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miskamm [114]
3 years ago
8

Suppose a football is kicked with an initial velocity of 82 ft/sec., at an angle of

Mathematics
1 answer:
satela [25.4K]3 years ago
6 0

Answer:

The position P is:

P = 87\^x + 75\^y ft     <u><em> Remember that the position is a vector. Observe the attached image</em></u>

Step-by-step explanation:

The equation that describes the height as a function of time of an object that moves in a parabolic trajectory with an initial velocity s_0 is:

y(t) = y_0 + s_0t -16t ^ 2

Where y_0 is the initial height = 0 for this case

We know that the initial velocity is:

82 ft/sec at an angle of 58 ° with respect to the ground.

So:

s_0 = 82sin(58\°) ft/sec

s_0 = 69.54 ft/sec

Thus

y(t) = 69.54t -16t ^ 2

The height after 2 sec is:

y(2) = 69.54 (2) -16 (2) ^ 2

y(2) = 75\ ft

Then the equation that describes the horizontal position of the ball is

X(t) = X_0 + s_0t

Where

X_ 0 = 0 for this case

s_0 = 82cos(58\°) ft / sec

s_0 = 43.45 ft/sec

So

X(t) = 43.45t

After 2 seconds the horizontal distance reached by the ball is:

X (2) = 43.45(2)\\\\X (2) = 87\ ft

Finally the vector position P is:

P = 87\^x + 75\^y ft

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Zina [86]

Answer:

The equation of the regression line is: y~=~88.518 ~-~ 3.068 \cdot x

Step-by-step explanation:

Linear regression is a linear approach to modelling the relationship between a dependent variable and one or more independent variables.

Let X be the independent variable and Y be the dependent variable. We will define a linear relationship between these two variables as follows:

Y=bX+a

We have the the following data:

\begin{array}{c|cccccccccc}No. \:of \:absences,\:x&0&1&2&3&4&5&6&7&8&9\\Final \:grade, y&88.5&85.7&82.8&80.3&77.4&73.1&63.6&68.1&65.2&62.4\end{array}

To find the line of best fit for the points, follow these steps:

Step 1: Find X\cdot Y and X\cdot X as it was done in the table.

Step 2: Find the sum of every column:

\sum{X} = 45 ~,~ \sum{Y} = 747.1 ~,~ \sum{X \cdot Y} = 3108.8 ~,~ \sum{X^2} = 285

Step 3: Use the following equations to find intercept a and slope b:

\begin{aligned}        a &= \frac{\sum{Y} \cdot \sum{X^2} - \sum{X} \cdot \sum{XY} }{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} =             \frac{ 747.1 \cdot 285 - 45 \cdot 3108.8}{ 10 \cdot 285 - 45^2} \approx 88.518 \\ \\b &= \frac{ n \cdot \sum{XY} - \sum{X} \cdot \sum{Y}}{n \cdot \sum{X^2} - \left(\sum{X}\right)^2}        = \frac{ 10 \cdot 3108.8 - 45 \cdot 747.1 }{ 10 \cdot 285 - \left( 45 \right)^2} \approx -3.068\end{aligned}

Step 4: Assemble the equation of a line

\begin{aligned} y~&=~a ~+~ b \cdot x \\y~&=~88.518 ~-~ 3.068 \cdot x\end{aligned}

The graph of the regression line is:

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