I need help anyone??? please??????

Mathematics

2 answers:

olchik [2.2K]3 years ago

8 0

The principal square root of 49 is just 7 because 7 times 7 is 49.
It can not be -7 because a principle square root cannot be negative.

$\sf\ Answer: A)\ 7$

$\sf\ \sqrt{49}=\\\±7\\\\-7\ and\ 7\ are\ both\ square\ roots\ of\ 49\ because\ 7\times7=49\ and\\\\-7\times-7=49.\\\\But\ as\ I\ said\ before,\ principal\ square\ roots\ can\ not\ be\ negative\\\\numbers.\\\\That\ will\ eliminate\ any\ options\ with\ -7.\\\\So\ the\ only\ principal\ square\ root\ that\ we\ have\ is\ {\boxed{7}$

Ronch [10]3 years ago

5 0

The answer would be 7
because the square root of 49 is 7.
so 7 multiplied 7 is ..49

The answer wont be -7 because in Principal root,
negative numbers are not involved, you cant do it! :)

That being said you'd also be able to know that since no negative numbers are allowed in principle root, -7 and 7 are out as choices, and D is totally wrong since we now know what the priniciple root means :)
The answer is 7
Hope this helped !

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0.3821 = 38.21% probability that Ricardo makes a higher proportion of putts than Tammy.

Step-by-step explanation:

To solve this question, we need to understand the normal distribution, the central limit theorem, and subtraction of normal variables.

Normal probability distribution

When the distribution is normal, we use 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.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$

Subtraction of normal variables:

When we subtract normal variables, the mean of the subtraction will be the subtraction of the means, while the standard deviation will be the square root of the sum of the variances.

Ricardo makes 47% of his putts, and attempts 25 putts.

By the Central Limit Theorem, we have that:

$\mu_R = 0.47, s_R = \sqrt{\frac{0.47*0.53}{25}} = 0.0998$