Last updated: September 2026 · Reviewed by the Punjab Assignment Help business analytics team · Reading time: 12 minutes
Quick answer: MGMT11169 Assessment 2 at CQUniversity asks you to test whether technological adaptation (TA) is linked to sales growth (SG) for Australian SMEs in one industry you choose. You hand in two files: an Excel workbook that shows your data cleaning, descriptive statistics, Pearson correlation, p-value and a simple linear regression (SG = a + b × TA), and a 1,600-word business report for TechWave Digital Inc. The Excel model is worth 35% of the marks, so your formulas need to be visible and correct.
MGMT11169 Assessment 2 at a glance
| Item | Detail |
|---|---|
| Unit | MGMT11169 Business Analytics, CQUniversity Australia |
| Assessment | Assessment 2: Business Report, "Navigating the Impact of Technological Adaptation and Business Performance (Sales Growth)" |
| Weighting | 60% of the unit grade |
| Deliverables | Part A: Excel spreadsheet (.xlsx) · Part B: Word business report (.docx) |
| Word count | 1,600 words ±5% (summary, contents, references and appendices are not counted) |
| Formatting | Times New Roman 12 pt, 1.5 line spacing, business report format |
| Referencing | APA 7th edition. At least 8 peer-reviewed journal articles from the last 10 years |
| AI rule | AIAS Level 1, so no generative AI at any stage. A GenAI declaration is required |
| Client scenario | TechWave Digital Inc. (leadership: Michael John), a consulting firm that helps SMEs adopt technology |
What is the central question?
Every section of your report should come back to one question: "Does a higher level of technological adaptation correlate with better business performance (sales growth) for Australian SMEs?" You answer it with statistics, not opinion. You test a null hypothesis (no significant correlation) against a one-directional alternative hypothesis (a significant positive correlation).
Understanding the dataset (and the normalisation formula)
Five senior executives in each SME rated technology use and performance on a 7-point Likert scale. Their scores were averaged and then converted to a percentage using min–max normalisation:
Normalised % = (Average score − 1) ÷ (7 − 1) × 100
Worked example: ratings 6, 7, 5, 6, 7 → average 6.2 → (6.2 − 1) ÷ 6 × 100 = 86.67%
Answer hint: In your data preparation section, show that you understand why this was done. It turns ordinal survey answers into a continuous 0–100% scale and reflects the consensus of the leadership team rather than one person's bias. Then add a limitation: Likert data is ordinal, so treating it as continuous is a simplification. Markers reward this kind of critical point.
Part A: Step-by-step Excel hints
Step 1: Data preparation (5%)
- Filter the dataset to your chosen industry only (Retail, Education, IT, Health Care, Hospitality, Financial or Manufacturing). Keep the full dataset on a separate sheet as evidence.
- Find missing values with
=COUNTBLANK(B2:B200)and check that every percentage falls between 0 and 100 with=COUNTIFS(B2:B200,"<0")+COUNTIFS(B2:B200,">100"). - Look for duplicate SME-IDs (Data › Remove Duplicates, or
=COUNTIF(A:A,A2)>1). - Decide whether to remove or impute each problem row (for example, mean imputation) and write a note on the sheet explaining why. This decision log is what earns the 5% for data preparation.
Step 2: Descriptive analysis
- Average technological adaptation:
=AVERAGE(TA_range) - Average sales growth for your industry:
=AVERAGEIF(Industry_range,"Retail",SG_range) - Go beyond the brief with MEDIAN, STDEV.S, MIN, MAX and COUNT. You can also run Data › Data Analysis › Descriptive Statistics to produce a full summary table.
Step 3: Pearson correlation
=CORREL(TA_range,SG_range)(or=PEARSON()) gives you r.- The brief also asks you to run TA vs Years in Operation or SG vs Years in Operation. Show both pairs in a small correlation matrix (Data Analysis › Correlation).
- How to read r (common guide): 0.1–0.3 is weak, 0.3–0.5 is moderate and above 0.5 is strong. The sign shows the direction.
