Five health scenarios, each solved with a named rule and read back as a sentence about patients, make up the probability problem set shown for HS345 Unit 4. Searches like "hs 345 unit 4 assignment example", "hs345 unit 4 sample" and "hs345 unit 4 example" land here.
What a finished HS345 Unit 4 probability problem set looks like
Every problem fills about half a page under the same four labels: scenario, rule, work and meaning. Problem 1 supplies a two-way table of 1,200 composite discharges by destination and 30-day readmission, and computes an overall readmission probability of 11.0 percent against 19.4 percent for patients discharged to skilled nursing. Problem 2 uses blood type shares given in the prompt to find that 8.1 percent of donors could supply a B-negative patient, and that ten random donors contain none about 43 percent of the time. Problem 3 asks how surprising four surgical site infections in 60 procedures are against a 2.5 percent benchmark. Problem 4 places a cholesterol reading of 240 on a normal curve. Problem 5 counts false alarms across a twenty-indicator dashboard.
How a HS345 Unit 4 example is structured
The set moves from counting to modeling. Problems 1 and 2 need no distribution at all, only a table and the rules for combining probabilities, and they come first so that conditional probability and the complement are secure before any formula appears. Problem 1 closes by testing independence: readmission and destination would be independent if every row matched the overall 11.0 percent, and they plainly do not, though the sheet refuses to read causation into that. Problem 3 introduces the binomial, checking its conditions before calculating, and concludes that four infections where 1.5 were expected would occur about 6.3 percent of the time with nothing wrong. Problem 4 shifts to a continuous measure. Problem 5 ends on an idea later units will need: with twenty indicators each tested at 0.05, the chance of at least one false signal is 64 percent.
Rows that do not match the margin
Readmission runs 8.1 percent after discharge home, 13.0 after home health and 19.4 after skilled nursing. Skilled nursing holds 15 percent of discharges and about 27 percent of readmissions.
Two compatible types, added
O-negative and B-negative are mutually exclusive, so their shares add to 8.1 percent. The complement rule then shows about 36 donors are needed for a 95 percent chance of finding one.
Four infections where 1.5 were expected
Binomial conditions are listed first, with a note that surgeons and case mix make patients less than identical. The probability of four or more is about 6.3 percent, not rare enough to prove a problem.
A reading of 240 on the curve
With a mean of 190 and a standard deviation of 38, z is about 1.32 and roughly 9.4 percent of adults sit higher, about 47 in a screening of 500.
Twenty chances to be wrong
One minus 0.95 to the twentieth power gives 64 percent. The sheet translates this into an expected count, one false alarm per dashboard review, and names the later topic it previews.
Where marks go in HS345 Unit 4
Item-by-item scoring is common on problem sets at this stage, with setup, calculation and interpretation marked separately and setup often worth the most. Setup credit requires naming the rule or distribution and stating why it applies: a binomial answer that skips the fixed-number and constant-probability conditions tends to lose part of the row despite a correct number. Calculation credit hinges on complements, where four or more is regularly confused with exactly four. Interpretation credit belongs to the final line of each item, which says what the number means for the patients, donors or managers involved. Frequent deductions include adding probabilities of events that can occur together, treating conditional probabilities as if order did not matter, reporting 0.063 without saying whether it is surprising, and reading the readmission table as proof that nursing facilities cause readmissions.
Get a HS345 Unit 4 example written to your instructions
Every HS345 Unit 4 set uses its own scenarios, and the custom version solves those in your prompt, not these five. Along with the problems, include the rubric and any table or data the set supplies. The first sample is free and returns within 24-48 hours, with each rule named, each complement shown and every answer read back in plain words.
HS345 Unit 4 questions, answered
Do four infections in 60 procedures mean the unit has a problem?
Not on this evidence alone. Four or more would happen about 6.3 percent of the time even if the true rate matched the 2.5 percent benchmark, so chance remains a reasonable explanation. The example says a review of the four cases is still sensible, since a probability answers how surprising a count is, not whether each infection was preventable.
Why does the readmission problem avoid saying skilled nursing causes readmissions?
Because patients are not assigned to destinations at random. People discharged to skilled nursing are usually older and sicker, and that alone would raise their readmission probability. The table shows the two variables are not independent, which is a statement about association. Explaining the gap would require data on how ill each group was at discharge.
Can I use software for the binomial and normal problems?
Usually. Excel's BINOM.DIST and NORM.DIST functions, a statistics package or an online calculator are accepted in most sections as long as the inputs are shown. The example writes each formula with its values, then reports the software result as a check. What a grader needs to see is the rule chosen and the tail used.