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CP2- September 2019 Paper 2- Data check

B

bernvall

Member
In the excel sheet given in the exam, the uniform distribution is tested by simply showing a scatterplot of the graph and acknowledging that they are in the range of 0 to 1.

However, I tried using a different method, as implied by other past papers, of using the chi-squared test (more notably the CHIINV function). the answer of summing up the (Actual-expected)^2/expected gives 9.2, whereas the test statistic gives 16.9 (for 9 degrees of freedom as split in 10 buckets of 0.1's, and prob of 0.05). this means the chi-squared test fails here.

Am I doing something wrong?
 
With a test statistic of 16.9 it means that the sum of (Actual-Expected)^2/Expected must exceed this in order to provide a statistically significant reason for rejecting the null hypothesis (ie that the random numbers are uniformly distributed).
Since 9.2 < 16.9 we can conclude that the null hypothesis should be accepted. In that sense the data passes the chi-square test.
 
Ah yes sorry for that, silly mistake. Thanks :)

Sticking to the same paper, I also realized a common mistake that could happen in the exam. This is with regards to GOALSEEK for the target profit to hit 100% of the time (Scenario 4). the solution is $2.36 per parcel. Now technically, ANY number below 2.36 will ALSO hit a 100% target profit (and will be given by the GOALSEEK) but this is not the MAXIMUM amount per driver as requested in the question. Therefore, how can we manage to perform the GOALSEEK to give us 2.36 as an answer, please?
 
There's nothing silly about it! This happens a lot :)

Goalseek is a powerful iterative solver, but it is simple. The solution it lands on (if at all) is sensitive to the starting condition. Where there are multiple solutions (such as finding the roots of a quadratic) we need to be mindful of that. This question doesn't really lend itself to the use of goalseek because of the point you've raised. Trial-and-improvement would be perfect here.
 
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