Step 4: Statistical inference (p-value)
Excel has no single function that returns the p-value for a correlation, so calculate it in two cells:
- t-statistic:
=r*SQRT((n-2)/(1-r^2)) - One-tailed p-value (the alternative hypothesis is positive):
=T.DIST.RT(t, n-2) - Two-tailed, if your tutor prefers it:
=T.DIST.2T(ABS(t), n-2)
Decision rule: if p < 0.05, reject H0. Write the decision in a sentence next to the result, for example: "p = 0.001 < 0.05, therefore we reject the null hypothesis."
Step 5: Simple linear regression
- Run Data › Data Analysis › Regression with Y = Sales Growth and X = Technological Adaptation. Tick "Labels" and "Line Fit Plots". (If the ToolPak is missing, enable it under File › Options › Add-ins.)
- Check the output with formulas:
=SLOPE(),=INTERCEPT()and=RSQ(). - Write the model like this: Predicted SG = a + b × TA. Interpretation template: "For every 1-percentage-point increase in technological adaptation, sales growth is expected to change by b percentage points."
- Explain R²: "R² = 0.42 means 42% of the variation in sales growth is explained by technological adaptation. The remaining 58% comes from other factors such as market conditions, firm size and management capability."
- Add a scatter chart with a trendline, and tick "Display equation" and "Display R-squared".
Common mistake: pasting values instead of formulas. The brief says the spreadsheet must show "clear Excel formulas", so markers click on cells to check. Keep the ToolPak output, but reproduce the key numbers with live formulas beside it.
Part B: How to structure the 1,600-word report
| Section | Suggested words | Answer hint |
|---|---|---|
| Executive summary | Not counted | Address Michael John at TechWave. Give the headline r, p-value, R² and your top 3 recommendations in 150 words. |
| Introduction | ~150 | Explain why technology adoption matters for Australian SMEs, the purpose of the analysis, your chosen industry and your methods (descriptive statistics, correlation, inference, regression). |
| Literature review | ~450 | Synthesise at least 8 recent journal articles by theme, not one article per paragraph. A summary table (author, industry, method, finding) scores well. |
| Analysis outcomes and insights | ~500 | Regression equation, R² interpretation, hypothesis decision, charts and what they mean for TechWave's clients. |
| Recommendations and limitations | ~350 | 3–4 specific actions for SMEs in your industry, plus limitations such as sample size, cross-sectional data, correlation vs causation and Likert-to-percentage conversion. |
| Conclusion | ~150 | Answer the central question directly: yes or no, and how strongly. |
Literature review hints (15% of marks)
Group your sources under themes like these:
- Digital transformation and SME performance: studies linking adoption of e-commerce, cloud or ERP systems to revenue growth.
- Adoption frameworks: the Technology–Organisation–Environment (TOE) framework, the Resource-Based View and dynamic capabilities explain why some SMEs adapt faster than others.
- Barriers: cost, digital skills gaps and cybersecurity concerns among Australian SMEs.
- Industry-specific evidence for the sector you chose, such as retail omnichannel or hospitality booking platforms.
Search Google Scholar or the CQU library with strings such as "digital transformation" AND SME AND "firm performance", and filter to 2016 onwards. Older foundational theory is fine for context, but it does not count towards the "last decade" requirement.
Writing the insights section
A strong paragraph moves from result → meaning → business action. For example: "The moderate positive correlation (r = 0.55, p < 0.05) suggests Retail SMEs with higher digital integration tend to grow faster. For TechWave, this supports bundling POS–inventory integration with staff training for low-adoption clients." Use your own numbers. The figures here are illustrations only.
