core Estimated learning time: 4 h

3.7 Describing data honestly in Excel

Your summary does not mislead the person reading it.

Before:02. Excel — Formulas & FunctionsUnlocks:05. Excel — Charts & Dashboards

Summarising data honestly means knowing when the mean lies and the median tells the truth, what a standard deviation is actually saying, and why a trendline through two correlated columns proves nothing about cause. This topic covers the describing side of statistics with Excel's functions, and it sits in the analysis module because pivots and charts constantly tempt you into summaries. The commonest confusion is false precision: eight decimal places on a rough estimate looks scientific and misleads, so rounding and significant figures get their own attention.

Work through these

  • Mean, median, mode, standard deviation and when the mean lies

    The average, the middle value and the most common value describe different things. Reporting only the first can be actively misleading when the data is skewed. Knowing when that happens is the point of this item.

  • Quartiles, percentiles and outliers

    Quartiles and percentiles describe the spread rather than the centre, and they are how unusual values get identified rather than argued about. Outliers deserve a decision, not silent removal.

  • Correlation, trendlines and the causation warning

    A correlation says two things move together and says nothing about one causing the other, and a trendline drawn through anything will look convincing. This item is the standing warning.

  • Rounding, significant figures and false precision

    Reporting a figure to more decimal places than your data supports implies a precision you do not have. Rounding honestly is part of describing data honestly.

Practice file

  • xl-05-pivot-sales.xlsx

    800 rows of fictional sales data for PivotTables, grouping, % of total and a first measure.

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