Three intervals from 216 sampled accounts, t, bootstrap and Wilson, are estimated and read in GB701's Unit 5 exercise, two of them checkable against known values. Searches like "gb 701 unit 5 assignment example", "gb701 unit 5 sample" and "gb701 unit 5 example" land here.
What a finished GB701 Unit 5 confidence interval exercise looks like
Five pages, a results table and one figure. A sample paragraph reports what the Unit 4 plan produced: 234 files drawn, 13 excluded because invoicing method switched mid-year and 5 for incomplete records, leaving 216. Mean days to pay is estimated first, at 39.79, with a standard deviation of 14.35, a standard error of 0.976 and a t critical value of 1.971 on 215 degrees of freedom, giving 37.86 to 41.71; the ERP mean of 40.46 falls inside. The second, a percentile bootstrap from 5,000 resamples, brackets the sample median of 36.70 between 35.15 and 39.50, and the ERP median of 37.8 again falls inside. The third estimates the share of accounts with at least one disputed invoice: 174 of 216, or 80.6 percent, with a Wilson interval of 74.8 to 85.3.
How a GB701 Unit 5 example is structured
The exercise is sequenced from verifiable to new. Estimating quantities the ERP already knows is not wasted effort: it tests whether the sample represents the frame before the sample is trusted with anything unknown, and the paper says so. The late share provides a third check, 8.8 percent in the sample with a Wilson interval of 5.7 to 13.3 against 10.7 percent in the ERP. Method is matched to each quantity and defended. The t interval suits the mean because 216 observations tame the skew reported in Unit 2. The median needs a bootstrap, since no simple formula serves a skewed variable. The dispute proportion sits near 80 percent, where the Wald interval, 75.3 to 85.8, is shown beside the Wilson and set aside. A closing note addresses the finite population correction, which would narrow the mean's half-width from 1.92 to 1.74 days.
The sample, accounted for
Every exclusion is counted and explained before any estimate appears. Readers see 234 drawn, 18 removed and 216 analyzed, with the stratum of each exclusion, so a committee can judge whether the losses could have tilted the sample toward faster or slower payers.
An interval that can be checked
The mean's interval, 37.86 to 41.71 days, contains the known ERP mean of 40.46. That capture is read as evidence the draw behaved, with a caution that one captured value is not proof, since 95 percent intervals miss one time in twenty by design.
Bootstrapping a skewed median
Five thousand resamples of the 216 accounts produce a distribution of medians whose 2.5th and 97.5th percentiles bound the interval. Seed and resample count are reported, and the interval's asymmetry around 36.70 is described, because skewed data rarely produce symmetric uncertainty.
Disputes, estimated for the first time
No ERP field records disputes, so the coded files supply the only estimate: four accounts in five disputed at least one invoice during the year. The lower bound, 74.8 percent, is the figure the paper says a cautious manager should plan around.
Why Wilson replaces Wald
Near 80 percent, the Wald formula places its limits symmetrically and can overstate precision toward the upper end. The Wilson interval corrects that, and the paper prints both so the difference is visible rather than asserted.
Where marks go in GB701 Unit 5
Interval work in GB701 is graded heavily on interpretation. Writing that the true mean has a 95 percent chance of lying inside one computed interval misreads the procedure and draws a correction in nearly every section. Methods chosen without defense, a t interval applied to a skewed median or a Wald interval used near the edge of the proportion scale, cost credit even when the arithmetic is right. Exclusions reported vaguely, or not at all, undermine every estimate downstream. Instructors typically reward the verification step when the frame permits it, and they also expect the paper to explain why capturing a known value once is reassuring rather than conclusive. Intervals printed to four decimals for a variable measured in days suggest precision the data cannot carry. Each interval also needs a sentence in business terms.
Get a GB701 Unit 5 example written to your instructions
Upload your data, or the summary statistics your section supplied, with the Unit 5 instructions and rubric. Each interval method gets matched to its quantity and defended, and each result becomes a sentence a manager could act on, in a custom exercise ready in 24-48h. The first sample is free of charge.
GB701 Unit 5 questions, answered
Which interval suits a skewed variable?
For the mean, a t interval usually holds up once the sample reaches a few dozen observations, because the sampling distribution of the mean is far less skewed than the data. For the median or a percentile, a bootstrap is the common choice. Whatever is used, a sentence explaining why it fits the variable is what instructors look for first.
How should a 95 percent confidence interval be interpreted?
As the product of a method that, repeated over many samples, captures the true value about 95 percent of the time. Any single computed interval either contains the value or does not. A safe written form says the data are consistent with values between the two limits, which avoids the probability misstatement instructors correct most often.
Is a bootstrap acceptable if the textbook never covers it?
Usually, provided the method is described clearly and cited. State the number of resamples, the type of interval, percentile or bias-corrected, and the software used. Some instructors prefer a formula-based method as the primary result, with the bootstrap as a check, so reading your instructions before choosing is worthwhile.