Answer: f(x)=2-x^2
Step-by-step explanation:
The quadratic equation is
y=ax^2+bx+c
and c is equal to the y-intercept.
in the twi graphs shown both have the same shape but different y-intervepts.
c(the y-intercept) in the first graph is 5 and in the second graph(F) is 2.
Answer:
Step-by-step explanation:
Previous concepts
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".
The margin of error is the range of values below and above the sample statistic in a confidence interval.
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The population proportion have the following distribution
Solution to the problem
We assume for this case a confidence level of 95%. In order to find the critical value we need to take in count that we are finding the interval for a proportion, so on this case we need to use the z distribution. Since our interval is at 95% of confidence, our significance level would be given by
and
. And the critical value would be given by:

The confidence interval for the mean is given by the following formula:
The margin of error for the proportion interval is given by this formula:
(a)
And if we replace the values obtained we got this:
Answer: y=5/7x+2
Step-by-step explanation:
The y- intercept would be 2 since that is where the line goes through the y axis. Also if you use slope form you will see that the slope is 5/7.
Step-by-step explanation:
Regression analysis is used to infer about the relationship between two or more variables.
The line of best fit is a straight line representing the regression equation on a scatter plot. The may pass through either some point or all points or none of the points.
<u>Method 1:</u>
Using regression analysis the line of best fit is: 
Here <em>α </em>= intercept, <em>β</em> = slope and <em>e</em> = error.
The formula to compute the intercept is:

Here<em> </em>
and
are mean of the <em>y</em> and <em>x</em> values respectively.

The formula to compute the slope is:

And the formula to compute the error is:

<u>Method 2:</u>
The regression line can be determined using the descriptive statistics mean, standard deviation and correlation.
The equation of the line of best fit is:

Here <em>r</em> = correlation coefficient = 
and
are standard deviation of <em>x</em> and <em>y</em> respectively.

I hope it workssssssssssssssssssssss.