“There are three kinds of lies: lies, damned lies, and statistics”
So often we are inundated with numbers and we take them for granted. We shouldn’t take these at face value without at least questioning them first. They are often used by the media for dramatic effect. But if we believe everything we read, we can end up making poor decisions, based on poor data.
The underlying fact is that many statistics are less dramatic when explained. Therefore, whoever is spinning the story will often leave out key details to suit their story.
A few examples of poorly used statistics
Asking prices are much different to sales prices
Often there are articles run about an increase in asking prices in the housing market. These articles are often promoted by real estate companies or people with involvement in the real estate industry. Reading a headline like this is supposed to make us think that the housing market is heating up and it is a good time to sell for sellers. And buyers better get in quick before it heats up even more! In reality though, asking prices of houses are no indication of sales prices. A car salesman can ASK for $100,000 for a Honda Civic, but doesn’t mean they will get it. The sales prices are what matter. Asking prices are irrelevant and a useless statistic.
averages can be misleading
The use of the word “average” is often used in the media. The average cost of a wedding or the average cost of houses. The problem is, averages do not tell the full story. Average in statistical terms is completely different to the everyday meaning of “average”. In statistics, average is the average number or cost. In general, average is normal, typical, or standard. The normal cost of housing and weddings is generally much lower than the average cost. A better reflection of “normal” is using the median cost. This is the middle number in a range. The average cost can be heavily skewed by extremely high or low numbers. Media often use the average price because it is higher than the median price. This creates sensationalism and clickbait. It also encourages us to spend more. It sells. Who doesn’t want to be normal? The problem is, average in the statistical sense is not normal, the median is.
some surveys may not be very diverse or comprehensive
Survey results need to be carefully considered. If a survey comes out and says 35% of New Zealander’s aren’t saving for their retirement, we probably shouldn’t accept this fact until we find out more. How was the survey conducted? How many participants in the survey were there? If the survey size was only 1,000 people, how is this supposed to be a representation of over 1 million people potentially saving for retirement? Or what if this was asked on a site such as interest.co.nz.This would be a very narrow representation of New Zealand, as I imagine the majority of the readers of this site are white males of a certain age and income level. This survey would make a result on the entire population of New Zealand, despite not surveying the young, the female, the low income, or the different races.
renters are not necessarily worse off than home owners
I often read articles about renters being less well off than home owners. Earning less income, and saving less. Again, this can be very misleading. One would naturally draw the conclusion that renting costs more than owning a home. However, owning a home is often more expensive than renting for periods of less than 7 years. Someone is not less well off because of their decision to rent. They are often already less well off BEFORE their decision to rent. Renting is not the contributing factor as we may be led to believe. This is another spin on statistics to make us want to buy more houses. This is in the best interests of banks, real estate agents, trades, employers and the government. Banks receive our mortgage interest. Real estate agents receive commissions. The trades receive our cash for building, maintenance, and upgrades. Employers and government benefit because when buying a house, we lock ourselves to one permanent location, less likely to move. Councils receive our rates/land tax. Almost everyone has a finger in the housing industry and they all benefit from us owning homes. So be weary of who is giving the information.
unemployment is higher than reported
Government uses very misleading unemployment statistics. Currently reported as sitting around 5%. This sounds pretty impressive right? But there are well over 100,000 available jobseekers who have not applied for any work in at least one month, but would like a paid job. They are not included in the unemployment numbers. Just because they have not applied for a job in the last month. So, you can be unemployed and want a job, but not included in the unemployed statistics. If unemployment was really just 5%, then our wage and salary increases should be much greater than we are getting currently (less than 2% average). We would be in a labour market with very few people competing for work so we could demand more. But we are not. Because unemployment is not really that low. The actual underutilisation rate is closer to 12%. 12% of people who are not fully being utilised, such as part time or casual workers seeking full time work. 12% is well over double the reported 5% unemployment rate. Unemployment figures are calculated by economists and they have an agenda in making the rate lower than it actually is. It makes us all feel more confident about the economy. When we are more confident we spend more.
investment fund returns are deliberately misleading
When looking at managed mutual funds, companies often publish the returns of their funds. The problem with these statistics, is they often sell poor performing stocks. This removes the stock from the portfolio, so they don’t include that dumped stock as part of their return performance. Others report the returns before fees. It makes the returns inflated and highly inaccurate.
different surveys can conclude opposing results
You can find studies that tell you chocolate and alcohol is both bad and good for you depending on who the study was conducted by.
Final thoughts
Statistics are useful in providing evidence to conclusions. The problem is that they can easily be manipulated to match evidence to conclusions. People often have a conclusion, and then find the statistics to match. This can result in information that is very misleading, and can cost us time and money if we act on the results of the numbers.
We shouldn’t take statistics at face value. Instead, we should ask:
Who did the study?
What is being measured?
Who was asked?
How big was the sample size?
How were they asked?
By asking these questions, we can begin to understand the reliability of the numbers thrown at us. We shouldn’t view statistics as a given. The statistics are often generated to support someone’s ideas. This involves subjectivity and bias which may sway the numbers. This includes the framing of their questions, which can be made in such a way as to influence the respondent to answer in a way that is preferable to the interviewer’s point of view. It is our job to examine the statistics to come to our own conclusion.
Statistics are often excellent forms of evidence. I am just expressing the need for you not to take everything as a given, as some statistics are heavily biased by the person or group providing the statistics. Otherwise, how can two identical surveys, conducted by two different people, provide different results?
The information contained on this site is the opinion of the individual author(s) based on their personal opinions, observation, research, and years of experience. The information offered by this website is general education only and is not meant to be taken as individualised financial advice, legal advice, tax advice, or any other kind of advice. You can read more of my disclaimer here
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