Marking rubric: where the marks actually are
| Criterion | Weight | How to score "Excellent" |
|---|---|---|
| Excel: data preparation | 5% | A documented cleaning log and a before/after row count |
| Excel: model analysis | 30% | Correct correlation, t-test, p-value and regression, all with live formulas and labelled charts |
| Literature review | 15% | 8+ recent peer-reviewed articles, synthesised by theme |
| Findings, insights, limitations | 20% | Numbers interpreted in business language, with honest limitations |
| Evaluation arguments | 10% | Concise, evidence-led paragraphs |
| Flow (summary, intro, conclusion) | 10% | The conclusion explicitly answers the central question |
| APA 7 referencing | 5% | Matching in-text citations and reference list, with DOIs |
| Grammar and clarity | 5% | Proofread, consistent tense, no filler |
Checklist before you submit
- ☐ Only one industry analysed, and named in the title
- ☐ Excel shows formulas, not pasted numbers
- ☐ Hypotheses stated, p-value calculated and a clear reject / fail-to-reject decision
- ☐ Regression equation, coefficients and R² explained in plain English
- ☐ At least 8 journal articles from the last 10 years in APA 7
- ☐ Times New Roman 12, 1.5 spacing, 1,520–1,680 words
- ☐ GenAI declaration included ("I declare that I have not used GenAI in my assessment")
Stuck on your MGMT11169 Excel model or regression output?
Our business analytics tutors can take you through data cleaning, CORREL, T.DIST and ToolPak regression one-to-one, and explain what your own results mean. We can also review your draft report for structure, APA 7 and flow. Our support is human-led, which suits CQU's AIAS Level 1 rule.
WhatsApp "MGMT11169" for a free Excel formula checklist Get a free quote in 15 minutes
MGMT11169 Assessment 2 answer hints and TechWave Digital solution steps
Students often search for MGMT11169 Assessment 2 answers or a TechWave Digital solution. Every student gets a dataset and chooses one industry, so your numbers will differ from anyone else's, and the unit is AIAS Level 1 (no AI). What you need is the correct method: the Excel formulas for CORREL, the t-statistic, T.DIST.RT and regression, plus the result → meaning → business action writing pattern above.
Answer-hint recap: clean and document your data, calculate AVERAGE and AVERAGEIF, run the Pearson correlation and its one-tailed p-value, fit SG = a + b × TA with R², then explain it all in plain business language for TechWave's leadership.
Where can I find MGMT11169 Assessment 2 answers?
There is no universal answer because each student analyses their own dataset and chosen industry. Use the formula steps and interpretation templates on this page. Our tutors can explain your own Excel output one-to-one.
What is the TechWave Digital case in MGMT11169?
TechWave Digital Inc. is a fictional consulting firm that helps Australian SMEs adopt technology. You test whether higher technological adaptation correlates with higher sales growth for SMEs in one industry.
Which Excel functions are needed for MGMT11169 Assessment 2?
COUNTBLANK and COUNTIFS for data checks, AVERAGE and AVERAGEIF for descriptive statistics, CORREL for correlation, T.DIST.RT for the p-value, and SLOPE, INTERCEPT, RSQ or the Analysis ToolPak for regression.
Frequently asked questions
How do I calculate the p-value for a correlation in Excel?
Calculate t = r × √((n − 2) ÷ (1 − r²)), then use =T.DIST.RT(t, n-2) for the one-tailed test in MGMT11169, because the alternative hypothesis predicts a positive correlation. If p < 0.05, reject the null hypothesis.
Can I analyse more than one industry in MGMT11169 Assessment 2?
No. The brief repeatedly says to choose one industry only, such as Retail, IT or Hospitality. You can mention the overall dataset for context, but your model and report must focus on a single sector.
What does R-squared mean in this assessment?
R² is the share of the variation in sales growth that technological adaptation explains. An R² of 0.30 means 30% is explained and 70% is driven by other factors, which you should discuss as a limitation.
Is AI allowed in MGMT11169 Assessment 2?
No. The assessment is set at AIAS Level 1, so generative AI must not be used at any stage, and you must include a GenAI declaration. Human tutoring, library workshops and your lecturer's consultation hours are all acceptable forms of support.
How many references do I need?
At least 8 high-quality, peer-reviewed journal articles published in the last ten years, formatted in APA 7th edition. Textbooks and websites can be used in addition to these.
Related help
- University assignment help in Australia
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- One-to-one online tutoring
Academic integrity note: this guide explains the assessment and gives study hints. Do not copy it into your submission. Use your own dataset, results and analysis, and follow CQUniversity's academic integrity and AI policies.