Sahil surveys 50 randomly selected people at the city park to find their favorite activities. How might the sample be biased?

1 answer:

5 0

Well, the answer quite stands out
First, Biased means how might it be "inaccurate", or in what ways could it be leaning more to one side than another, etc
Like if you ask a bunch of old people at a nursing home: "What's your favorite video game?" Well, chances are most of them don't want anything to do with video games, so that would be biased.

Well, same thing here. If you go to a park, chances are your not going to find a whole lot of people who like indoor activities better than outdoor.
So, by going to a PARK for your survey, your biased, because this particular survey is about favorite activities, and if your at a park, practically nobody will say something about an indoor activity being their favorite.

Meaning, your answer is B

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Hurryyy I’m giving brainliest <br><br> Solve for p.<br> 5p = 35

djverab [1.8K]

Step-by-step explanation:

$5p = 35$

Divide both sides of the equation by 5

$\frac{5p}{5} = \frac{35}{5}$

Simplify

$5p \div 5 = p \\ 35 \div 5 = 7 \\ p = 7$

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3 years ago

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Suppose that 20% of the adult women in the United States dye or highlight their hair. We would like to know the probability that

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Answer:

71.08% probability that pˆ takes a value between 0.17 and 0.23.

Step-by-step explanation:

We use the binomial approxiation to the normal to solve this question.

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The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

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

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

$Z = \frac{X - \mu}{\sigma}$

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 $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .