| Course | DDBA 8307B Quantitative Business Data Analysis Using SPSS |
|---|---|
| Week | Week 7 |
| Paper type | Association memo |
| Length | About 560 words, 4 pages |
| Format | Memo, APA 7 citations |
| School | Walden University |
| Program | Doctor of Business Administration (DBA) |
| Updated | October 2026 |
Free sample paper for DDBA 8307B Week 7
Memorandum
To: Vice President of Sales, Lakeview Medical Supply
From: Sales operations analyst
Date: October 12, 2026
Re: What the training and sales correlation does and does not show
The Result in One Sentence
Sales representatives who logged more training hours last year tended to have higher quarterly sales, a moderate positive association, but the data cannot show that training caused the higher sales.
The Table
I correlated each representative's total training hours in fiscal 2025 with average quarterly sales over the same year, for the 86 representatives who were employed for the full year at Lakeview Medical Supply, a composite distributor of surgical and wound-care products to hospitals and clinics in the upper Midwest.
Table 1
Correlations Among Training, Tenure, Territory and Sales (n = 86)
| Variable | Training hours | Quarterly sales | Years in role | Territory accounts | |
|---|---|---|---|---|
| Training hours | 1 | .38 | .09 | .27 | |
| Quarterly sales | .38 | 1 | .31 | .52 | |
| Years in role | .09 | .31 | 1 | .22 | |
| Territory accounts | .27 | .52 | .22 | 1 | |
Pearson correlations computed in SPSS. Training and sales: r(84) = .38, p < .001, 95 percent interval from .18 to .55.
Strength and Direction in Plain Terms
The correlation of .38 means that representatives with more training hours tended to have higher sales, and those with fewer tended to have lower sales. The relationship is moderate. Squaring the coefficient gives about .14, which means training hours and sales share about 14 percent of their variation; the other 86 percent is related to other things. The 95 percent interval runs from .18 to .55, so the true association could be modest or fairly strong. Cumming (2014) recommends reporting the interval rather than relying on the p value, because the interval shows how precisely the strength is known. Cohen (1992) suggested .30 as a rough marker of a medium correlation in the behavioral sciences, and .38 sits just above it.
A rank-based Spearman correlation gave a similar result, .35, which suggests the association is not driven by a few unusual representatives.
What the Coefficient Does Not Show
The coefficient does not show that training increases sales, for three reasons visible in the table itself. First, representatives with larger territories, measured by the number of active accounts, had both more training (r = .27) and much higher sales (r = .52). Larger territories may give representatives more reasons to take product training and more opportunities to sell, so territory size could account for part of the link. Second, the direction is unknown: successful representatives may seek out training because they sell more complex products, rather than selling more because they trained. Third, representatives chose their own elective training; motivated representatives may both train more and sell more. Field (2018) is blunt that correlation coefficients describe association, not causation, whatever their size.
What Would Get Closer to the Causal Question
A regression of sales on training hours, controlling for territory size and years in role, would show whether the association survives those factors. A stronger test would compare sales before and after a required training program rolled out to some regions before others. Either step would help you decide whether expanding the training budget is likely to pay.
What I Recommend Saying to the Sales Team
That representatives who train more tend to sell more, and that the company is looking into whether the training itself is the reason.
References
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159. https://doi.org/10.1037/0033-2909.112.1.155
Cumming, G. (2014). The new statistics: Why and how. Psychological Science, 25(1), 7-29. https://doi.org/10.1177/0956797613504966
Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). SAGE Publications.
The Walden DDBA 8307B Week 7 instructions
Week 7 asks you to interpret a correlation in a memo to a decision maker. Open with a single sentence stating the finding and its main limit together. Present the correlations table, including other variables that bear on the relationship. Describe strength and direction in plain terms, including shared variation and the confidence interval, and check robustness with a rank-based correlation. Then explain, using evidence in the table, why the correlation does not show cause: possible third variables, the direction of influence and self-selection. Suggest analyses or designs that would get closer to the causal question. Close with what the decision maker can safely say. Cite sources on estimation and on interpreting correlations.
How the DDBA 8307B Week 7 example is put together
The memo leads with its one-sentence finding and limit. A four-by-four table correlates training hours, quarterly sales, years in role and territory accounts for 86 representatives, with the main result reported beneath. The strength section explains .38 in plain words, squares it to about 14 percent and reports the interval, citing Cumming, and places it against Cohen's medium marker; Spearman's .35 follows. The limits section uses the table: territory size relates to both training and sales, successful representatives may seek training and elective training attracts motivated people, with Field's warning about correlation. A regression controlling for territory and tenure and a staggered training rollout are proposed, and a closing sentence tells the vice president what to say.
Reading the DDBA 8307B Week 7 rubric
Instructors give the most credit to the sentence that states the finding and its limit together, since it governs how the result will be repeated. Describing strength in plain terms, with shared variation and an interval, shows the writer understands what a coefficient means. Instructors weigh the causal limits section heavily when the alternative explanations come from the data in the table rather than from a generic list. A robustness check earns credit. Proposing specific analyses or designs shows how to get closer to cause. The memo should be addressed to a real decision maker and end with language that decision maker can safely use. Sources should support interpretation, not decorate it. A plain closing line for the team shows the memo's purpose.
Common DDBA 8307B Week 7 mistakes, and how to avoid them
Correlation memos often bury the limit at the end where it is ignored. Write one sentence with both the finding and the limit and put it first. Report the coefficient, its interval and shared variance in words a manager understands. Look at your correlations table for variables related to both of your main variables; those are your strongest alternative explanations. Think about which direction influence could run. Check with a Spearman correlation. Suggest the next analysis. A tutor can help you build the correlations table in SPSS and read it. Name the variables you would add in a regression and why.
Get a DDBA 8307B Week 7 example written to your instructions
Send the Week 7 prompt and rubric and name the two variables your analysis relates. An association memo with its translation and cause-limiting sentence returns in 24-48h; a first request costs nothing. Its coefficient and scatterplot come from a made-up pair of variables, which keeps every figure in your submission tied to what you ran.
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DDBA 8307B Week 7 questions, answered
Where can I find a free DDBA 8307B Week 7 sample paper?
The full correlation memo, table and recommendations included, appears below and can be read at no cost.
What relationship does the DDBA 8307B Week 7 memo examine?
Training hours and average quarterly sales among 86 sales representatives at a medical-device distributor.
How strong is the correlation?
Moderate, at .38, with a 95 percent interval from .18 to .55 and about 14 percent shared variation.
Why doesn't it show training causes sales?
Larger territories relate to both, successful representatives may seek training and representatives chose their own training.
What can the vice president safely say?
That representatives who train more tend to sell more, and that the company is checking whether training is the reason.