Expected values by script, [8.6] days for surgery against [7.2] for antibiotics, anchor a decision tree for NU743 Unit 5 whose sensitivity analysis finds the tipping points. Searches like "nu 743 unit 5 assignment example", "nu743 unit 5 sample" and "nu743 unit 5 example" land here.
What a finished NU743 Unit 5 decision tree looks like
One page of diagram, [900] words of text and a [30]-line script in an appendix. The tree runs left to right: a square decision node, two arms, and chance nodes carrying probabilities in brackets, [0.05] for a complication after planned surgery, [0.25] for antibiotic failure within [90] days, [0.15] for recurrence later in the year among early successes. Each terminal branch ends in a days-lost figure. A table beside the diagram lists every input with its source and its plausible range. The text rolls the tree back branch by branch, so the [7.2] can be checked by hand as well as by code. Two one-way sensitivity analyses follow, each plotted as a line crossing the surgical value, and a closing section returns the numbers to the patient, whose own weighting of an operation the tree cannot hold.
How a NU743 Unit 5 example is structured
Decision framing comes first, one sentence naming the patient, the two options and the single outcome measure, days away from normal activity across one year, with a note on what that measure leaves out. The diagram follows, then the input table, because a reader should see the shape before the numbers. Rollback is written out rather than asserted: the success branch averages [5.29] days once recurrence is folded in, the failure branch [12.96], and weighting them by [0.75] and [0.25] gives [7.21]. Sensitivity analysis is where the tree earns its place. Antibiotic failure would have to reach about [43] percent before surgery wins, near rates some trials report when an appendicolith is present, which is why that CT finding is named as the one that would flip the recommendation. A limits section closes the paper.
One outcome, named with its gaps
Days away from normal activity was chosen because the patient is paid by the job. The paper concedes that the measure ignores pain, anxiety about recurrence and the value some people place on avoiding an operation altogether.
Inputs a reader can trace
Each probability carries a citation and a range, and each days-lost figure is labeled an estimate for this composite patient. Brackets mark every value as illustrative, so none reads as a rate to quote at a real bedside.
Rolled back by hand and by code
The appendix script and the hand calculation reach the same [7.21] and [8.60]. Showing both lets a grader verify the arithmetic without running anything, and lets a classmate change one input and watch the result move.
Where the choice flips
Surgery overtakes antibiotics if early failure passes about [43] percent or if later recurrence passes about [37] percent. The paper reports both thresholds and states which is more plausible for this patient, given no appendicolith on imaging.
What the tree cannot weigh
A [1.4]-day advantage is small beside a patient's dread of either path. The closing section treats the tree as one input to shared decision-making and names the questions a clinician would still ask before recommending anything.
Where marks go in NU743 Unit 5
Most graders will recompute at least one branch, so rollback errors are found quickly and cost more than their size suggests. Trees with probabilities that do not sum to one at a chance node, or with a terminal value that double-counts the antibiotic days, draw comments. Unsourced inputs are the other large deduction; a probability without a citation or a stated range turns the expected value into an opinion with decimals. Sensitivity analysis is often weighted heavily, and a tree with none, or with one that varies an input nobody doubts, gives up much of its value. Credit rises when a threshold is connected to a clinical finding, as the appendicolith is here. A diagram too dense to read, branch-end values never defined and a conclusion that overstates a one-day margin cost smaller amounts.
Get a NU743 Unit 5 example written to your instructions
Share the clinical choice your prompt sets, the outcome measure if one is specified, and the rubric. A first custom sample is free and returns within 24-48h with the tree drawn, every input sourced and bracketed, the rollback shown by hand and by a short script, and the threshold where the recommendation would reverse.
NU743 Unit 5 questions, answered
Does a decision tree need utilities, or are probabilities enough?
Probabilities alone describe what might happen; the tree needs a value at each end to say which path is better. That value can be a utility score, a cost, or a natural unit such as days lost, as it is here. What matters is defining it once, applying it consistently, and saying what it leaves out.
What software should draw and compute the tree?
Whatever your section allows. Spreadsheets, dedicated decision software and short scripts all work, and some faculty accept a hand-drawn diagram with the rollback written out. The sample shows the calculation by hand beside a brief script so a reader can verify it either way. Your prompt may also say whether the working itself is submitted.
Where do the probabilities come from in a composite case?
From published trials and reviews, cited, with a range around each estimate. The sample brackets every figure so it reads as illustrative rather than as a rate for a real patient. Your own tree should draw on sources your faculty accept and show why each estimate fits the patient in your prompt.