A finished DBA-831 Topic 2 claim and design alignment paper example, matching a retailer's causal claim to designs that could test it and showing what a before-and-after comparison cannot conclude. Searches like "dba 831 topic 2 assignment example", "dba831 topic 2 sample" and "dba-831 topic 2 example" land here.
What a finished DBA-831 Topic 2 claim and design alignment paper looks like
The finished paper begins with the claim in the retailer's own words: coaching raised sales. It then states what kind of claim that is, causal, and what a causal claim requires, a credible estimate of what sales would have been without coaching. Four designs are compared against that requirement. A before-and-after comparison of coached stores cannot separate coaching from seasonality or a strong local economy. Comparing coached and uncoached stores fails if the best managers volunteered. A staggered rollout, in which regions start coaching at different times, supports a difference-in-differences comparison. Randomly choosing which stores begin first supports the strongest claim. Shadish, Cook and Campbell's catalog of threats to validity organizes the comparison, and a qualitative strand is proposed to explain how coaching changes what managers do day to day.
How a DBA-831 Topic 2 example is structured
Classification of the claim comes first, then its requirement, the candidate designs and a recommendation. The opening quotes the retailer's claim and classifies it as causal, distinguishing it from the descriptive statement that sales rose. The second part states what causal claims require, a counterfactual, and explains that no design observes one directly; each estimates it with a different comparison. A third part takes the four candidate designs in rising order of strength and lists the threats to validity each leaves open. Fourth, the paper sets the designs against the retailer's constraints, including its unwillingness to withhold coaching from some stores indefinitely. The fifth part explains why a staggered rollout meets that constraint. A sixth adds interviews with managers to explain mechanism rather than estimate effect, in the explanatory sequential form Creswell describes. The recommendation names the design and the exact claim it can support.
The claim classified before design
Saying that coaching raised sales is a causal claim, so the paper sets out what such a claim requires and judges every candidate design against it.
A counterfactual no design observes
What coached stores would have sold without coaching can only be estimated, and each design is described by the comparison it uses for that estimate.
Volunteer managers as a selection threat
If the strongest managers chose coaching first, a comparison of coached and uncoached stores measures who volunteered as much as what coaching did.
Staggered rollout as a workable compromise
Starting regions at different times gives every store coaching eventually while creating the comparison a difference-in-differences estimate requires.
Interviews that explain rather than estimate
A qualitative strand asks managers what changed in their routines, which can explain an effect but cannot by itself show that one occurred.
Where marks go in DBA-831 Topic 2
Deductions on this paper usually begin with a design chosen before the claim is classified. Papers that recommend a survey of managers' views on coaching have picked a method that cannot address whether sales changed. A before-and-after comparison presented as evidence of effect ignores everything else that changed over the same period. Comparisons of coached and uncoached stores that never ask how stores entered the program miss the selection threat the case plants. Qualitative interviews offered as proof that coaching worked confuse explanation with estimation, a distinction graders at this level expect to see drawn. Designs recommended without the retailer's constraints in view are ones the organization would never run, and a paper that never states the claim its chosen design can support has not finished the match.
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DBA-831 Topic 2 questions, answered
Why does a causal claim need a comparison?
Because a cause is defined by what would have happened without it, and that outcome is never observed for the same stores at the same time. Every causal design substitutes a comparison, such as earlier periods, other stores or randomly chosen groups, for the missing outcome. The claim is only as strong as the resemblance between that comparison and the counterfactual, and so the example judges designs by their comparisons.
When is qualitative work the right design?
When the question asks how or why something happens, what it means to participants, or which mechanisms are at work. Interviews can show how coaching changes a manager's routines in ways no sales figure captures. They cannot estimate how much sales changed. The example therefore pairs a quantitative estimate with a qualitative strand, so each method answers only the question it is suited to.
Is a randomized design realistic in a business?
Sometimes. Firms randomize prices, offers and interface changes routinely, and rollouts can be ordered at random when every unit will eventually be treated. Where randomization is impossible or unacceptable to leadership, quasi-experimental designs such as staggered rollouts offer a weaker but defensible comparison. The example shows both and explains what each can support, as coursework rather than advice on any real study.