4.2 – University Rankings: The dataset on American college and university rankings contains information on 1302 American colleges and universities offering an undergraduate program. For each university, there are 17 measurements that include continuous measurements (such as tuition and graduation rate) and categorical measurements (such as location by state and whether it is a private or a public school). a. Remove all categorical variables. Then remove all records with missing numerical measurements from the dataset.

4.2 – University Rankings: The dataset on American college and university rankings contains information on 1302 American colleges and universities offering an undergraduate program. For each university, there are 17 measurements that include continuous measurements (such as tuition and graduation rate) and categorical measurements (such as location by state and whether it is a private or a public school). a. Remove all categorical variables. Then remove all records with missing numerical measurements from the dataset.

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Description: #4.2 – University Rankings: The dataset on American college and university rankings contains information on 1302 American colleges and universities offering an undergraduate program. For each university, there are 17 measurements that include continu

C++ Programming: From Problem Analysis to Program Design

8th Edition

ISBN:9781337102087

Author:D. S. Malik

Publisher:D. S. Malik

Chapter12: Points, Classes, Virtual Functions And Abstract Classes

Section: Chapter Questions

Problem 27SA

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Suppose a group of 9 sales price records has been stored as follows: 9, 25, 28, 30, 48, 72, 78, 195, 213 Partition them into three bins then smoothing them by the following methods: Partition into equal-width then smoothing by bin means. Partition into equal-depth then smoothing by bin boundaries.
The file UniversalBank.csv contains data on 5000 customers of Universal Bank. The data include customer demographic information (age, income, etc.), the customer’s relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign. In this exercise, we focus on two predictors: Online (whether or not the customer is an active user of online banking services) and Credit Card (abbreviated CC below) (does the customer hold a credit card issued by the bank), and the outcome Personal Loan (abbreviated Loan below). Partition the data into training (60%) and validation (40%) sets. a. Create a pivot table for the training data with Online as a column variable, CC as a row variable, and Loan as a secondary row variable. The values inside the table should convey the count. In R, use…
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V5. min jee wants to combine the sales data from each of the art fairs. switch to the combined sales worksheet and then update the worksheet as follows. in cell A5 enter a formula without using a function that references cell a5 in the Madison worksheet. copy the formula from cell a5 to the range a6:a8 without copying the formatting. in cell b5, enter a formula using the sum function, 3d references, grouped worksheets that totals the values from cell b:5 in the chicago: madison worksheets.
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Please explain A major airline decides it wants to board passengers passed on their priority status. The passengers will board the airplane one at a time in a single file order. The higher the priority passenger rating, the earlier they should board (assume there are no ties). What data structure should this airline use? How long will it take to board N passengers in Big-O? Note: We do not know when the passengers will arrive at the gate, but we will always want to allow the passenger with the highest priority to board first. Group of answer choices a. A priority queue is the best data structure. The priority queue uses a max-heap such that passengers with the highest priority will be at the top of the heap. In order to board N passengers, it will take O(nlog(n) time. N removals for each of the passengers and then log(n) time for each removal to rebuild the max-heap structure. b. A binary search tree is the best data structure. The binary search tree will search for…
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