Statistical models or methods

-linear regression model

-logistic regression model

-CART or Random Forest model

-the "bag of words" approach (text analytics method)

-Hierarchical Clustering or K-Means Clustering

-data visualization method

-linear optimization model

-integer optimization model

Question:Which of the statistical model above can be used to handle situations below? Each statistical model (or method) may be applicable for "only one" or "more than one" situation?

A. Situation 1:A manufacturer needs to decide how many machines of various types to buy so that they can increase their production next month. They want to maximize total revenue, while not spending more than $50,000 on new machines.

B. Situation 2:A clothing store needs to predict their total revenue next month using the total sales this month, the types of styles that will be released next month, and seasonality.

C. Situation 3:A medical researcher wants to predict whether or not a patient will be re-admitted to the hospital, using information from the patient's medical record (e.g. demographic information, medical history, doctor's free-text notes).

D. Situation 4:An airline wants to use historical data to segment their customers into different categories to better understand the different types of customers they have and to target them with advertisements.

E. Situation 5:A chicken feed company wants to decide what percentage of four different grains to use to develop a new product. They want to minimize the total cost of the product, while making sure that it meet all of the nutritional requirements for chicken feed.

F. Situations 2and3

G. Situations 1and5.

H. Situations 1,2,3,4, and5

I.None of the above situations.