"Comparing the cost of care provided to Medicare beneficiaries assigned to primary care nurse practitioners and physicians" is a study that
<h3>What is the cost of Medicare according to the above study?</h3>
The study shows that after controlling for demographics, geography, comorbidities, and proclivity to visit an NP, Medicare evaluation and management payments for patients allocated to an NP were $207, or 29%, less than PCMD assigned beneficiaries.
The similar tendency was seen for inpatient and total office visit payment amounts, with NP-assigned beneficiaries receiving 11 and 18 percent less, respectively. The work component of relative value units yields similar results.
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Answer: Wow that's really cool!
Answer:
An array.
Explanation:
An array can be defined as a structure that organizes data in a list that is commonly 1-dimensional or 2-dimensional.
Simply stated, an array refers to a set of memory locations (data structure) that comprises of a group of elements with each memory location sharing the same name. Therefore, the elements contained in array are all of the same data type e.g strings or integers.
Basically, in computer programming, arrays are typically used by software developers to organize data, in order to search or sort them.
Binary search is an efficient algorithm used to find an item from a sorted list of items by using the run-time complexity of Ο(log n), where n is total number of elements. Binary search applies the principles of divide and conquer.
In order to do a binary search on an array, the array must first be sorted in an ascending order.
Hence, array elements are mainly stored in contiguous memory locations on computer.
Answer:
4. Supervised learning.
Explanation:
Supervised and Unsupervised learning are both learning approaches in machine learning. In other words, they are sub-branches in machine learning.
In supervised learning, an algorithm(a function) is used to map input(s) to output(s). The aim of supervised learning is to predict output variables for given input data using a mapping function. When an input is given, predictions can be made to get the output.
Unsupervised learning on the other hand is suitable when no output variables are needed. The only data needed are the inputs. In this type of learning, the system just keeps learning more about the inputs.
Special applications of supervised learning are in image recognition, speech recognition, financial analysis, neural networking, forecasting and a whole lot more.
Application of unsupervised learning is in pre-processing of data during exploratory analysis.
<em>Hope this helps!</em>
