How to Calculate Likert Percentages and Means for 5CO02 Task 2

You have a spreadsheet of 46 pulse-survey responses, nine Likert statements and a brief that wants percentages, means and two charts, all inside a 1,000-word task. The arithmetic is easy. Presenting it so a marker can see your reasoning is where marks go missing in 5CO02 Task 2.

Quick answer: to calculate Likert percentages for 5CO02, divide each option’s count by the total respondents (46) and multiply by 100, rounding to whole numbers. For the mean, multiply each score (1 to 5) by its count, add the results, divide by 46 and round to a whole number, as the brief requires (keep the 2 dp value in your working). Then chart the means and the response percentages separately.

What AC2.1, AC2.2 and AC2.3 actually ask for

Task 2 of the 2026 5CO02 Evidence-based practice assessment (CIPD Level 5 Associate Diploma in People Management) hangs on the Camellia scenario. You are a consultant at a people-data firm and the client wants clearer insight on learning and development. The brief gives you pulse-survey data, and the three criteria run in a fixed order.

Check the marking scheme in your brief, because a weak Task 2 can sink an otherwise good report. Charts and tables are excluded from the word count, but the commentary is not, and going more than 10% over the limit risks a refer.

How to calculate Likert percentages and means for 5CO02

Open your own spreadsheet and work one statement at a time. Do not trust a pivot table you have not checked by hand at least once.

Step by step

1. Count how many respondents chose each of the five options for the statement.
2. Check the five counts add to 46. If they do not, find the blank or duplicate before you go further.
3. Divide each count by 46 and multiply by 100.
4. Round each percentage to a whole number.
5. Multiply each option’s score by its count, add the five products and divide by 46 for the mean, then round the mean to a whole number.
6. Write one line stating your rounding rule and what the scale values are (1 = strongly disagree, 5 = strongly agree).

A tiny worked example (illustrative, not your data)

Suppose one invented statement gets counts of 5, 9, 10, 15 and 7. The table shows how the rounding behaves.

The whole-number percentages add to 101, not 100. Do not quietly nudge one figure to force 100. Add a short note that totals may differ from 100% because of rounding. Markers read that as competence. The mean here is (5 + 18 + 30 + 60 + 35) ÷ 46 = 148 ÷ 46 = 3.22 as a working value, reported as 3 when rounded to a whole number. Whole-number means hide small differences, so rank statements using the 2 dp working values and say so in a note.

Do not forget the limits of a Likert mean

Likert responses are ordinal. The gap between “agree” and “strongly agree” is not guaranteed to equal the gap between “neutral” and “agree”, so a mean is a handy summary rather than an exact measurement (Jamieson, 2004). The scale itself comes from Likert (1932). One sentence on this, tied to a small sample of 46, earns the critical-thinking credit that evidence-based practice is about.

Also look at the spread. Two statements can share a mean of 3.0 where one has everyone neutral and the other has half strongly agreeing and half strongly disagreeing. That is exactly why the brief asks for response percentages as well as means.

Choosing two chart types that earn marks

Pick charts for what each one shows, not for looks. A good pairing for this task is a horizontal bar chart of means and a 100% stacked bar of response percentages.

Label every axis, add a title that states the finding, and order the bars rather than leaving them in survey order. If you can, mark the neutral midpoint of 3 on the means chart.

How to interpret a chart in two or three sentences

A strong paragraph names the highest and lowest statements, quotes the numbers, says what it could mean for Camellia and flags one limitation. For example: the lowest-scoring statement is about feedback; nearly half of respondents disagree; this may indicate that learners do not see their views change anything; with 46 responses, the pattern should be tested again before major spending.

Turning numbers into recommendations (AC2.3)

The brief wants at least three recommendations, each justified. A reliable layout is one short paragraph per recommendation, covering what to do, which statistic supports it, the benefit, the risk and an approximate cost. A table works well here and does not use up your word allowance.

Anchor each point in literature as well as data. The CIPD (no date) evidence-based practice factsheet and Barends, Rousseau and Briner (2014) show the four sources of evidence, while Rousseau (2020) is useful on deciding when evidence is incomplete. Kirkpatrick and Kirkpatrick (2006) help you argue for evaluating learning at the level of behaviour, not just satisfaction. A bare list of CIPD documents will not reach the top band; the brief expects a variety of academic references.

On finance, be honest about assumptions. If the scenario gives no budget, label your estimates as assumptions and show how you reached them. Never invent a precise saving and present it as fact.

