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tamaranim1 [39]
2 years ago
10

. The total distance from Keith's home to the office,

Mathematics
1 answer:
Serggg [28]2 years ago
3 0

Answer:

the total distance from the home to the office is 52 m

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The residual plot for a data set is shown.
Cerrena [4.2K]

Answer:

The regression line is not a good model because there is a pattern in the residual plot.

Step-by-step explanation:

Given is a  residual plot for a data set

The residual plot shows scatter plot of x and y

The plotting of points show that there is not likely to be a linear trend of relation between the two variables. It is more likely to be parabolic or exponential.

Hence the regression line cannot be a good model as they do not approach 0.

Also there is not a pattern of linear trend.

D) The regression line is not a good model because there is a pattern in the residual plot.

3 0
3 years ago
Read 2 more answers
Due today. Pls help.
alexandr1967 [171]
X is 19
Explanation: because the opposite side of the angle is 134 degrees the other side also has to be 134 degrees. So we do 134-20 which is 114 and then 114 divided by 6 because the number next to x is 6 and the number that is x has to be 19 as 19x6 is 114.
I think this is the right answer and I hope it helps :)
5 0
3 years ago
Read 2 more answers
What is the standard form of the equation y=3/4x-6
umka21 [38]
Answer :

y=3/4x-6

explanation:

it is already in standard form.
6 0
3 years ago
PLEASE HELP ASAP THERE ARE 20 POINTS ON THE LINE! Sierra has to pay 7% taxes on her purchase at IKEA. If the tax is $38.36, what
Dominik [7]

Answer:

$31.36

Step-by-step explanation:

If she has $38.36 and you subtract 7 you would get the answer $31.36. I hope I helpped (◡ ω ◡)

6 0
3 years ago
An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation a
Amiraneli [1.4K]

Answer:

Following are the responses to the given question:

Step-by-step explanation:

Mean Absolute Deviation MAD

MAD = \sum_{i=1}^{n} \frac{\left | actual_{i}-forecast_{i} \right |}{n}

Mean squared error  

MSE=\Sigma^{n}_{i=1} \frac{(Actual_i - Forecast_i)^2}{(n - 1)}

linear trend equation is Ft = 124 + 2t

MAD = \frac{23}{10} = 2.3\\\\MSE = \frac{91}{9}= 10.11\\\\

Naive method

MAD = \frac{36}{9} = 4\\\\MSE = \frac{202}{8}=25.25\\\\MAD (Naive) = 4\\\\MAD (Linear) =2.3\\\\MSE (Naive)=25.25\\\\MSE (Linear)=10.11\\\\

Please find the attached file.

7 0
3 years ago
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