Six worked scenarios make up this probability problem set for GB513 Unit 3, each carrying its setup, Excel function, answer and a line of business meaning. Searches like "gb 513 unit 3 assignment example", "gb513 unit 3 sample" and "gb513 unit 3 example" land here.
What a finished GB513 Unit 3 probability problem set looks like
Numbered problems run down the page, each in the same four parts: the given information restated, the probability rule or distribution chosen and why, the calculation with its Excel function shown, and a result sentence in plain terms. Problem 1 builds a contingency table of 500 customers by age group and whether they bought an extended warranty, then reads joint, marginal and conditional probabilities from it. Problem 2 tests two events for independence. Problems 3 and 4 use BINOM.DIST for defective units in a shipment of twenty. Problem 5 applies POISSON.DIST to walk-in customers per hour at the service counter. The last compares the expected value of two warranty prices. Answers are rounded to four decimals and restated as percentages where a manager would read them that way.
How a GB513 Unit 3 example is structured
Each problem stands alone, so a grader can mark it without reading the others, but the sequence moves from counting to modeling. The contingency table comes first because it grounds probability in actual customers before any formula appears. Conditional probability follows directly from the table, which makes the difference between the probability of a warranty purchase given a young buyer and the reverse visible on the page. The independence check reuses the same table. The binomial problems state all four conditions before calculating, since the setup carries as much credit as the answer. The Poisson problem names its rate and time interval and links the result to staffing the counter. Expected value closes the set because it turns probability into a pricing decision, the kind of judgment the rest of the course keeps asking for.
Givens restated in words
Each problem opens by repeating what is known in a sentence, including units and the time frame. It sounds redundant, yet it is where misread prompts show up, and setup credit is frequently awarded on its own line.
A contingency table of real counts
Rows for three age groups, columns for warranty purchased or declined, totals on both margins. Every probability in problems 1 and 2 is read from these cells, and the cell used is named beside each answer.
Distribution chosen, conditions checked
Before BINOM.DIST is called, the problem confirms a fixed number of trials, two outcomes, a constant probability and independence. The Poisson problem confirms a rate over a fixed interval. Function syntax appears in full so the result can be reproduced.
At most, at least, exactly
Cumulative questions are the usual trap. The example shows the complement explicitly when a problem asks for at least three defectives, rather than leaving the reader to guess which tail was computed.
Expected value as a pricing call
Two warranty prices are compared by expected profit per sale, using claim probabilities and average repair costs. The result sentence says which price the retailer should choose and how sensitive that choice is to the claim rate.
Where marks go in GB513 Unit 3
Credit in this problem set tends to split three ways: setup, computation and interpretation. Setup losses come from choosing the wrong distribution, often a binomial where events are not independent or a Poisson with the rate scaled to the wrong interval. Computation losses cluster on cumulative probabilities, especially at least and more than, where the complement is computed from the wrong value. Conditional probability read in the wrong direction, the probability of age given purchase instead of purchase given age, is marked wrong outright in most sections. Interpretation is the row that separates strong papers: a bare decimal earns less than the same figure turned into a staffing or pricing consequence for the retailer. Rounding intermediate steps too early, and omitting the Excel function when the prompt asks for it, draw smaller deductions.
Get a GB513 Unit 3 example written to your instructions
The scenarios your GB513 section set for Unit 3 are what the sample works, not the retailer used above. Send the problem list with its instructions and rubric; a custom set arrives in 24 to 48 hours, each answer carrying its function and its business sentence. There is no charge for the first one.
GB513 Unit 3 questions, answered
How do I know whether a problem is binomial or Poisson?
Look at what is being counted. If there is a fixed number of trials, such as twenty units inspected, and each is a success or failure, the problem is binomial. If the count happens over an interval of time or space with no fixed ceiling, such as arrivals per hour, it is Poisson. The sample puts that reasoning in one line before each calculation.
Does the problem set need the Excel functions written out?
In many GB513 sections, yes, or at least the inputs to them. Showing =BINOM.DIST(2,20,0.05,TRUE) lets a grader see which tail you computed and whether the cumulative flag was right. When the prompt calls for hand calculation instead, the example shows the formula with values substituted. Either way the method must be visible, not just the answer.
Why does the example turn every probability into a sentence?
Because the course treats probability as an input to decisions. A result of 0.1887 means little to a store manager; saying that roughly one hour in five will see more than six walk-ins, which exceeds what one technician can handle, gives the same number a use. Rubrics across GB513 reserve credit for exactly that translation.