Mark-maximising checklist for Task 2

• Counts for each statement add to 46 before you calculate anything.
• Percentages and means are whole numbers, as the brief requires, with a stated rounding rule and the 2 dp working value kept.
• Two different chart types, each with a title, labelled axes and a short interpretation.
• At least three recommendations, each tied to a named statistic.
• Benefits, risks and financial implications covered for every recommendation.
• Academic references beyond the CIPD factsheets, in the centre’s Harvard style.
• Word count checked, with tables and charts excluded and no more than 10% over.
• A sentence on survey limitations: small sample, one point in time, ordinal data.

Common mistakes we see in this task

Most students waste their first 150 words restating the scenario. Markers know it. Start with the method.

Other errors repeat across submissions. People chart percentages for only two statements and call it a day. They interpret by describing (“the bar is tall”) instead of explaining. They recommend “more training” with no link to the data. Or they use AI to draft the commentary, which the brief prohibits and which tends to produce generic prose that does not match their own spreadsheet.

What students ask before they get stuck

The same worries come up. Can I use Excel formulas? Yes, and screenshot or describe them as your method. Do I show every calculation? Show one worked example and a full results table. What if my percentages do not total 100? Explain the rounding. Can I add a third chart? Only if words allow; two well-interpreted charts beat four ignored ones.

If you want to see how this looks in a finished layout, read our 5CO02 Camellia Task 2 data analysis sample, which uses invented figures for reference only. You can read the unit requirements in the 5CO02 evidence-based practice learner assessment brief.

When the report side is the problem, our report writing help and CIPD assignment help pages explain how support works.

Frequently asked questions

How do I calculate the percentage for each Likert option in 5CO02?

Divide the number of people who chose an option by the total number of respondents, then multiply by 100 and round to a whole number. With 46 respondents, 12 responses equals 26%. Do this for all five options on all nine statements and check each statement’s counts add to 46.

How do I calculate the mean of a Likert statement?

Multiply each response value (1 to 5) by the number of people who chose it, add the five results and divide by the total respondents. For counts of 5, 9, 10, 15 and 7, the mean is 148 divided by 46, which is 3.22 as a working value and 3 as a whole number. State your rounding.

Which two charts should I use for 5CO02 Task 2?

A bar chart of means and a 100% stacked bar of response percentages is a sound pairing, because one ranks the statements and the other shows how opinion is split. Whatever you choose, make the two types different and interpret each one separately.

What if my percentages add up to 99% or 101%?

That is normal when you round to whole numbers. Keep the rounded figures and add a note under the table that totals may not equal 100% because of rounding. Forcing a figure to make the total neat distorts your data and weakens the accuracy your marker is checking.

How many recommendations do I need for AC2.3?

The brief asks for at least three. Each should link to a specific result, explain benefits and risks, give a financial implication and be supported by references. Three well-argued points are better than six thin ones, particularly with roughly 1,000 words for the whole of Task 2.

Can I use AI to write my Task 2 analysis?

The brief states that AI must not be used to generate content, so do not. Use our material for structure and method only, and write your own interpretation from your own spreadsheet. If you are unsure what your centre allows, check with your tutor before you submit.

Next step

Do the arithmetic by hand for one statement tonight, then compare it with your spreadsheet. If the two agree, build the charts; if not, fix the data first. Should the deadline be tight, send the brief through the submit assignment page for a quote and look at student reviews before you decide. We provide model answers and academic guidance; how you use them, and your centre’s rules, remain your responsibility.

References

Barends, E., Rousseau, D.M. and Briner, R.B. (2014) Evidence-based management: the basic principles. Amsterdam: Center for Evidence-Based Management.

CIPD (no date) Evidence-based practice for effective decision-making [factsheet]. London: Chartered Institute of Personnel and Development. Available at: https://www.cipd.org/uk/knowledge/factsheets/evidence-based-practice-factsheet (Accessed: 13 October 2026).

Jamieson, S. (2004) ‘Likert scales: how to (ab)use them’, Medical Education, 38(12), pp. 1217–1218.

Kirkpatrick, D.L. and Kirkpatrick, J.D. (2006) Evaluating training programs: the four levels. 3rd edn. San Francisco: Berrett-Koehler.

Likert, R. (1932) ‘A technique for the measurement of attitudes’, Archives of Psychology, 22(140), pp. 1–55.

Rousseau, D.M. (2020) ‘Making evidence-based organizational decisions in an uncertain world’, Organizational Dynamics, 49(1), 100756.