| Course | BUSI 820 Quantitative Research Methods (BUSI820) |
|---|---|
| Module/Week | 2 |
| Assignment | Discussion Forum 2 Main Thread |
| Paper type | Doctoral discussion thread and reply |
| Length | about 544 words (thread and replies). Course guide: the course guide keeps the forum's word counts and rubric inside the course; this sample gives a main thread of about 400 words with a table of descriptive statistics, plus a reply of about 150 words to a classmate's Forum 1 thread |
| Format | APA 7 citations and reference list |
| Points | 25 |
| School | Liberty University Online |
| Program | DBA |
| Where it sits | Module/Week 2 in Liberty's published BUSI 820 course guide; current sections can differ |
| Updated | October 2026 |
Free sample paper for BUSI 820 Week 2
Discussion Forum 2: Main Thread and Forum 1 Reply
BUSI 820 Quantitative Research Methods, Discussion Forum 2 Main Thread (with the Forum 1 reply)
Thread by [Student Name]
The data set is illustrative, generated for this page with a fixed random seed and analyzed with the same statistics SPSS reports; the bank, the classmate and the prompt are composites standing in for the course's own; the books are real; the week, points and readings follow Liberty's public course guide for BUSI 820.
In Forum 1, I framed our bank's teller and personal banker turnover as a study of intention to leave. For this forum, I generated an illustrative data set with the structure our survey will have: 186 respondents from 22 branches, about a 62 percent response rate. Morgan et al. (2020) recommend that researchers describe every variable and check its distribution before choosing any inferential statistic. Table 1 reports the scale variables.
| Variable | Mean | SD | Min | Max | Skewness | Kurtosis |
|---|---|---|---|---|---|---|
| Intention to leave (5-25) | 13.47 | 4.12 | 5 | 23 | 0.09 | -0.66 |
| Supervisor support (6-30) | 20.22 | 4.56 | 7 | 30 | 0.21 | -0.28 |
| Branch size (FTE) | 17.33 | 8.55 | 6 | 34 | 0.71 | -0.71 |
| Tenure (months) | 32.46 | 31.11 | 2 | 165 | 2.01 | 5.03 |
Intention to leave averages 13.47 on a 5-to-25 scale, slightly below the midpoint of 15, with a standard deviation of 4.12, so most respondents fall between about 9 and 18. Its skewness of 0.09 is close to zero. Supervisor support averages 20.22 of a possible 30, meaning employees on average mildly agree that their supervisors support them, and its skewness of 0.21 is also small. Morgan et al. (2020) treat skewness between minus 1 and plus 1 as approximately normal, so both variables can be used in parametric tests. Branch size has a skewness of 0.71, within the rule but positive, because a few large branches employ many respondents; its median of 15 is below its mean of 17.33 for the same reason.
Tenure is the problem. Its skewness of 2.01 and kurtosis of 5.03 show a long right tail: most respondents have been with the bank for under two years, with a median of 21.5 months, while a few have stayed more than a decade. With a standard deviation nearly as large as its mean, tenure's average describes almost no one in the sample. Following Morgan and colleagues' guidance for positively skewed variables, I computed the base-10 logarithm of tenure. The transformed variable has a skewness of minus 0.21 and a kurtosis of minus 0.56, within the acceptable range, so log tenure will replace raw tenure as a control in later analyses, and I will report raw medians for readers.
The categorical variable, work arrangement, is described with frequencies: 115 respondents work fully on site, 44 hybrid and 27 rotate between branches. The small rotating group will matter when comparing groups, since unequal group sizes make the homogeneity of variance assumption more important.
Part II of Keller and Alsdorf (2012) describes how work becomes frustrating, pointless and selfish in a fallen world. Descriptive statistics can show that intention to leave is common, but not why work at a teller window feels frustrating to the people doing it; that will require listening as well as measuring.
Reply to Tamara (Forum 1)
Tamara, your Forum 1 thread on readmissions at your hospital framed a clear associational question about discharge education and 30-day readmission. One variable may need reclassifying. You listed patient satisfaction, recorded as poor, fair, good or excellent, as a scale variable and planned a Pearson correlation with the number of education minutes. Since nothing guarantees that the step from poor to fair equals the step from good to excellent, Morgan et al. (2020) would classify a single rating like this as ordinal. That changes the statistic: a Spearman rank-order correlation would suit an ordinal variable paired with a scale one. Alternatively, if your survey includes several satisfaction items, summing them into a scale and checking its skewness could justify treating the total as scale data and keeping your Pearson correlation. Which version does your hospital's survey allow?
