Ok here is a better pic I need help with it

Mathematics

1 answer:

BartSMP [9]3 years ago

6 0

Answer:

Step-by-step explanation:

First,You have to realize that if you multiply the amount of food by something, you multiply the amount of calories. if some piece of food is 100 calories what happens if you eat 2? you get 2 times that number of calories. Same fi you eat half of one of that kind of food. You get half the amount of calories.

Here he makes 1 1/2 (one and a half) times the amount. Now, if this is confusing you just need to realize that multiplying by this is the same as multiplying by 1+1/2. Say, again, a piece of food is 100 calories. Multiplying it by this would look like the following.

100(1+1/2)

100*1 + 100*1/2

100+50

150

So if you ever have a mixed number like this you could split it up into an addition problem and then distribute hat you're multiplying. Another solution is to multiply by the improper fraction, which here is 3/2, so 100*3/2=150 as well. Let me know if you don't get how to get the improper fraction or how to multiply fractions.

Now, super simple, just multiply the calories by that number.

310(1+1/2) = 310(3/2)

310 + 155 = 930/2

465 = 465

Kinda showed how to multiply by fractions, still if you don't get it let me know.

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Assume that 24.5% of people have sleepwalked. Assume that in a random sample of 1478 adults, 369 have sleepwalked. a. Assuming t

solniwko [45]

Answer:

a) 0.3483 = 34.83% probability that 369 or more of the 1478 adults have sleepwalked.

b) 369 < 403.4, which means that 369 is less than 2.5 standard deviations above the mean, and thus, a result of 369 is not significantly high.

c) Since the sample result is not significant, it suggests that the rate of 24.5% is a good estimate for the percentage of people that have sleepwalked.

Step-by-step explanation:

We use the normal approximation to the binomial 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:

$E(X) = np$

The standard deviation of the binomial distribution is:

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

A result is considered significantly high if it is more than 2.5 standard deviations above the mean.

Normal probability distribution

Problems of normally distributed distributions 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 $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .