READING JOURNAL 1

Please respond to any 8 of the following 11 essays noted below and appearing as either 1) a selected reading posted to Blackboard, or 2) an anthologized essay in the texts assigned for this course. You are asked to write a minimum of 300 words per entry and share your response to the ideas presented by the author.

Course texts:
 Biguenet, John and Rainer Schulte (Eds.). The Craft of Translation. Chicago: U of Chicago Press,

1989.
 Biguenet, John and Rainer Schulte (Eds.). Theories of Translation: An Anthology of Essays from

Dryden to Derrida. Chicago: U of Chicago Press, 1992.
READINGS FOR JOURNAL 1 – Due to Blackboard Friday, February 28, by midnight

1. 1) “NoTwoSnowflakesAreAlike”(Rabassa)
2. 2) “Introduction”toTheoriesofTranslation(Biguenet&Schulte)
3. 3) “TheProcessofTranslation”(Weaver)
4. 4) “Building a Translation, The Reconstruction Business: Poem 145 of Sor Juana Ines de laCruz” (Peden)
5. 5) “QuestfortheEssenceofLanguage”(Jakobson)
6. 6) “On Linguistic Aspects of Language” (Jakobson)
7. 7) “Language” (Heidegger)
8. 8) “TheIdeaofSilence”(Agamben)
9. 9) “TheIdeaofLanguage”(Agamben)
10. 10) “The Task of the Translator” (Benjamin)
11. 11) “Ziv, that light: Translation and Tradition of Paul Celan” (Felstiner)

1. Identify all questions that you attempted in this templateQ1 Textbook Exampleshttps://github.com/JWarmenhoven/ISLR-python
   1. Chapter 5 – Resampling Methods Recreate and explain – Figure 5.2, 5.4
   2. Chapter 6 – Linear Model Selection and Regularization Redo:
   • Lab 2: Ridge Regression
   • Lab 2: The Lasso
   • Lab 3: Principal Components Regression

   Q2 Textbook Theory5.3. Review k-fold cross-validation.(a) Explain how k-fold cross-validation is implemented.(b) What are the advantages and disadvantages of k-fold cross-validation relative to:i. The validation set approach? ii. LOOCV?Q3 Textbooks Applied
   5.5. In Chapter 4, we used logistic regression to predict the probability of default using income and balance on the Default data set. Estimate the test error of this logistic regression model using the validation set approach. Do not forget to set a random seed before beginning your analysis.(a) Fit a logistic regression model that uses income and balance to predict default.(b) Using the validation set approach, estimate the test error of this model. In order to do this, you must perform the following steps:

   1. Split the sample set into a training set and a validation set
   2. Fit a multiple logistic regression model using only the training observations.
   3. Obtain a prediction of default status for each individual in the validation set by computing the posterior probability of default for that individual. Classify the individual to the default category if the posterior probability is greater than 0.5.
   4. Compute the validation set error, which is the fraction of the observations in the validation set that are misclassified.

   (c) Repeat the process in (b) three times, using three different splits of the observations into a training set and a validation set. Comment on the results obtained.(d) Now consider a logistic regression model that predicts the probability of default using income, balance, and a dummy variable for student. Estimate the test error for this model using the validation set approach. Comment on whether or not including a dummy variable for student leads to a reduction in the test error rate.5.7 (page200) Compute the LOOCV error for a simple logistic regression model on the Weekly data set. Recall that in the context of classification problems, the LOOCV error is given in (5.4).(a) Fit a logistic regression model that predicts Direction using Lag1 and Lag2.(b) Fit a logistic regression model that predicts Direction using Lag1 and Lag2 using all but the first observation.(c) Use the model from (b) to predict the direction of the first observation. You can do this by predicting that the first observation will go up if P(Direction=”Up”|Lag1, Lag2) > 0.5. Was this observation correctly classified?(d) Write a for loop from i = 1 to i = n, where n is the number of observations in the data set, that performs each of the following steps:

   1. Fit a logistic regression model using all but the ith observation to predict Direction using Lag1 and Lag2.
   2. Compute the posterior probability of the market moving up for the ith observation.
   3. Use the posterior probability for the ith observation in order to predict whether or not the market moves up.
   4. Determine whether or not an error was made in predicting the direction for the ith observation. If an error was made, then indicate this as a 1, and otherwise indicate it as a 0.