References
Keller, T., & Alsdorf, K. L. (2012). Every good endeavor: Connecting your work to God's work. Dutton.
Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for introductory statistics: Use and interpretation (6th ed.). Routledge.
What the BUSI 820 Week 2 instructions ask
In the second week, students read chapters 3 and 4 of the SPSS text and Part II of Keller, then submit three items: a new forum thread (15 points), a reply in the first forum (10) and the week's 95-point assignment. Liberty's public guide counts nine forums and eight assignments across the course without printing their instructions. Because every weekly assignment is built on the textbook's own exercises and data files, the sample here covers the two forum posts. The chapters move from what variables are to how they behave: measures of central tendency and variability, the shape of distributions and the checks a researcher runs before choosing a statistical test.
How this BUSI 820 Week 2 example is built
The thread continues the turnover study introduced in Forum 1. It describes the illustrative data set, 186 respondents from 22 branches, and presents a table with the mean, standard deviation, minimum, maximum, skewness and kurtosis for intention to leave, supervisor support, branch size and tenure. It interprets each variable against Morgan and colleagues' guidance: intention to leave and supervisor support are approximately normal, branch size is moderately skewed but within the rule of thumb, and tenure is strongly positively skewed. The thread applies a base-10 log transformation to tenure and shows that skewness falls from 2.01 to negative 0.21. A short note connects Keller's Part II, on work's frustrations, to what the descriptives cannot show. The reply follows.
BUSI 820 Week 2 grading rubric: where the points go
The main thread is judged on correct computation and interpretation of descriptive statistics and on sound decisions about assumptions. Readers look for statistics reported clearly, ideally in a table, interpretations that use the numbers rather than repeating them, a stated rule for judging normality and a defensible response when a variable fails it. The reply earns its points by helping a classmate with something specific in their Forum 1 thread, such as a level of measurement or a research question that does not match its statistic. Accuracy about Morgan and colleagues' rules matters. Faith integration, where the prompt invites it, should be brief and relevant. The course's rubric sets the details.
BUSI 820 Week 2 help: mistakes that cost points
Descriptive threads often paste SPSS output without saying what it means. After reporting each statistic, write one sentence about what it tells you for your study. State the rule you use for normality, such as Morgan and colleagues' guideline that skewness between minus 1 and plus 1 is acceptable, and apply it to every scale variable. When a variable fails, explain your response, whether transformation, a nonparametric test or reporting the median. Round consistently, usually to two decimals. In the reply, read the classmate's Forum 1 thread again before writing, and focus on one improvement they can actually make, such as reclassifying a variable or rewording a question.
Related BUSI 820 sample papers
Other BUSI 820 weeks
- BUSI 820 Week 1: Forum 1: Variables and Questions
- BUSI 820 Week 3: Forum 3: Choosing the Statistic
- BUSI 820 Week 4: Forum 4: Chi-Square and Cramer's V
- BUSI 820 Week 5: Forum 5: Correlation and Regression
- BUSI 820 Week 6: Forum 6: Independent t Test
- BUSI 820 Week 7: Faith Integration: Honest Data
- BUSI 820 Week 8: Forum 8: ANOVA and Faith Reply
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BUSI 820 Week 2 questions, answered
What is due in BUSI 820 Module/Week 2?
A second forum thread and the first reply, 25 points between them, plus the 95-point Assignment 2, while students read the chapters on descriptive statistics and assumptions and Keller's Part II.
Where can I find a free BUSI 820 Week 2 sample paper?
Here you will find a complete BUSI 820 Week 2 thread with descriptive statistics and assumption checks for a bank turnover survey, plus a reply to a classmate.
How do you check normality in SPSS?
Morgan and colleagues suggest examining skewness, with values between minus 1 and plus 1 treated as approximately normal, alongside histograms; a variable outside that range may need a transformation or a nonparametric test.
When should you log-transform a variable?
When a scale variable is strongly positively skewed, such as tenure or income, a log transformation often brings it close to normal so parametric statistics can be used.
Is a Likert rating ordinal or scale?
A single Likert item is ordinal, but a summated scale built from several items is usually treated as scale data when its distribution is approximately normal.
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