Simmons owns and operates a national chain of department stores. Simmons wants to send an expensive sales catalog with a "30% off"coupon only to those customers who have a sufficiently high probability of using the coupon. Management thinks that the decision shot1 if the customer has a Simmons credit carddepend on x1 - annual spending at Simmons ($1000) and x₂0 otherwiseAssuming y =output for the logit, InCoefficients1 if the customer uses the coupon0 otherwisePPredictorIntercepta.0.4688b.0.5436c.0.5075d.0.4476was obtained:Estimate-2.100.351.40and, p-P(y-1), the logistic regression was run in Data Mining and the followingWhat is the predicted probability of using the coupon by a customer who spends $2500 annually and has a Simmons credit card?

Answered: Image /qna-images/answer/b4fb3f2d-7987-4254-a3e8-b4a8f4e4bf38.jpg

Answered: Simmons owns and operates a national…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Determine whether the statements are true or false. A. In logistic regression, the model is fitted by using The Least Square Regression Estimation method. B. Odds ratio is defined as the ratio of two log-odds. C. In logistic regression, as Bo + Bx gets huge, p approaches 1.
The Environmental Protection Agency is concerned with the problem of setting criteria for the amounts of certain toxic chemicals to be allowed in freshwater lakes and rivers. A common measure of toxicity for any pollutant is the concentration of the pollutant that will kill half of the test species in a given amount of time (usually 96 hours for fish species). This measure is called LC50 (lethal concentration killing 50% of the test species). In many studies, the values contained in the natural logarithm of LC50 measurements are normally distributed, and, hence, the analysis is based on In(LC50) data. Suppose that n = 30 observations are to be taken on In(LC50) measurements and that o 0² = 1.7. Let S² denote the sample variance of the 30 measurements. (a) Find a number b such that P(S² ≤ b) = 0.975. (Round your answer to three decimal places.) b = (b) Find a number a such that P(a ≤ S²) = 0.975. (Round your answer to three decimal places.) a = (c) If a and b are as in parts (a) and…
Hanny
Comment on the statistical significance of the estimated logit model.
Can gender, educational level, and age predict the odds that someone votes for a particular candidate in the election? Over 1500 voters were selected, and data were col-lected on the highest year of school completed, their age, and their gender. We wish to t a logistic regression model: log(1 p p ) = 0 + 1Age + 2Education + 3Gender, where p is the binomial probability that a person voted for candidate Johnson, and gender is coded as the indicator for female. The R output is given below. parameter df estimate s.e z p-value (Intercept) 1 .1119 .3481 .321 .748 Age 1 .0020 .0032 .613 .54 Education 1 -.0100 .0184 .547 .585 Gender 1 .4282 .1040 4.117 .000 Null deviance: 255.95 on 1499 degrees of freedom Residual deviance: 220.80 on 1496 degrees of freedom Write down the tted logistic regression and give a short summary about the data analysis . Calculate the probability of voting for Johnson for a…
The Baytown Post Office has 4 stations for service. Customers line up in single file for service on an FIFO basis. The mean arrival rate is 32 per hour, Poison distributed, and the mean service time per server is 6 minutes, exponentially distributed. Compute the operating characteristics for this operation. Does the operation appear to be satisfactory in terms of: (a) Postal workers' (servers') idle time; (Round answer to 3 decimal places, e.g. 2.750.) (b) customer waiting time and the number waiting for service; (c) the percentage of the time a customer can walk in and get served without waiting at all?
The following model studies the effect that a chemical spill disaster had on nearby housing values. They used data from a sample of houses sold in 1980, before chemical spill disaster happened, and a separate sample of houses sold in 1985, after chemical spill had occurred. where the variables used in the analysis are: log(price) is natural log of selling price in $ y85 is a dummy variable equal to 1 if a house was sold in 1985, 0 otherwise far is a dummy variable equal to 1 if a house was far from the affected area, 0 otherwise If the chemical spill reduces the value of houses closer to the affected area, which of the following statement is correct? Select one: O a. a₁ is expected to be positive O b. O c. O d. log(price) = a + Boy85 + a₁ far + B₁y85 * far + u a₁ is expected to be negative B₁ is expected to be positive B₁ is expected to be negative
A golfer practices different parts of their game for hours. Specifically, the golfer practices:(1) putting, (2) their short game, and (3) their iron game. The amount of time spent on each partof their game is exponentially distributed. If the golfer is practicing their putting, they will alwaysswitch to their short game after an average of 30 minutes. When the golfer practices their short game,they do so for an average of 45 minutes, and then switches to putting with probability 0.6 or to theiriron game with probability 0.4. When they practice their iron game, they do so for an average of 60minutes. After practicing their iron game, the golfer will switch to putting or to their short game withequal probability.(a) Draw the CTMC rate diagram, clearly label your states and transition rates (qij ’s)(b) Find the transition rates out of the states (vi’s) and transition probabilities (Pij ’s).(c) Find the limiting probabilities (make sure to write out the balance equations).(d) In the long…
Would you include ros in a final model explaining CEO compensation in terms of firm performance?
Q1. 807 people were randomly selected and data was collected on whether or not they smoked cigarettes in the past 12 months (smoked = 1 if they did, smoked = 0 otherwise), their years of schooling (educ), the natural log of their annual income in dollars (In[income]), age in years (age), and race (white = 1 if white, white = 0 otherwise). The following logit models were estimated and the results are summarized in the table below. The numbers in parentheses are the standard errors. (1) logit (2) logit (3) sample average constant 1.43 0.02 (0.40) (1.06) educ -0.10 -0.11 12 (0.03) (0.03) In[income] 0.16 10.8 (0.11) age -0.02 -0.02 41 (0.0004) | (0.0004) white 0.02 0.7 (0.23) log-likelihood -525 -524 In column (2), the regression equation for smokeď* is: smoked* = x'3 + e = B1 + B2educ + B3 In[income] + B4age + B5white + e In column (3), the sample averages of the regressors are listed. For example, 12 is the sample average of educ, 10.8 is the average of In[income], etc. (a) Using the…
2. This question is about logistic regression. The outcome variable is success (1=success, 0=failure), and we have two groups of observations: group A and group B. a. Assume that on average, the odds of success is x for group A members. What is the average probability of success (p) for group A? Please write down p as a function of x. Given an x, is there a unique p? b. Assume that on average, the odds ratio for success of group A over group B is 2. The average probability of success for group A is pA and that the average probability of success for group B is pg. Is the set of Paand pg unique? c. The logistic regression of success ~ group (link=logit) returns a coefficient estimate of -1.3863 for the dummy variable group (1=group A, 0=group B). Interpret this coefficient estimate.
G FTSE 100 6. Consider the OLS estimator of a model to explain the stock prices of observations from 2012 m1 to 2021 m 12, all variables are calculated company using 120 at the end of the month t log (stock +) 0.86 + 0.86 + 0.54 log (profit 6) - 0.65 log (research t)-1.34 log (marketing 6) (6.1) (1.12) (0.24) (0.30) (0.12) 3 n = 120, R² = 0.34 SSR = 1.29 F = 3.99 : / " 116 where stuck t the › in millions of stock price in GBP (British Sterling) profit & (the profit before tax GBP), research & (expenditure on research and development), and marketing t marketing) are measured in parentheses, SSR is the Sum of Squared Residuals, and the I statistic for the significance GBP. Standard errors are reported in (expenditure on millions of of the regression is $ provided. lat What is the interpretation of the coefficient on as you would expect? Explain your answer. log (profit t) 7 Is the sign of coefficient measured in thousands of GBP? Explain your answer. Hint: Would your interpretation…

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