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iragen [17]
3 years ago
6

An observational study of suburban towns reveals that towns with more dedicated park land tend to have higher median home prices

. A real estate agent suggests that a town’s crime rate is a more accurate predictor of median home price.
What is the confounding variable in this study?

the median home price
the crime rate
the distance from a large city
the median home size
Mathematics
2 answers:
lubasha [3.4K]3 years ago
4 0

Answer:

the median home size.

Step-by-step explanation:

In this scenario, the confounding variable would be the median home size. This is because this factor is both a cause and effect of the median home prices. A bigger house would obviously be worth more than a smaller house so the house size affects the prices of the homes in the market. At the same time, the median home sizes can also cause an increase or decrease in crime rates as criminals are more likely to target homes that seem as though they have more valuables inside.

Alja [10]3 years ago
4 0

Answer:

Crime rate

Step-by-step explanation:

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What is the slope of the line below? If necessary, enter your answer as a
alisha [4.7K]

Step-by-step explanation:

Use formula to find the slope/gradient

\frac{y2 - y1}{x2 - x1}

(-5, -1) = (x1, y1)

(5, 11) = (x2, y2)

So,

=  \frac{11 - ( - 1)}{5 - ( - 5)}  \\  =  \frac{12}{10 }  \\  =  \frac{6}{5}

8 0
3 years ago
5 g of margarine contains 3.6 g
Komok [63]

Answer:

59.04g of fat

Step-by-step explanation:

I) Figure out how much grams of fat is in 1g of margarine:

3.6 ÷ 5 = 0.72

II) Next, we can figure out how much fat is in 82 g of margarine:

0.72 × 82 = 59.04

One shot formula:

(3.6g ÷ 5g) × 82g = 59.04g

8 0
3 years ago
Among all right circular cones with a slant height of 24​, what are the dimensions​ (radius and​ height) that maximize the volum
aleksklad [387]

Answer:

5571.99

Step-by-step explanation:

We need to use the Pythagorean theorem to solve the problem.

The theorem indicates that,

r^2+h^2=24^2 \\r^2+h^2=576\\r^2=576-h^2

Once this is defined, we proceed to define the volume of a cone,

v=\frac{1}{3}\pi r^2 h

Substituting,

v=\frac{1}{3} \pi (576-h^2)h\\v=\frac{1}{3} \pi (576h-h^3)

We need to find the maximum height, so we proceed to calculate h, by means of its derivative and equalizing 0,

\frac{dv}{dh} = \frac{1}{3} \pi (576-3h^2)

\frac{dv}{dh} = 0 then \rightarrow \frac{1}{3}\pi(576-3h^2)=0

h_1=-8\sqrt{3}\\h_2=8\sqrt{3}

<em>We select the positiv value.</em>

We have then,

r^2 = 576-(8\sqrt3)^2 = 384\\r=\sqrt{384}

We can now calculate the maximum volume,

V_{max}= \frac{1}{3}\pi r^2 h = \frac{1}{3}\pi (\sqrt{384})^2 (8\sqrt{3}) = 5571.99

4 0
3 years ago
HELP ASAP!!! (The problem is on a screenshot)
Darina [25.2K]

The correct answers are A, D, and E.

7 0
3 years ago
Travel time data is collected on an arterial. With 30 runs, an average travel time of 152 seconds is computed over the 2.0 miles
o-na [289]

Answer:

a

 The 95% confidence bounds is  145.80 <  \mu <   158.19

b

It was not necessary to make any assumption about the shape of the travel  time distribution

Step-by-step explanation:

From the question we are told that

 The sample size is  n =  30  

  The sample mean  is  \=x = 152

   The standard deviation is  \sigma =  17.3 \  second

From the question we are told the confidence level is  95% , hence the level of significance is    

      \alpha = (100 - 95 ) \%

=>   \alpha = 0.05

Generally from the normal distribution table the critical value  of  \frac{\alpha }{2} is  

   Z_{\frac{\alpha }{2} } =  1.96

Generally the margin of error is mathematically represented as  

      E = Z_{\frac{\alpha }{2} } *  \frac{\sigma }{\sqrt{n} }

=>    E =  1.96 *  \frac{17.3 }{\sqrt{30} }

=>     E = 6.19  

Generally 95% confidence bounds  is mathematically represented as  

      \= x -E <  \mu <  \=x  +E

=>  152  -6.19 <  \mu <  152  -6.19

=> 145.80 <  \mu <   158.19

This 95% confidence bounds show that there is 95% confidence that the true mean lies within this bound hence there is it was not necessary to make any assumption about the shape of the travel  time distribution

5 0
3 years ago
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