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4 years ago

What is the difference between an equation and an expression

2 answers:

7 0

Answer: An expression is a number, a variable, or a combination of numbers and variables and operation symbols. An equation is made up of two expressions connected by an equal sign.

Step-by-step explanation:

julsineya [31]4 years ago

6 0

Equation 1x2 expression (12 x45) 34•=

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How to graph y=2x-4 x+3y=9

NikAS [45]

Answer:

Step-by-step explanation:

The point form: (3,2)

You solve for X

You solve for y

On the Y-axis where the 2 is you go 3 to the right and put your point right there above the 3.
There you have your answer on the graph.

4 0

3 years ago

How many solutions does this equation have?

drek231 [11]

The answer is infinitely many solutions because 0 = 0.

If you don't seem to see where I got 0 = 0, look at the equation,

4b – 4b = 0

first lets do the math on the left side.

4b - 4b is equal to 0.

so lets put 0 on the left side, now lets look at the equation all together,

0 = 0,

and this means that it has infinitely many solutions.

The reason why it is not no solution because no solution means when there are no answers to the equation. For example, the solution is not true, such as the equation 24 ≠ 29. This is a no solution equation. One solution can be 4x = 20, as x = 5, concluding it being one solutions.

5 0

3 years ago

In college basketball, a shot made from beyond a designated arc radiating about 20 ft from the basket is worth three points ins

denis-greek [22]

Answer:

a) By the Central Limit Theorem, the distribution would be approximately normal, with mean $\mu = 0.45$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.45*0.55}{100}} = 0.0497$

b) 4.02 standard deviations below the mean.

c) Making 25 or less shots has a pvalue of -4.02. Z-scores lower than -2 are considered surprising, so yes, it would be surprising for him to make only 25 of these shots.

Step-by-step explanation:

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

Normal probability distribution

Problems of normally distributed samples are 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.

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 proportions, we have that the mean is $\mu = p$ and the standard deviation is $s = \sqrt{\frac{p(1-p)}{n}}$

In this problem, we have that:

$p = 0.45, n = 100$

a)By the Central Limit Theorem, the distribution would be approximately normal, with mean $\mu = 0.45$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.45*0.55}{100}} = 0.0497$

b)This is Z when X = 0.25.

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

By the Central Limit Theorem

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