Explaining Spanish Data and Its Main Implications to a General Audience

In this lesson, you will explain one or two important findings from a dataset in language that a non-specialist can understand. You will define the unit and baseline, use one limited numerical example, and state the main implication without adding unsupported causation or unnecessary precision.

Start with the main message

Technical-looking statement:

— The rate went from 12.4% to 16.1%.

General-audience explanation:

— The proportion increased by 3.7 percentage points.

Then explain what the percentage represents.

Define the unit

— In this report, the rate represents the percentage of customers who use the service at least once per week.

The reader now knows what 12.4% and 16.1% refer to.

Define the baseline

— The comparison is made with the same period of the previous year.

Without the baseline, “increased” is incomplete.

Use one simple numerical example

— If we think of 1,000 customers, a rate of 12.4% is equivalent to approximately 124 people, while a rate of 16.1% is equivalent to about 161.

This is an illustrative conversion based on the stated rate, not a claim that the actual sample contained exactly 1,000 people.

Explain the main implication

— The main implication is that the service is used more frequently than one year earlier.

This stays close to the data.

Do not invent a cause

Unsupported:

— The increase is due to the new advertising campaign.

Unless the analysis provides causal evidence, say:

— The data show an increase, but they do not by themselves determine what caused it.

Avoid false precision

If the chart is rounded to whole percentages, do not invent decimals.

If the bar is labeled 37%, say:

— The value is 37%.

Do not say 37.2% unless the source provides that precision.

Explain a comparison

— Group A records 48% and group B 42%.

General explanation:

— Group A is 6 percentage points above group B.

Explain an exception

— Most groups increased, but the 45–64 group remained practically stable.

A good explanation includes the important exception when it changes the overall picture.

State a limitation in plain language

— The survey includes 320 responses and we do not know whether it exactly reflects all service users.

This communicates the sample limitation without technical jargon.

Do not overstate implications

Too strong:

— These data prove that the new policy works.

— The data are consistent with an improvement, but more information would be needed to attribute the change to the policy.

General-audience model

— The main finding is that weekly use of the service increased from 12.4% to 16.1% compared with the same period of the previous year. This is an increase of 3.7 percentage points. In simple terms, if we imagine 1,000 customers, we would go from about 124 weekly users to about 161. The increase is clear, but the data alone do not indicate why it happened. In addition, the survey is based on a sample and does not necessarily represent all customers exactly.

A practical plain-language data method

Select the most important trend or difference.
Define the unit.
State the baseline.
Use one simple numerical example if it improves understanding.
Preserve the correct percentage or percentage-point relationship.
State the implication at the level the data support.
Include the main limitation.
Avoid unsupported causation and invented precision.

From Data Explanation to Word Families

You can now explain numerical findings clearly without distorting them. The next lesson teaches you to build Spanish word families from common roots, prefixes, and suffixes.