How to Lie with Statistics - Deepstash

# How to Lie with Statistics

Darrell Huff

12 ideas

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## Book Overview

• The author does a good job of covering a variety of topics in a small book.
• However, the book lacks proper explanation of statistic concepts thus if you didn't take a stats class in University you will struggle to understand the concepts.
• There are a lot of practical examples of how these concepts have been used.

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The secret language of statistics is employed to sensationalise, inflate, confuse and oversimplify.

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## Method 1: Using Samples with bias

• Researchers can intentionally choose a group of people (or things) that have similar traits and thus 'prove' their point.
• This is deceiving because a report based on sampling must use a representative sample - every name or thing in the whole group must have an equal chance.
• Another famous method is choosing a very small sample.
• Depending on the population size, samples sizes must be at least 30% of the population.

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## Method 2: Reporting The Wrong Average

There are 3 common averages: mean, median and mode. In some cases, the result of all 3 is the same number but in most cases the numbers are very different!

The Median (middle number) tells you more about the situation. On the left of this number is 50% of the sample on the right is the other 50% of the sample. Thus gives a good overview of what's happening as a whole.

But marketers normally report using the mean (the sum of all numbers divided by the number of units in the sample).

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Averages, Relationships, Trends and Graphs are not always what they seem. There may be more in them than meets the eye, and there may be a good deal less

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## Method 3: Missing Figures

1. Not including the number of trials the experiment / research took - given a small enough number of cases, random 'by chance' occurrences can happen.
2. Leaving out the Degree of Significance - the demanded level is 1% which means there are 99 chances out of 100 that have an apparent difference.
3. The Range - this figure tells you the deviation of the sample from the average that is given.

Place little faith in an average or a graph or a trend when those important figures are missing

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## More Figures to Look For 👀

1. The Probable Error and The Standard Error - these tell you how accurately the sample presents the whole field (or population)
2. The Test of Significance (often calculated with the degree of significance)

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## Method 4: Exaggerating

To make things seem bigger than what they are, marketers can use these methods / tools

• The Gee Whiz Graph - basically adding more numbers on the graph to create an upward or downward trend that otherwise looked like a straight line.
• Bar Graphs - not using the same size for the bars or objects used

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Only when there is a substantial number of trials involved is the law of averages a useful description or prediction

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## Method 5: Make Assumptions

" If you can't prove what you want to prove, demonstrate something else and pretend that they are the same thing "

The general method is to pick two things that sound the same, but are not.

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## How To Talk To a Statistic

1. Look for conscious bias - ask "Who says so?"
2. Ask yourself "How does HE know that?" What methods were used (if any) to acquire that information?
3. Does it make sense - use your own intellect to see through the cracks!

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# CURATED BY

welcome 🤗, sharing my obsession with non-fiction books about marketing, business, productivity, relationships and spirituality🤍

# CURATOR'S NOTE

Let's explore how marketers lie using statistics (👀 and how you can too)

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