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daser333 [38]
2 years ago
10

Some residuals for a scatterplot are given. for x = 3, the residual is –5. for x = 5, the residual is –1. for x = 7, the residua

l is 3. for x = 9, the residual is 0. for which value of x is the data point farthest from the line of best fit? 3 5 7 9
Mathematics
1 answer:
Viktor [21]2 years ago
7 0

The value of x that is the data point farthest from the line of best fit is 3

<h3>How to determine the x value farthest from the line of best fit?</h3>

The given parameters are:-

x      Residual

3         -5

5         -1

7          3

9          0

Take the absolute value of the residuals

x      Residual

3         5

5         1

7         3

9         0

The largest absolute value is 5

Hence, the value of x that is the data point farthest from the line of best fit is 3

Read more about residuals at:

brainly.com/question/16180255

#SPJ4

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Hoochie [10]

The correct answer is C (7, 9)

Firstly we know that each point is 6 away from the other in terms of x and in terms of y. Now we also know that for every 6, we will be one away from point B and five away from point A. We know this because the ratio is AB 5:1, meaning that the 5 is on the A side (they both come first).

So, we can just add 5 to each of the A value numbers to get point P.

A = (2, 4)

P = (2+5, 4+5)

P = (7, 9)

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300 dollars would be the independent variable and 50 dollars a week is dependent
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The price of a 2 dozen gum balls is $4
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3 years ago
Twenty-five students from Harry High School were accepted at Magic University. Of those students, 10 were offered athletic schol
Taya2010 [7]

Answer:

Step-by-step explanation:

Part A

For Athletic scholarship,

Mean = (16 + 24 + 20 + 25 + 24 + 23 + 21 + 22 + 20 + 20)/10 = 21.5

Standard deviation = √(summation(x - mean)²/n

n = 10

Summation(x - mean)² = (16 - 21.5)^2 + (24 - 21.5)^2 + (20 - 21.5)^2 + (25 - 21.5)^2 + (24 - 21.5)^2 + (23 - 21.5)^2 + (21 - 21.5)^2 + (22 - 21.5)^2 + (20 - 21.5)^2 + (20 - 21.5)^2 = 64.5

Standard deviation = √64.5/10 = 2.54

For non athletic scholarship,

Mean = (23 + 25 + 26 + 30 + 32 + 26 + 28 + 29 + 26 + 27 + 29 + 27 + 22 + 24 + 25)/15 = 26.6

n = 15

Summation(x - mean)² = (23 - 26.6)^2 + (25 - 26.6)^2 + (26 - 26.6)^2 + (30 - 26.6)^2 + (32 - 26.6)^2 + (26 - 26.6)^2 + (28 - 26.6)^2 + (29 - 26.6)^2 + (26 - 26.6)^2 + (27 - 26.6)^2 + (29 - 26.6)^2 + (27 - 26.6)^2 + (22 - 26.6)^2 + (24 - 26.6)^2 + (25 - 26.6)^2 = 101.6

Standard deviation = √101.6/15 = 2.6

This is a test of 2 independent groups. The population standard deviations are not known. it is a two-tailed test. Let 1 be the subscript for scores of athletes and 2 be the subscript for scores of non athletes.

Therefore, the population means would be μ1 and μ2

The random variable is x1 - x2 = difference in the sample mean scores of athletes and non athletes.

We would set up the hypothesis.

The null hypothesis is

H0 : μ1 = μ2 H0 : μ1 - μ2 = 0

The alternative hypothesis is

H1 : μ1 ≠ μ2 H1 : μ1 - μ2 ≠ 0

Since sample standard deviation is known, we would determine the test statistic by using the t test. The formula is

(x1 - x2)/√(s1²/n1 + s2²/n2)

From the information given,

x1 = 21.5

x2 = 26.6

s1 = 2.54

s2 = 2.6

n1 = 10

n2 = 15

t = (21.5 - 26.6)/√(2.54²/10 + 2.6²/15)

t = - 4.65

The formula for determining the degree of freedom is

df = [s1²/n1 + s2²/n2]²/(1/n1 - 1)(s1²/n1)² + (1/n2 - 1)(s2²/n2)²

df = [2.54²/10 + 2.6²/15]²/[(1/10 - 1)(2.54²/10)² + (1/15 - 1)(2.6²/15)²] = 1.2008/0.1039

df = 12

We would determine the probability value from the t test calculator. It becomes

p value = 0.00056

Since alpha, 0.1 > than the p value, 0.00056, then we would reject the null hypothesis.

Therefore, these data provide convincing evidence of a difference in ACT scores between athletes and nonathletes.

Part B

The formula for determining the confidence interval for the difference of two population means is expressed as

Confidence interval = (x1 - x2) ± z√(s²/n1 + s2²/n2)

For a 90% confidence level, the z score from the normal distribution table is 1.645

x1 - x2 = 21.5 - 26.6 = - 5.1

√(s1²/n1 + s2²/n2) = √(2.54²/10 + 2.6²/15) = 1.05

The confidence interval is - 5.1 ± 1.05

This analysis provides evidence that the mean scores for non athletes is higher than the mean scores for athletes, and that the difference between means in the population is likely to be between 4.05 and 6.15

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