Correlation - cause and effect, Applied Statistics

Assignment Help:

Cause and Effect

Even a highly significant correlation does not necessarily mean that a cause and effect relationship exists between the two variables. Thus, correlation does not necessarily imply causation or functional relationship though the existence of causation always implies correlation or association between variables. It might sometimes happen that a fair degree of correlation is observed between the two variables but this is only due to chance as the theory might indicate non-existence of cause and effect relationship. Such a correlation is known as spurious correlation. While interpreting the correlation coefficient, it is necessary to see whether there is any cause and effect relationship between the variables under study. If there is no such relationship, the correlation observed is meaningless.

Figure 1

733_cause and effect.png

Ferrochrome is a material used in the manufacture of stainless steel. Suppose, in recent times there has been such a large increase in the supply of ferrochrome worldwide that its international price has dropped.

The simplified figure above reveals that as supply increased from S1 to S2, prices fell from P1 to P2. Hence, there is an inverse correlation between supply and price, that is, when supply increases, prices fall. Further we can say that the increase in supply was the CAUSE that led to the EFFECT of falling prices. So far so good.

Now consider the figure given below:

Figure 2

1313_cause and effect1.png

Here we have plotted supply against price. We may now be tempted to say that the fall in price from P1 to P2 was the CAUSE that led to the EFFECT of increase in supply from S1 to S2. This does not make economic sense because a fall in price does not lead to an increase in supply. The problem is that we have reversed the cause (increase in supply) and the effect (fall in price).

Continuing the example, suppose supply increases from S1 to S2, but demand increases by a disproportionately larger quantity. As demand increases more than supply the price will increase. In such a case if we plot price against supply the simplified graph would be as follows:

Figure 3

1900_cause and effect2.png

Hence, when supply increases from S1 to S2, price increases from P1 to P2. This is again poor economics because an increase in supply should reduce prices and not increase prices. The problem here is that the main CAUSE for the increase in price is the disproportionate increase in demand which is not shown in the graph. Hence, by ignoring the vital factor of demand and by comparing supply with price we come up with a spurious positive correlation between supply and price which defies good economics.


Related Discussions:- Correlation - cause and effect

Properties of standard deviation, PROPERTIES   1. The value of stand...

PROPERTIES   1. The value of standard deviation remains the same if, in a series each of the observation is increased or decreased by a constant quantity. In statistical lan

Postneonatal mortality rate, Mid year population 440000 Late fatal death...

Mid year population 440000 Late fatal death          29 No. of live birth           5200 No. of infant death      423 No. of maternal death 89 No. of infant deaths i

Explain ridge regression, Using log(x1), log(x2) and log(x3) as the predict...

Using log(x1), log(x2) and log(x3) as the predictors, do pair wise scatterplots of all pairs of variables (including the response) and comment (use the pairs function). Do you thin

Expected average time, Question: A car was machine washes each car in 5 min...

Question: A car was machine washes each car in 5 minutes exactly. It has been estimated that customers will arrive according to a Poisson distribution at an average of 8 per hour.

Penman-monteith method, (a) Average rainfall during the month of January...

(a) Average rainfall during the month of January is found to be 58 mm. A Class A pan evaporation recorded an average of 8.12 mm/day near an irrigation reservoir. The average

Riemannian integral approximations, Investigate the use of fixed and perce...

Investigate the use of fixed and percentile meshes when applying chi squared goodness-of- t hypothesis tests. Apply the oversmoothing procedure to the LRL data. Compare the res

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd