable, called Elite, by binning
the Top10perc variable and divide universities into two groups
based on whether or not the proportion of students coming from
the top 10 % of their high school classes exceeds 50 %
v. Produce some histograms with differing numbers of bins for a
few of the quantitative variables: Room.Board','Books',
'Personal', 'Expend'
vi. Examine the elite schools more closely.
Q3 Textbook Applied Questions – Attempt with Python
9. Exploration with Auto.csv data.
Make sure that the missing values have been removed from the
data.
(a) Which of the predictors are quantitative, and which are
qualitative?
(b) What is the range of each quantitative predictor?
(c) What is the mean and standard deviation of each quantitative
predictor?
(d) Now remove the 10th through 85th observations. What is the
range, mean, and standard deviation of each predictor in the
subset of the data that remains?
(e) Using the full data set, investigate the predictors
graphically, using scatterplots or other tools of your choice.
Create some plots highlighting the relationships among the
predictors. Comment on your findings.
(f) Suppose that we wish to predict gas mileage (mpg) on the
basis of the other variables. Do your plots suggest that any of
the other variables might be useful in predicting mpg? Justify
your answer.
Q4 Textbook Applied Questions – Attempt with Python

4. 10. Exploration with Boston.csv data
a) How many rows and columns in the data set? What do the
rows and columns represent?
(b) Make pairwise scatterplots of the predictors (columns) in
this data set. Describe findings.
(c) Are any of the predictors associated with per capita crime
rate? If so, explain relationship. (d) Do any of the suburbs of
Boston appear to have particularly high crime rates? Tax rates?
Pupil-teacher ratios? Comment on the range of each predictor.
(e) How many of the suburbs in this data set bound the Charles
river?
(f) What is the median pupil-teacher ratio among the towns in
this data set?
(g) Which suburb of Boston has lowest median value of owner
occupied homes?
What are the values of the other predictors for that suburb, and
how do those values compare to the overall ranges for those
predictors? Comment on your findings.
(h) In this data set, how many of the suburbs average more than
seven rooms per dwelling? More than eight rooms per dwelling?
Comment on the suburbs that average more than eight rooms per
dwelling.
Hint – several github sites have the complete solution in python
e.g.
https://github.com/mscaudill/IntroStatLearn
https://botlnec.github.io/islp/
1
4/30/19
PHIL110 Critical Thinking – SPS CUNY

5. Unit 8 Discussion Assignment
Multimedia Fallacies
Step 1.
There are many websites that provide information on both
formal and informal fallacies. For
example: the Internet Encyclopedia of Philosophy (entry on
"Fallacies"), the Nizkor Project, and
the Fallacy Files. Your discussion assignment is to first visit
each of these sites and find the
fallacies that correspond to those in Unit 9 and 10 (what we’ve
studied so far).
Step 2.
After you feel comfortable recognizing fallacies of failed or
flawed induction, conduct a search
online and find one video or cartoon example for one of these
fallacies. Your multi-media
example must take the form of a video/image/cartoon (check out
YouTube, for instance, or
search for the fallacies in cartoon banks). The Cartoon Network,
Family Guy, Stephen

6. Colbert/Jon Stewart, or even just plain old cartoon websites are
good places to look.
Step 3.
Once you've located the example, re-construct the fallacy from
the video or cartoon. You can
refer back to the Logically Fallacious site, which we used in
Unit 7 discussion to find additional
examples and logical form for your fallacy. Embed the multi-
media example on the Discussion
Forum (or you can paste in the link), and include your
reconstruction and analysis. Be sure to
address the following:
• Clearly state what fallacy your example represents.
• Share your reconstructed fallacy and make sure to present the
full argument (that the
video, image or cartoon presents) by identifying its implicit
premise(s) and conclusion.
• Explain why you think this is a good example of the fallacy.
Step 4.
Read and respond to other students’ posts with substantial
comments that follow these

7. commenting points:
• Do you think their reconstruction of the fallacy is well done?
If not, how would you
reconstruct it?
• Do you think their multi-media represents the fallacy they
claimed? If not, what fallacy
do you think it represents?
• What variations on their fallacy have you encountered, if any?
Or have you seen their
multi-media somewhere before and were you aware that it
represented a fallacy?
http://www.iep.utm.edu/fallacy/
http://www.nizkor.org/features/fallacies/
http://www.fallacyfiles.org/index.html
https://www.logicallyfallacious.com/tools/lp/Bo/LogicalFallacie
s/3/Book-Contents
PHIL110 Critical Thinking – SPS CUNY
• Do you have any questions for them regarding the content of
their multi-media or about
the process of identifying the fallacy?

8. Recommendations for Success and Grading Criteria:
• Respond to the assignment with clear and detailed answers,
organized thoughts.
• Follow all assignment prompts and answers all prompt
questions.
• Incorporate relevant examples and evidence to support claims.
• Write clearly and without errors a well-composed answer and
post it on time.
• Respond to other students with interesting comments and
follow-up
questions. Acknowledge all students who commented on your
post.