MSQM Statistical Modeling Course Outline

About supervised machine learning, in the context of Linear Regression; Decision tree; Logistics Regresion; Randon forest and neural network, which metrics should be used to know if a classification model is good and why use them? What about regression, what metrics are used to say how good the model is? What is the best for each case?

An electrical contractor’s records during the last five weeks indicate the number of job requests: Week 1 2 3 4 5 Jobs 20 22 18 21 22 Predict the number of requests for week 6 using each of this method:a. Naive

Multiple choice questions. Choose correct answer 1. Sampling is used because A) it increases the data quality B) the processing of entire data can be time-consuming C) it reduces dimensionality D) it helps find missing data Answer: 2) Correlation coefficient is always in the range A) 0 to 1 B) -1 to 1    C) 0 to 100    D) 1 to 2   Answer: True or False. Choose correct answer 3. Regression analysis is used to predict a value of a continuous valued variable. Answer:

Q=What is the importance of regression analysis in transportation engineering? ANSWER in word fomat

An electrical contractor’s records during the last five weeks indicate the number of job requests: Week 1 2 3 4 5 Jobs 20 22 18 21 22 Predict the number of requests for week 6 using each of this method:c. Exponential smoothing with α = .30; use 20 for week 2 forecast

The following data provide the time in months from hire to promotion to manager for a random sample of 25 software engineers from all software engineers employed by a large telecommunications firm. 5 7 229 453 12 14 18 14 14 483 22 21 25 23 24 34 37 34 49 64 47 67 69 192 125 Calculate the mean, variance, and standard deviation for this sample.

Materials of Interest: CuFeS, in a silica matrix, 1.5% Cu (4.3318% CuFeS,); Top Size = 1.5 cm; CuFeS, grain size = 0.01 cm Desired sampling accuracy: +0.02% Cu, certainty of 0.99 (2.576 standard deviations) CuFeS, specific gravity=4.2: Overall specific gravity 2.8 Broad size distribution. Determine the minimum sample weight (in grams) needed for testing.

An electrical contractor’s records during the last five weeks indicate the number of job requests: Week 1 2 3 4 5 Jobs 20 22 18 21 22 Predict the number of requests for week 6 using each of this method:A) A four-period moving average

Flow Characteristics (Entrance flow) Why was not the linear regression applied to all of the data?(it shouldnot have needed to be applied to all data?

Determine if the data has a positive or a negative relationship with each other. Showcase the regression line, and determine if the data provided fits the approximate curve.

Hello Sir.Good night.Permission, i have a question in my homework related numerical methods lesson. The following bellow is question. Please advice. Thank you so much Regards,Irfan Mention the types of problems that exist in the field of engineering, especially mechanical engineering that can be solved by the linear regression method

Please Identify the correct answer along with concise reasoning( Step-by-step is preferred) on why the selected option is the right answer.   Please also explain concisely why the remaining options are incorrect.    I'll rate for the response positively if the answer is correct. Thx!

Needs Complete typed solution with complete explanation and 100 % accuracy.      Don't use chat gpt or any ai

Diffrentate between classification vand regression ? Give any 3 points

As an industrial engineer, you intend to use linear trend (or linear regression) method to solve a forecasting problem. You have decided to use the equation of y = m(x) + c to establish the relationship between the sales (y) and the related month (x). It is known that 8 consecutive months data (Jan to Aug) were used and they resulted to the following parameter values of m = 320 and c = 1017. Using the regression technique, estimate the percentage of sales improvement from December this year to June next year.

The following table presents the highway gasoline mileage performance and engine displacement for Audi vehicles for model year 2005. a) (5 Pts.) Fit simple linear model. Test for significance of the regression using alpha=0.05. Find the p-value for this test. What conclusions you can reach? b) (5 Pts.) Test Ho: P₁= -0.05 versus H₁: ₁

Given: N=3,000, n1=200, c1=10, r1=14, n2=300, c2=20, r2=21. Write the formula of the probability of acceptance. If a certain lot with 2.0 % non-conforming, what is the probability of rejecting the lot during the second sampling?

What can surrogate models enable? Check all that apply. They can help linearize strongly nonlinear forward models. They can help accelerate evaluation of the forward model or likelihood in Bayesian inference. They can make it easier to exploit parallel computing resources. They can reduce the dimensionality of the data. They can help push more computation to an "offline" phase of the analysis.