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AleksAgata [21]
3 years ago
8

The children in my subdivision were bored one summer and decided to hold a competition to see who could run to the end of the st

reet in the shortest time. One hundred children participated, and the average finish time was 75 seconds. The SD was 20 seconds and the histogram of the times followed the normal curve. Estimate the percentage of children who finished the race in under 45 seconds.
Mathematics
1 answer:
Ainat [17]3 years ago
4 0

Answer:

6.7% of children who finished the race in under 45 seconds.

Step-by-step explanation:

We are given the following information in the question:

Mean, μ = 75 seconds

Standard Deviation, σ =  20 seconds

We are given that the distribution of time of completion is a bell shaped distribution that is a normal distribution.

Formula:

z_{score} = \displaystyle\frac{x-\mu}{\sigma}

P(finished the race in under 45 seconds.)

P(x < 45)

P( x < 45) = P( z < \displaystyle\frac{45 - 75}{20}) = P(z < -1.5)

Calculation the value from standard normal z table, we have,  

P(x < 45) = 0.067 = 6.7\%

6.7% of children who finished the race in under 45 seconds.

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Answer:

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Step-by-step explanation:

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[(theta)/360]*πr^2

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3 years ago
Find the value of x.<br> 3<br> x = [?]
satela [25.4K]

Answer:

12

Step-by-step explanation:

According to Euclidian theorem h^2 = 3*x (h : height)

36 = 3x divide both sides by 3

12 = x

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3 years ago
What is the Y intercept pls help
Ad libitum [116K]

Answer:

y- intercept = 1

Step-by-step explanation:

The y- intercept is the point on the y- axis where the graph crosses.

This occurs when the x- coordinate is 0

From the table the point (0, 1 ) is where the graph crosses the y- axis

Then y- intercept = 1

5 0
3 years ago
In a study relating the degree of warping, in mm, of a copper plate (y) to temperature in °C (x), the following summary statisti
kipiarov [429]

Answer:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

Step-by-step explanation:

Linear regression is a way "to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables)".

Regression estimates are "used to describe data and to explain the relationship between one dependent variable and one or more independent variables"

The linear model is given by the following equation Y=mx +b, where y is the dependent variable, x the independent variable, m the slope and b the intercept.

For this case we have the following info given:

\sum_{i=1}^n (x_i -\bar x)^2 =98775

\sum_{i=1}^n (y_i -\bar y)^2 =19.4

\bar x =26.36

\bar y =0.5188

n= 40  represent the sample size

\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y) =796.94

The total sum of squares is given by this formula:

SST= \sum_{i=1}^n (y_i -\bar y)^2 =19.4

And from the formulas for a simple regression, we need to calculate the slope for the regression like this:

m=\frac{\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)}{\sum_{i=1}^n (x_i -\bar x)^2}

And if we replace the values given we have:

m=\frac{796.94}{98775}=0.008068

We have another useful equation in order to find the sum of squares for the regression, given by:

SSR=m* \sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)=0.008068*796.94=6.430

And we know this equivalence:

SST= SSR+SSE

And solving for the sum of squares for the error we have:

SSE=SST-SSR=19.4-6.430=12.97

So then we have the final solutions:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

6 0
3 years ago
Don’t mind the already picked answer..i don’t understand this question though
Tatiana [17]
The answer is = because all of the other dimensions to the triangles are equal.
5 0
3 years ago
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