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3 years ago

35/7•5+2 Help with math Simplify

Mathematics

2 answers:

crimeas [40]3 years ago

6 0

Answer:

27, correct me if im wrong

Step-by-step explanation:

stellarik [79]3 years ago

4 0

Answer:

35/7 = 5

5*5 = 25

25+2 = 27

Step-by-step explanation:

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Graph the linear equation. 3x−4y=12 Please show it on a graph

baherus [9]

Answer: The graph is attached.

Step-by-step explanation:

By definition, the line intersects the y-axis when $x=0$ .

Then, in order to find the y-intercept, substitute $x=0$ into the equation and solve for "y":

$3(0)-4y=12\\\\y=\frac{12}{-4}\\\\y=-3$

By definition, the line intersects the x-axis when $y=0$ .

Then, in order to find the x-intercept, you can substitute $y=0$ into the equation and then you must solve for "x". Then you get:

$3x-4(0)=12\\\\x=\frac{12}{3}\\\\x=4$

Knowing that the line passes through the points $(0,-3)$ and $(4,0)$ , you can graph it (The graph is attached).

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4 years ago

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3 years ago

Suppose that daily calorie consumption for american men follows a normal distribution with a mean of 2760 calories and a standar

lianna [129]

Answer:

38.11% probability that the mean of her sample will be between 2700 and 2800 calories

Step-by-step explanation:

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

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 $s = \frac{\sigma}{\sqrt{n}}$ .