   (e) Take the average of the n numbers obtained in (d)iv in order to obtain the LOOCV estimate for the test error. Comment on the results.6.8 (page 262) generate simulated data and use this data to perform best subset selection.(a) generate a predictor X of length n = 100, as well as a noise vector of length n = 100.(b) Generate a response vector Y of length n = 100 according to the model Y = β0 + β1X + β2X2 + β3X3 + , where β0, β1, β2, and β3 are constants of your choice.(c) perform best subset selection in order to choose the best model containing the predictors X, X2,…,X10. What is the best model obtained according to Cp, BIC, and adjusted R2? Show some plots to provide evidence for your answer and report the coefficients of the best model obtained.(d) Repeat (c), using forward stepwise selection and also using backwards stepwise selection. How does your answer compare to the results in (c)?(e) Now fit a lasso model to the simulated data, again using X, X2, …, X10 as predictors. Use cross-validation to select the optimal value of λ. Create plots of the cross-validation error as a functionof λ. Report the resulting coefficient estimates, and discuss the results obtained.(f) Now generate a response vector Y according to the model Y = β0 + β7*X⁷ + ε, and perform best subset selection and the lasso. Discuss the results obtained.6.9 (page 263) predict the number of applications received using the other variables in the College data set.(a) Split the data set into a training set and a test set.(b) Fit a linear model using least squares on the training set and report the test error obtained.(c) Fit a ridge regression model on the training set, with λ chosen by cross-validation. Report the test error obtained.(d) Fit a lasso model on the training set, with λ chosen by cross validation. Report the test error obtained, along with the number of non-zero coefficient estimates.(e) Fit a PCR model on the training set, with M chosen by cross validation. Report the test error obtained, along with the value of M selected by cross-validation.Hint use: https://botlnec.github.io/islp/https://github.com/a-martyn/ISL-pythonhttps://github.com/a-martyn/ISL-python/blob/master/Notebooks/ch6_linear_model_selection_and_regularisation_applied.ipynb
   Q5 Dimensionality Reduction – on Wine data.zip
   Hitters.zip
   Chap5Review.py
   Default.xlsx
   Weekly.csv
   College.csv
   Auto.csv
   HW Dimensionaliy Reduction.docx

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Zero days vulnerabilities in Digital Forensics… Please, discuss your views and ideas on how can we be prepared for zero day vulnerabilities and attacks. Share your views with your classmates and comment on at least two of your classmates’ posts.

FASB Code Questions (5 pts.):

Pleasant Co. manufactures specialty bike accessories. The company is known for product quality, and it has offered one of the best warranties in the industry on its higher-priced products—a lifetime guarantee, performing all the warranty work in its own shops. The warranty on these products is included in the sales price.

Due to the recent introduction and growth in sales of some products targeted to the low-price market, Pleasant is considering partnering with another company to do the warranty work on this line of products, if customers purchase a service contract at the time of original product purchase. Pleasant has called you to advise the company on the accounting for this new warranty arrangement.

Instructions

Go to http://aaahq.org/asclogin.cfm to log in and prepare responses to the following. Provide Codification references for your responses.

• Identify the accounting literature that addresses the accounting for the type of separately priced warranty that Pleasant is considering.
• When are warranty contracts considered separately priced?
• What are incremental direct acquisition costs and how should they be treated?

The accounting literature that addresses the accounting for the type of separately priced warranty that Pleasant is considering is addressed by FASB ASC 605-20-25, and it explained how the revenue and costs from a separately priced extended warranty should be recognized.

Some products include warranty obligations that are incurred in connection with the sale of the product, that is, obligations that are not separately priced or sold but are included in the sale of the product. The accounting for these is described in Topic 450. Separately priced contracts for extended warranty and product maintenance contracts provide warranty protection or product services and the contract price of these contracts is not included in the original price of the product covered by the contracts.

Costs that are directly related to the acquisition of a contract and that would have not been incurred but for the acquisition of that contract (incremental direct acquisition costs) shall be deferred and charged to expense in proportion to the revenue recognized.

Student Login

Username – AAA51242

Password – 35xjAEV

Written Questions (10 pts):

Answer the following questions in 1 page or less for each question.

Question 1:

Pleasant Co. is considering issuing bonds for the expansion of its business overseas.Is it more advantageous for Pleasant Co. to offer customers the option to purchase additional service contracts or to provide warranties on all products sold considering its upcoming bond issuance?

Suggested approach to answer this question:

• Write out the journal entries for Assurance-typed warranties and Service-typed warranties and think of the balance sheet impact of each.
• Think about how the balance sheet impact would impact the selling price of bonds.Remember that investors look at liquidity ratios when determining the risk of a bond issuance

Question 2:

Pleasant Co. currently relies upon third-party service providers to repair products under assurance-typed warranties and is considering opening service locations.

Opening service locations would require significant fixed asset investment but would be less expensive per repair.

Discuss the impact on the balance sheet and impact on any two liquidity ratios of moving from a per unit more expensive third-party service provider to a less expensive in-house warranty servicing in an e-mail format to your hypothetical manager.

Suggested approach to answer this question:

• Consider where Pleasant Co. would gather funds for the investment in fixed assets to open service locations and its effects on the balance sheet.
• Write out the journal entries for assurance-typed warranties and think of how the estimates in the journal entries are affected by this proposed change.

3 page paper.

Chicago-style paper format.

The books I am using are:

Richard Reid, A History of Modern Africa.

Collins and Burns, History of Sub-Saharan Africa.

John iliffe, African: History in World History.

Reynolds and Gilbert, Africa in World History.