<u>Answer:</u>
The correct answer option is P (S∩LC) = 0.16.
<u>Step-by-step explanation:</u>
It is known that the probability if someone is a smoker is P(S)=0.29 and the probability that someone has lung cancer, given that they are also smoker is P(LC|S)=0.552.
So using the above information, we are to find the probability hat a random person is a smoker and has lung cancer P(S∩LC).
P (LC|S) = P (S∩LC) / P (S)
Substituting the given values to get:
0.552 = P(S∩LC) / 0.29
P (S∩LC) = 0.552 × 0.29 = 0.16
146Answer:146 and your hot
Step-by-step explanation:
Answer:
hope this helps!!:)
Step-by-step explanation:
Sampling errorThe natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter.distribution of sample means<span>The collection of sample means for all of the possible random samples of a particular size (n) that can be obtained from a population.</span>sampling distributionA distribution of statistics obtained by selecting all of the possible samples of a specific size from a population.central limit theorem<span>For any population with mean μ and standard deviation σ, the distribution of sample means for sample size n will have a mean of μ and a standard deviation of σ/√n and will approach a normal distribution as n approaches infinity.</span><span>expected value of M</span>The mean of the distribution of sample means is equal to the mean of the population of scores, μ, and is called this.<span>standard error of M</span><span>The standard deviation for the distribution of sample means. Identified by the symbol σ˯M. This standard error provides a measure of how much distance is expected on average between a sample mean (M) and the population mean (μ).</span>law of large numbers<span>States that the larger the sample size (n), the more probable it is that the sample mean is close to the population mean.</span>
