In GB532 Unit 5, the sampling plan stratifies a propane dealer's automatic accounts by change in fuel use, computes 653 target completes and names who the list omits. Searches like "gb 532 unit 5 assignment example", "gb532 unit 5 sample" and "gb532 unit 5 example" land here.
What a finished GB532 Unit 5 sampling plan looks like
A formula box and two tables anchor five pages. Target population and frame are defined in separate sentences: residential households heating with the firm's propane, and the billing list of automatic-delivery accounts active through last winter. Stratum A holds the 1,140 flagged accounts, each burning at least a fifth fewer gallons per degree day than a year earlier; stratum B holds the other 7,020. The formula box shows the calculation for estimating a proportion within 5 points at 95 percent confidence, 384 before correction, then 288 for stratum A and 365 for stratum B after the finite population correction. At an expected 30 percent response, 960 and 1,217 households are invited. A weighting table gives 3.96 and 19.23 as the weights that restore population proportions, and the overall margin, allowing for that weighting, of about 4.5 points.
How a GB532 Unit 5 example is structured
Definitions come first because every later choice depends on the distance between the population the manager cares about and the list the firm can actually draw from. The coverage section follows immediately and treats that distance as the plan's main risk rather than a footnote. Stratification is justified by purpose: stratum A is small but holds most of the heat pump homes, so a proportionate draw would yield too few of them to describe. The size calculation is shown step by step, with the assumed proportion of one half stated as the conservative choice. Response rate is treated as an assumption with a source, earlier customer mailings, and the invitation counts follow from it. Weighting comes after sizing, since disproportionate strata need it before any overall estimate is reported. A nonresponse section closes the plan with a reminder mailing and a comparison of respondents to the frame on K-factor.
Population and list, defined apart
Residential propane households are the population; the automatic-delivery billing list is the frame. The plan names the 1,240 will-call accounts as the largest group sitting between them, since they have no fill history to flag.
Why the strata are unequal
Stratum A is 14 percent of the frame but holds most suspected heat pump homes. Sampling it at a far higher rate yields enough of them to describe, and weights correct the overall picture afterward.
Size computed, not chosen
For a proportion near one half, 1.96 squared times 0.25, divided by 0.05 squared, gives 384. Corrected for the finite stratum sizes, that becomes 288 and 365 completes, then 2,177 invitations at a 30 percent return.
Weights and the price of oversampling
Unequal weights raise the variance of overall estimates. The plan computes a design effect near 1.37, an effective sample of about 477, and a combined margin of roughly 4.5 points.
People no draw from this list can reach
Will-call buyers, renters whose landlord holds the account, customers lost last season and homes heating with oil or wood all fall outside. Each is named with a sentence on how its absence might bend the estimates.
Where marks go in GB532 Unit 5
Sampling plans earn their marks through the frame far more than through the formula. A plan that states a sample size and never says what list the sample comes from has skipped the step graders check first. Coverage gaps named honestly earn credit here, and the will-call and former customers named in this plan are the kind of omission instructors expect to see acknowledged. Probability methods are expected to be named precisely; calling a stratified draw random, or a convenience sample representative, costs accuracy points. Size calculations with no stated confidence, margin or assumed proportion read as arithmetic without reasoning. Oversampling without weighting produces overall estimates that are simply wrong, and sections that cover weighting grade it. Nonresponse ignored, as though every invited household will answer, is a recurring deduction.
Get a GB532 Unit 5 example written to your instructions
Sampling plans depend on the list available, so describe the frame your GB532 case offers, even if it is imperfect, and send it with the Unit 5 prompt and rubric. Within 24-48h a free first sample returns with the strata argued, each size computed in the open and the uncovered groups named.
GB532 Unit 5 questions, answered
Which sample size formula should the plan use?
The one your course text presents, most often the formula for estimating a proportion or a mean within a chosen margin at a chosen confidence level. State every input: confidence, margin, the assumed proportion or standard deviation, and whether a finite population correction applies. Graders tend to check the inputs and reasoning more than the final number.
Is a convenience sample ever acceptable in GB532?
For exploratory work, often yes, such as a handful of interviews to learn what questions to ask. For estimates about a population, it cannot support inference, and a plan should say so rather than dress it up. If your case leaves no alternative, name the method honestly and limit the conclusions to what it permits.
How should I estimate the response rate?
From the best evidence available: earlier surveys by the same firm, published rates for similar mail or web studies, or the course text's guidance. State the figure and its source, then compute invitations from it. A plan that sizes the completed sample and forgets that many invitations go unanswered will come up short.