Using the normal distribution and the central limit theorem, it is found that the probability is of 0.1368 = 13.68%.
In a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
In this problem:
The mean and the standard error are given by:
[tex]\mu = p = 0.47[/tex]
[tex]s = \sqrt{\frac{p(1 - p)}{n}} = \sqrt{\frac{0.47(0.53)}{61}} = 0.0639[/tex]
The probability that less than 40% of the sample are looking to buy an SUV is the p-value of Z when X = 0.4, hence:
[tex]Z = \frac{X - \mu}{\sigma}[/tex]
By the Central Limit Theorem
[tex]Z = \frac{X - \mu}{s}[/tex]
[tex]Z = \frac{0.4 - 0.47}{0.0639}[/tex]
Z = -1.095
Z = -1.095 has a p-value of 0.1368.
0.1368 = 13.68% probability that less than 40% of the sample are looking to buy an SUV.
To learn more about the normal distribution and the central limit theorem, you can check https://brainly.com/question/24663213