This GB513 Unit 7 two-sample comparison example tests a menu redesign with an unequal-variance t test on sampled checks, then confirms it with a paired before-and-after test. Searches like "gb 513 unit 7 assignment example", "gb513 unit 7 sample" and "gb513 unit 7 example" land here.
What a finished GB513 Unit 7 two-sample comparison looks like
The comparison fills about four pages, with an Excel appendix. A paragraph introduces the pilot and names the decision: reprint menus at forty locations or keep the old design. A side-by-side summary table follows, pilot and control, showing sample size, mean check, standard deviation and a 95 percent interval for each. The main test compares 120 randomly sampled checks from each group using the two-sample t test assuming unequal variances, with hypotheses, test statistic, p-value and degrees of freedom set out in a short block. A second, smaller test compares each pilot location's average check before and after the change, a paired design that controls for location. The discussion weighs statistical against practical significance, converting the difference into annual revenue across the chain.
How a GB513 Unit 7 example is structured
The design question is settled before the test is chosen, and the paper says so. Independent samples fit the pilot-versus-control comparison because different restaurants and different diners produced the two groups; the paired test fits the before-and-after data because each location serves as its own control. The summary table precedes both tests so the reader sees the raw gap, about $1.40 a check, before learning whether it is significant. The unequal-variance version is chosen after comparing the two standard deviations, and a sentence explains that choice rather than defaulting. Both tests share one layout, which makes the agreement between them easy to see. The practical-significance section follows the statistics, since a real difference can still be too small to pay for a reprint. The recommendation cites both results and the revenue estimate together.
Why two tests, not one
One paragraph matches each design to its data. Pilot and control are independent groups; the same eight restaurants before and after are pairs. Naming the design is frequently its own rubric line.
Groups side by side
Pilot and control figures are lined up in the summary table so the gap is visible immediately. Each column carries its own interval, and overlap between them is noted without being treated as a test.
Unequal variances, justified
Standard deviations of $6.10 and $8.40 lead the paper to Welch's version, reported through Excel's matching tool. A sentence explains that the pooled test assumes equal spread, which these groups do not show.
Pairs that control for location
Differences are computed per restaurant, then tested against zero. The paired result agrees with the independent one, which strengthens the case more than either test alone.
Is $1.40 worth a reprint?
Multiplying the difference by annual check volume gives a revenue estimate, set against printing and staff training costs. The paper recommends a staged rollout, beginning with the busiest locations.
Where marks go in GB513 Unit 7
Choosing the wrong design is the costliest error in a two-sample comparison: running an independent test on before-and-after data from the same stores, or pairing observations that have no natural match. Graders in most sections mark that as a setup failure that no amount of correct arithmetic recovers. The equal-variance tool used without comment is a smaller but common deduction. Reporting a significant difference with no statement of its size, or its size in dollars, misses the practical-significance row that many GB513 rubrics include. Hypotheses stated for sample means, a one-tailed test chosen after seeing the direction of the data, and conclusions that say the new menu causes higher spending without noting how locations were chosen all draw comments. Clear tables and consistent units earn back more than they cost.
Get a GB513 Unit 7 example written to your instructions
Two groups, two conditions or two time periods: send whatever your GB513 Unit 7 prompt compares, with the data and the rubric, and a custom comparison comes back in 24 to 48 hours. It names the design before choosing the test. The first request is free, and a post for the unit's discussion board can be requested on its own.
GB513 Unit 7 questions, answered
How do I decide between the paired and independent t test?
Ask whether each observation in one group has a natural partner in the other. The same store before and after a change, the same employee under two schedules, or the same customer rating two products are pairs. Different stores or different customers are independent. The menu example settles this in one sentence before running anything, since the design sets the test.
Excel offers equal and unequal variance t tests. Which one is right?
When the two sample standard deviations differ noticeably, the unequal-variance version is the safer choice, and many statisticians use it by default. The equal-variance test is fine when the spreads are similar. What matters in GB513 is that the paper states which one was used and why, rather than accepting whichever tool appeared first in the menu.
The Unit 7 discussion board asks about a comparison too. Is that a separate piece?
Usually, yes. The board tends to pose a smaller scenario and asks which test fits and what a result would mean, often in one calculation and a paragraph. A sample post can be written to that question on its own. It tends to reward clear design reasoning over lengthy output, and replies to classmates follow the same logic.