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4 years ago

Please help me out with these no one is helping me.Please anyone

Mathematics

2 answers:

Olin [163]4 years ago

8 0

Answer:

Below.

Step-by-step explanation:

You find the values of y by substituting the values of x in the expression x^2 + 3x - 1.

So f(-4) = (-4)^2 + 3(-4) - 1 = 16-12-1 = 3

in the same way f(-3) = -1, f(-2) = -3, f(-1) = -3,

f(0) = -1 and f(1) = 3.

Now plot the points (-4, 3) , (-3, -1) and so on

Then you can read the values off this graph.

MariettaO [177]4 years ago

3 0

Answer:

graph attached

when y=3, x=1, x=-4

when x=-3.5, y=-23.75

just input the value of x in the equation:-3.5^2+3(-3.5)-1=-23.75

minimum value is the vertex:(-3/2,-13/2)

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3 years ago

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Step-by-step explanation:

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3 years ago

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3 years ago

Calculate a_57 for the sequence {a_n}={-6,-9/2,-3,-3/2,0}

Archy [21]

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Step-by-step explanation:

The sequence is an arithmetic sequence. The formula for determining the nth term of an arithmetic sequence is expressed as

Tn = a + (n - 1)d

Where

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d represents the common difference.

n represents the number of terms in the sequence.

From the information given,

a = - 6

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3 years ago

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Dovator [93]

Answer:

B) 0.0069

Step-by-step explanation:

To solve this question, we 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 $s = \frac{\sigma}{\sqrt{n}}$ .