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TiliK225 [7]
2 years ago
11

Assume that the distribution of weights of adult men in the United States is normal with mean 190 pounds and standard deviation

30 pounds. The weight of a randomly selected adult male in the United States marks the start of the 40th percentile. How much does he weigh? Enter a number rounded to two decimal places, e.g. 165.12 not 165.12876. Do not enter the units.
Mathematics
1 answer:
avanturin [10]2 years ago
5 0

Answer:

182.41

Step-by-step explanation:

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.

In this problem, we have that:

\mu = 190, \sigma = 30

40th percentile

Value of X when Z has a pvalue of 0.4. So X when Z = -0.253.

Z = \frac{X - \mu}{\sigma}

-0.253 = \frac{X - 190}{30}

X - 190 = -0.253*30

X = 182.41

So the answer is 182.41.

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Can we predict how fast a tennis player can hit a serve from the playerâs height? The following computer output and scatterplot
olga_2 [115]

Complete question :

The computer output and scatter plot output pertaining to the question can be found in the attached picture.

Answer:

Kindly check explanation

Step-by-step explanation:

A.) Relationship between height and fastest serve speed :

According to the scatterplot and Correlation Coefficient (R) value which can be obtauned by getting the square root of R²

R = √27.7%

R = 0.5263 = 52.63% ; this depicts a fairly strong positive correlation or relationship between height and fastest serve speed

B.)

Equation of least square regression line :

From the computer output and scatter plot above :

Recall :

y = mx + c

y =predicted variable (s fastest serve)

m= slope

x = predictor variable (height)

c = intercept

y = 84.98x + 68.81

C.) 27.7% of the variation in fastest speed can be explained by height while the remaining percentage is due to other variables

D.) fastest serve of tennis player with height 1.7m

y = 84.98x + 68.81

y = 84.98(1.7) + 68.81

y = 213.276km/hr

E.)

R = √27.7%

R = 0.5263 = 52.63% ; this depicts a fairly strong positive correlation or relationship between height and fastest serve speed

F.)

Height = 2.06m = x

y = 84.98(2.06) + 68.81

y = 243.8688 km/hr

Residual = Actual - predicted

Actual = 230 ; predicted = 243.8688

Residual = 230 - 243.8688

Residual = −13.8688

Hence, the model overestimated fastest serve speed of a 2.06 m tall player by −13.8688 km/hr

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Answer:c

Step-by-step explanation:

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When Sophia runs the 400 meter dash, her finishing times are normally distributed with a mean of 75 seconds and a standard devia
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e-lub [12.9K]

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The difference in areas is 36 - 4 = 32 which is the area of the shaded region

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In summary:

1. The unshaded square (smallest square) has area 4 square inches

2. The area of the large square is 36 square inches

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Find the missing term. () + (7 − 3i) + (5 + 9i) + 13i = 10 − 5i.
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X + (7 - 3i) + (5 + 9i) + 13i = 10 - 5i

Subtract 13i from both sides

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Do the same with (7 - 3i). You'll be adding 3i since -(-3i) = 3i.

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5 0
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