A due diligence sample of 200 card accounts, estimated twice, simple random then stratified by score band, with each interval computed by hand: GF582 Unit 4's sampling exercise. Searches like "gf 582 unit 4 assignment example", "gf582 unit 4 sample" and "gf582 unit 4 example" land here.
What a finished GF582 Unit 4 sampling exercise looks like
Four pages: a design section, two estimate tables and a sample size calculation. The design section defines the population, 6,240 open accounts on a cutoff date, the frame, the servicer's account list, and the parameters, mean balance and the share 30 or more days past due. The simple random sample returns a mean balance of 3,087.67 dollars with a standard deviation of 2,220.84; the finite population correction of 0.9839 brings the standard error to 154.51 and the 95 percent interval to 2,782.98 to 3,392.36. Fifteen of 200 accounts are delinquent, 7.5 percent, with an interval from 3.9 to 11.1. The stratified table allocates 42, 92 and 66 accounts across three score bands and reaches 2,994.65 with a standard error of 120.05. The last section sizes a sample for a margin of 150 dollars.
How a GF582 Unit 4 example is structured
Design precedes arithmetic, since an estimate is only as good as its frame. Population, frame and parameter are defined separately, and a paragraph notes what the frame excludes: accounts closed in the prior month, which the buyer will not acquire anyway. The simple random estimate comes next with every step shown, including a finite population correction that trims only 1.6 percent from the error at this sampling fraction but is reported because the method asks for it. The delinquency interval carries a caution that 15 events make it wide. Stratification follows as the procedure the question suits: balances differ sharply by score band, 5,017 below 660 against 1,553 above 740, so proportional allocation removes that variation from the error. Variance falls to 0.604 of the simple random figure. Sizing asks for 842 accounts, 742 after correction, for a 150-dollar margin.
Population, frame, parameter
6,240 open accounts, the servicer's list as of the cutoff date, and two parameters: mean revolving balance and the share 30 or more days past due. Each is defined before a single account is drawn.
A small correction, shown anyway
Two hundred accounts are 3.2 percent of the population, so the correction factor of 0.9839 trims the standard error only from 157.04 to 154.51 dollars. The exercise shows the step because the method criterion asks for it.
Delinquency on fifteen accounts
7.5 percent past due, interval 3.9 to 11.1. The text notes that the normal approximation is borderline with so few events and names an exact binomial method as a check.
Three bands, one estimate
Weights of 0.210, 0.460 and 0.330 combine band means of 5,017, 3,106 and 1,553 into 2,994.65. The standard error of 120.05 is 22 percent below the simple random figure for the same 200 accounts.
How many accounts the buyer needs
A margin of 150 dollars at 95 percent requires 842 accounts before correction and 742 after, which the exercise sets against the cost of pulling and reading each file.
Where marks go in GF582 Unit 4
Sampling exercises in GF582 lose the most when the sample is treated as the population: a mean reported with no standard error, or an interval computed but never read back into the question. Most sections want the population, frame and parameter named separately, and papers that blur them usually lose the design criterion before any arithmetic is checked. Omitting the finite population correction when the sampling fraction is large draws a deduction in many sections, as does applying it silently when the fraction is tiny. Stratified estimates that average the band means without weighting them by band size give a wrong answer with correct-looking steps. Sample size calculations that use a guessed standard deviation without saying where it came from, or that forget the correction, cost the planning marks.
Get a GF582 Unit 4 example written to your instructions
A population list, a drawn sample or only summary figures: whichever the case for Unit 4 provides will do, alongside the prompt and rubric. The custom exercise defines the frame and parameter, estimates with the interval worked by hand and, where the data allow, compares designs. Expect it inside 24-48h, with the first one free.
GF582 Unit 4 questions, answered
When does the finite population correction matter?
When the sample is a noticeable share of the population, commonly taken as more than about 5 percent, though some texts use a lower threshold. Below that, the correction barely changes the standard error. Above it, leaving the correction out overstates uncertainty. Stating the sampling fraction and whether you applied the correction is usually enough to satisfy the rubric.
Why stratify if a simple random sample is unbiased?
Because unbiased is not the same as precise. When a population contains groups that differ sharply on the measure, such as balances by credit score band, sampling within each group removes the between-group variation from the error. The estimate stays unbiased and its interval narrows. The gain is largest when the groups differ most, so the strata should follow the variable being measured.
Can I use a convenience sample if the case provides one?
Use it, but say what it is and what it cannot support. A sample drawn from the first accounts on a list, or from files that were easy to reach, may not represent the population, and the interval formulas assume random selection. Describing the likely direction of any bias, and what a random draw would change, usually earns the design credit.