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When presenting data-driven insights to a non-technical audience, the goal is to make the data easy to understand and relevant to their decision-making process. The best approach is to use clear visualizations (such as charts, graphs, or dashboards) along with simple language to explain the key findings. Visualizations can help simplify complex data, making it easier for the audience to grasp the message. Focusing on key takeaways ensures that the audience understands the most important insights without being overwhelmed by technical details. Why Other Options Are Wrong : A) Incorrect : Using complex statistical terminology may confuse non-technical audiences and hinder their understanding of the insights. B) Incorrect : While detailed analysis is important, a non-technical audience may not have the background to understand intricate details. Simple, digestible summaries work better. D) Incorrect : While data sources are important for transparency, a non-technical audience typically doesn't need to know all the sources in detail unless they ask. E) Incorrect : Presenting results without context or explanation will leave the audience uncertain about the meaning and significance of the findings. Context is essential for understanding.
In classical linear regression model if we add in 90 in X and Y observation and re-estimate the regression model then slope coefficient
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