Suppose 30% of a population possess a given characteristic. If a random sample of size 1200 is drawn from the population, then the probability that less than 348 possess that characteristic is

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Answer:

The probability that less than 348 possess that characteristic is 0.2148 = 21.48%.

Step-by-step explanation:

I am going to use the binomial approximation to the normal to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

[tex]E(X) = np[/tex]

The standard deviation of the binomial distribution is:

[tex]\sqrt{V(X)} = \sqrt{np(1-p)}[/tex]

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that [tex]\mu = E(X)[/tex], [tex]\sigma = \sqrt{V(X)}[/tex].

In this question, we have that:

[tex]n = 1200, p = 0.3[/tex]

So

[tex]\mu = E(X) = np = 1200*0.3 = 360[/tex]

[tex]\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{1200*0.3*0.7} = 15.8745[/tex]

The probability that less than 348 possess that characteristic is

Using continuity correction, this is P(X < 348 - 0.5) = P(X < 347.5), which is the pvalue of Z when X = 347.5. So

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]Z = \frac{347.5 - 360}{15.8745}[/tex]

[tex]Z = -0.79[/tex]

[tex]Z = -0.79[/tex] has a pvalue of 0.2148.

The probability that less than 348 possess that characteristic is 0.2148 = 21.48%.

The population follows a normal distribution.

The probability that less than 348 possess that characteristic is 0.2248

The given parameters are:

[tex]\mathbf{n = 1200}[/tex]

[tex]\mathbf{p = 30\%}[/tex]

Start by calculating the mean:

[tex]\mathbf{\mu =np}[/tex]

[tex]\mathbf{\mu =1200 \times 30\%}[/tex]

[tex]\mathbf{\mu =360}[/tex]

Calculate the standard deviation

[tex]\mathbf{\sigma = \sqrt{np(1 - p)}}[/tex]

[tex]\mathbf{\sigma = \sqrt{360(1 - 30\%)}}[/tex]

[tex]\mathbf{\sigma = \sqrt{252}}[/tex]

[tex]\mathbf{\sigma = 15.87}[/tex]

Calculate the z-score

[tex]\mathbf{z = \frac{x - \mu}{\sigma}}[/tex]

Where:

x = 348

So, we have:

[tex]\mathbf{z = \frac{348 - 360}{15.87}}[/tex]

[tex]\mathbf{z = -\frac{12}{15.87}}[/tex]

[tex]\mathbf{z = -0.7561}[/tex]

So, the probability is represented as:

[tex]\mathbf{P(x < 348) = P(z < -0.7561)}[/tex]

From the z-table of probabilities, we have:

[tex]\mathbf{P(x < 348) = 0.2248}[/tex]

Hence, the probability that less than 348 possess that characteristic is 0.2248

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https://brainly.com/question/11234923

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