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Dovator [93]
2 years ago
4

Joe runs 8.75 times around a track in 1,125.803 seconds. If one lap around the track is 420.3 meters, which is the best estimate

of the runner's average speed in meters per second (m/s)?
Mathematics
2 answers:
elena55 [62]2 years ago
8 0
8.75laps(420.3m/lap)/1125.803=3.26666 m/s

I don't know how your answers were rounded, so you can round appropriately.
olchik [2.2K]2 years ago
7 0

Answer:

Runner's average speed is 3.26666832 m/s.

Step-by-step explanation:

One lap around the track = 420.3 meters

Joe runs around a track  = 8.75 times

Joe runs total = 420.3 × 8.75 = 3,677.625 meters

Joe runs 3,677.625 meters in 1,125.803 seconds.

runner's average speed per second = \frac{3,677.625}{1,125.803}

                                                            = 3.26666832 meter/second.

Runner's average speed is 3.26666832 m/s.

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Find the ratio of $22 to $5.50
solniwko [45]

Answer:

4:1

Step-by-step explanation:

22/5.50

divide numerator by denominator and denominator by denominator

22/5.50=4

5.50/5.50=1

4/1 or 4:1

4 0
2 years ago
Which answer choice shows 12.444 rounded to the nearest half?
vesna_86 [32]

Answer:

C. 12

Step-by-step explanation:

Remember 0 to 4 turn it back

5 or above give it a shove.

Since 12.444 is around 0 to 4.

We can round that to 12.

3 0
2 years ago
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Four pounds of bananas cost $1.96. how much does it cost per pound?
adelina 88 [10]
4 pounds = $1.96
1.96 / 4 = $0.49 
4 0
2 years ago
Solve for x:<br> 3(5x + 10) + 10 = 6x - (x + 10)
34kurt

Answer:

x= -5

Step-by-step explanation:

3(5x+10)+10=6x-(x+10)

15x+30+10=6x-x-10

15x+40=5x-10

15x-5x=-10-40

10x=-50

x=-5

8 0
2 years ago
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A researcher gathers data on the length of essays​ (number of​ lines) and the SAT scores received for a sample of students enrol
LenaWriter [7]

Answer:

(C) The slope of the regression equation is not significantly different from zero

Step-by-step explanation:

Let's suppose that we have the following linear model:

y= \beta_o +\beta_1 X

Where Y is the dependent variable and X the independent variable. \beta_0 represent the intercept and \beta_1 the slope.

In order to estimate the coefficients \beta_0 ,\beta_1 we can use least squares estimation.

If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: \beta_1 = 0

Alternative hypothesis: \beta_1 \neq 0

Or in other wouds we want to check is our slope is significant.

In order to conduct this test we are assuming the following conditions:

a) We have linear relationship between Y and X

b) We have the same probability distribution for the variable Y with the same deviation for each value of the independent variable

c) We assume that the Y values are independent and the distribution of Y is normal

The significance level is provided and on this case is \alpha=0.05

The standard error for the slope is given by this formula:

SE_{\beta_1}=\frac{\sqrt{\frac{\sum (y_i -\hat y_i)^2}{n-2}}}{\sqrt{\sum (X_i -\bar X)^2}}

Th degrees of freedom for a linear regression is given by df=n-2 since we need to estimate the value for the slope and the intercept.

In order to test the hypothesis the statistic is given by:

t=\frac{\hat \beta_1}{SE_{\beta_1}}

The confidence interval for the slope would be given by this formula:

\hat \beta_1 + t_{n-2, \alpha/2} \frac{\sqrt{\frac{\sum (y_i -\hat y_i)^2}{n-2}}}{\sqrt{\sum (X_i -\bar X)^2}}

And using the last formula we got that the confidence interval for the slope coefficient is given by:

-0.88 < \beta_1

IF we analyze the confidence interval contains the value 0. So we can conclude that we don't have a significant effect of the slope on this case at 5% of significance. And the best option would be:

(C) The slope of the regression equation is not significantly different from zero

6 0
2 years ago
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