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Vladimir [108]
3 years ago
14

The number of students going to the school field trip reduced from 1000 to 950. What is the percent of change? I will help the f

irst person who gets it right and helps
Mathematics
1 answer:
klasskru [66]3 years ago
3 0

Answer:

decrease of 5%

Step-by-step explanation:

always start of by finding 10% which would be 100 students

1000-100=900

you would still have 50 students left

half of 100 is 50 so half of 10% is 50 students

5%=50 students

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Amswer in its lowest terms<br> 5 3/5 + 2 1/10
Nataly [62]

5 \frac{3}{5}  + 2 \frac{1}{10}  \\  =  \frac{28}{5}  +  \frac{21}{10}  \\  =  \frac{56}{10}  +  \frac{21}{10}  \\  =  \frac{77}{10}  \\  = 7 \frac{7}{10}

<em>Hope it helps and is useful :)</em>

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3 years ago
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picture included , please help, which of the following equations describe the line shown below (1,10) and (-3,2) *check all that
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Slope is\text{m}=\frac{y_1-y_2}{x_1-x_2}=\cfrac{10-2}{1-(-3)}
Then you use the equation
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10=m(1)+b
You know m (from above) and now you can solve for b.

Rearrange terms:
y-b=mx

And that will be the answer.

Make sense?
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The difference between the observed value of the dependent variable and the value predicted using the estimated regression equat
Elenna [48]

Answer:

For this case we define the dependent variable as Y and the independent variable X. We assume that we have n observations and that means the following pairs:

(x_1, y_1) ,....,(x_n,y_n)

For this case we assume that we want to find a linear regression model given by:

\hat y = \hat m x +\hat b

Where:

\hat m represent the estimated slope for the model

\hat b represent the estimated intercept for the model

And for any estimation of the dependent variable \hat y_i , i=1,...,n is given by this model.

The difference between the observed value of the dependnet variable and the value predicted using the estimated regression equation is known as residual, and the residual is given by this formula:

e_i = y_i -\hat y_i , i=1,...,n

So the best option for this case is:

d. residual

Step-by-step explanation:

For this case we define the dependent variable as Y and the independent variable X. We assume that we have n observations and that means the following pairs:

(x_1, y_1) ,....,(x_n,y_n)

For this case we assume that we want to find a linear regression model given by:

\hat y = \hat m x +\hat b

Where:

\hat m represent the estimated slope for the model

\hat b represent the estimated intercept for the model

And for any estimation of the dependent variable \hat y_i , i=1,...,n is given by this model.

The difference between the observed value of the dependnet variable and the value predicted using the estimated regression equation is known as residual, and the residual is given by this formula:

e_i = y_i -\hat y_i , i=1,...,n

So the best option for this case is:

d. residual

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Answer:

They both have the same answer.

Step-by-step explanation:

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