Compute the standard deviation for the set of data 2, 5, 6, 8, 14

You want to estimate the mean weight loss of people one year after using a popular weight-loss program being advertised on TV. H

maria [59]

Answer:

At least 6907 people.

Step-by-step explanation:

Population std deviation = sigma= 10.6

Since population std deviation is known, we can use normal probability table to get sample size from confidence interval.

The sample mean weight loss is within 0.25 lb of the true population mean.

Hence margin of error < 0.25

Margin of error = z critical (std dev/n) where n = sample size

Z critical for 95% = 1.96

Hence 0.25 >1.96(10.6)/sq rt n

Simplify to get

sq rt n > 1.96(10.6)/0.25 = 83.104

Square both the sides to get

n > 83.104 square = 6906.27

i.e. sample size should be atleast 6907.

3 0

3 years ago

I WILL GIVE BRAINLIESTTT

larisa [96]

Answer:using the graph of a function you can find the value of f (x), all you need to do is locate on the x axis, the value, in this case 3, and we will find f (3), locate the number (3 ) on the x-axis and see what is the value of y that the function takes at that point, that will be the value f (3)

Step-by-step explanation:it’s a

b. The function f(x)=g(x)/h(x) will have a horizontal asymptote only if the degree of g is less than or equal to the degree of h.

8 0

2 years ago

The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x

Andrew [12]

Answer:

$r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}$

The value of r is always between $-1 \leq r \leq 1$

And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

$r^2 = 0.8^2 = 0.64$

So then the best conclusion for this case would be:

c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.

Step-by-step explanation:

For this case we know that the correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. And we know that we use the height x of a child to predict the weight y of the child

We need to rememeber that the correlation is a measure of dispersion of the data and is given by this formula:

$r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}$

The value of r is always between $-1 \leq r \leq 1$

And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

$r^2 = 0.8^2 = 0.64$

So then the best conclusion for this case would be:

c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.

3 0

3 years ago

1 Which expression is equivalent to

Fiesta28 [93]

Answer:

what's the original equation

Step-by-step explanation:

4 0

3 years ago

A company bought New Year's greeting cards to send to its valued customers. Sixty of the cards they sent cost $2.30 each. Thirty

const2013 [10]

Answer:

$287.82

Step-by-step explanation:

60 * 2.30 = 138

30 * 2.75 = 82.5

34 * 1.98 = 67.32

138 + 82.5 + 67.32 = 287.82

3 0

3 years ago