The probability that the sample proportion will be less than 0.04 is <u>0.8995</u> or <u>89.95%</u>.
The true proportion (p) is given to be 0.03.
Therefore, Mean (μ) = p = 0.03.
The standard error of sampling distribution can be calculated using the formula σ = √[{p(1 - p)}/n], where n, is the sample size, that is, n = 476.
Therefore, σ = √[{0.03(1 - 0. 03)}/476] = 0.00782.
Since, np = 14.28 and n(1 - p) = 461.72 are both greater than 5, we assume the sample is normally distributed.
Since, we are asked to find the probability that the sample proportion is <u>less than</u> 0.04, we using our calculator, enter as following:
Normalcdf(-100000000,0.04,0.03,0.00782), which gives us the value 0.8995 or 89.95%.
Thus, the probability that the sample proportion will be less than 0.04 is <u>0.8995</u> or 89.95%.
Learn more about probability of sampling distributions at
brainly.com/question/15520013
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