Misinterpretation is a common problem when using statistical information. It may be caused by a number of factors,

Question 1

• Misinterpretation is a common problem when using statistical information. It may be caused by a number of factors, such as misunderstanding the data, using incomparable definitions, or even deliberately misinterpreting the information. Please describe two (2) recent examples in real life where statistics are Explain in detail how they are misinterpreted and what should be the correct interpretation.

• Employees in a big company are rated on their performance and their potential for advancement. The data for the 250 sampled employees are summarised in the following table.

    Potential for advancement     Fair Good Excellent Performance Below average 8 6 11 Average 22 30 23 Above average 46 36 68

• State the probability that an employee selected at random has average performance?
• State the probability that an employee selected at random has average performance and has excellent potential for advancement?
• State the probability that an employee selected at random has above average performance or good potential for advancement?
• State the probability that an employee selected at random will have an excellent potential for advancement given that he/she has average performance?