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Here's how you can convey statistical findings to non-technical stakeholders with effectiveness.

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Conveying statistical findings effectively to stakeholders who may not have a technical background is crucial in many fields, from business to public policy. The key is to translate complex data into clear insights that drive decision-making. To achieve this, you must focus on clarity, relevance, and simplicity without sacrificing the integrity of the information. Whether you're presenting to a board of directors or sharing insights with a team, the following strategies will help ensure that your statistical findings make an impact and lead to informed decisions.

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Philip Hotor

Data Science & AI | Biomedical Engineering

1 Simplify Data

When presenting statistics to non-technical stakeholders, start by simplifying the data. This doesn't mean altering the data, but rather presenting it in a way that is easily digestible. Use clear visuals like charts and graphs that can illustrate trends and comparisons at a glance. Avoid cluttering the visuals with too much information; focus on the key points that are relevant to the stakeholders' interests or decision-making needs. Remember, the goal is to make the data accessible, so stakeholders can grasp the implications without getting bogged down by complex statistical terms or calculations.

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Philip Hotor

Data Science & AI | Biomedical Engineering
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Here are two additional points that will help: 1. Instead of overwhelming stakeholders with raw data, provide concise summaries that capture the main insights. This could include metrics like averages, totals, or percentages that distill complex information into easily understandable figures. 2. Help stakeholders interpret the data by providing context and explanations for the findings. Describe any external factors or trends that may have influenced the results, and offer insights into what the data means for the organization. This could involve comparing current performance to historical data or industry benchmarks to give stakeholders a frame of reference.

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2 Tell Stories

Statistics can be dry and difficult to relate to, so wrap your data in a story. Storytelling helps contextualize the numbers, making them more meaningful. For example, if you're presenting sales data, don't just show a bar graph of increasing sales; explain what drove those numbers, like a successful marketing campaign or a change in consumer behavior. This approach helps stakeholders understand the 'why' behind the numbers, which can be just as important as the numbers themselves. Always aim to connect the data to real-world scenarios that your audience cares about.

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Philip Hotor

Data Science & AI | Biomedical Engineering
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In my opinion, stories can evoke emotions in people. Take for instance, if your statistical findings reveal a concerning trend in customer retention, tell the story of a loyal customer who was disappointed by a recent experience and chose to take their business elsewhere. By humanizing the data, you can make a stronger impact and motivate stakeholders to take action.

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3 Focus on Impact

Highlight the impact of your findings by linking them directly to the interests and goals of your audience. For instance, if your stakeholders are primarily concerned with profitability, tailor your presentation to show how the data affects the bottom line. Use clear, non-technical language to explain how statistical trends may influence future strategies or operations. By directly correlating your findings with outcomes that matter to your stakeholders, you help them see the value of the data and how it can inform their decisions.

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Philip Hotor

Data Science & AI | Biomedical Engineering
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I can also point out that providing tangible numbers helps stakeholders understand the significance of the findings and facilitates decision-making. For instance, if your analysis reveals that implementing a new marketing strategy like increasing customer feedback could lead to a 10% increase in customer acquisition, quantify this impact in terms of projected revenue growth.

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4 Use Analogies

Analogies are a powerful tool for explaining complex statistical concepts in simple terms. By comparing a statistical idea to something familiar, you can bridge the gap between confusion and understanding. For example, you might liken a data distribution to various grades in a classroom to explain the concept of variance. Choose analogies that are relevant and easy for your audience to understand, and avoid overcomplicating them. The right analogy can turn a perplexing statistical result into an 'aha' moment.

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5 Limit Jargon

Jargon can quickly alienate non-technical stakeholders, so it's important to limit its use. Instead of using terms like 'heteroscedasticity' or 'kurtosis,' describe what these concepts mean in plain language. If you must use technical terms, provide a brief and clear explanation. Remember that your goal is to communicate insights, not to showcase your statistical vocabulary. By speaking in terms that everyone can understand, you ensure that your message is received and appreciated.

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6 Encourage Questions

Finally, encourage questions throughout your presentation. This not only engages your audience but also provides you with immediate feedback on which parts of your presentation may need further clarification. Be prepared to answer questions in a way that furthers understanding without reverting to technical explanations. This dialogue can also reveal what aspects of the data are most important to your stakeholders, allowing you to tailor your presentation in real-time to better meet their needs.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Here's how you can convey statistical findings to non-technical stakeholders with effectiveness.

1

2

3

4

5

6

7

1 Simplify Data

2 Tell Stories

3 Focus on Impact

4 Use Analogies

5 Limit Jargon

6 Encourage Questions

7 Here’s what else to consider

Statistics

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Here's how you can convey statistical findings to non-technical stakeholders with effectiveness.

1

2

3

4

5

6

7

1 Simplify Data

2 Tell Stories

3 Focus on Impact

4 Use Analogies

5 Limit Jargon

6 Encourage Questions

7 Here’s what else to consider

Statistics

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