Help! :)

Based on the scatterplot, which equation BEST represents the relationship between velocity and time?

lutik1710 [3]

The line of best-fit that represents the relationship between velocity and time is:

v = 2.19t + 6.7.

<h3>How to find the equation of linear regression using a calculator?</h3>

To find the equation, we need to insert the points (x,y) in the calculator.

For this problem, the points (t,v) are given as follows:

(0, 6.1), (2.1, 12.2), (5.3, 17.4), (8.2, 26.4), (10, 28.1), (12.1, 32.8).

Hence, inserting these points into a calculator, the equation is given by:

v = 2.19t + 6.7.

More can be learned about a line of best-fit at brainly.com/question/22992800

#SPJ1

3 0

1 year ago

What is the slope-intercept form of the equation y - 7= -5/2(x+4)

GREYUIT [131]

The first thing I would probably do is distribute (multiply) the -5/2 into the parenthesis:

= (-5/2)x + (-20/2)

Notice how I am not putting the x into the fraction. This is to make it easier to see the slope-intercept form.

Lets simplify the (-20/2) and then add 7 to both sides:

y - 7 = (-5/2)x - 10

y = (-5/2)x - 3

Your answer would then be:

y = (-5/2)x - 3

y = mx + b

Since it is now in the requested format.

4 0

3 years ago

Suppose that 76% of Americans prefer Coke to Pepsi. A sample of 80 was taken. What is the probability that at least seventy perc

Anastasy [175]

Answer:

C. 0.896

Step-by-step explanation:

We use the binomial approximation to the normal 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:

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

Normal probability distribution

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