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EastWind [94]
3 years ago
6

For a set of data: x = (0,1,2,3,4,5,6) and y=(36, 28, 25, 24, 23, 21, 19), is it wise to use a linear regression to extrapolate

data for x = 50? Solution: Since the coefficient of determination is 0.8582, the linear model is a reasonably good fit for the data, so extrapolation for any x-value is acceptable. What is wrong with this solution?
Mathematics
1 answer:
melisa1 [442]3 years ago
4 0

Answer:

The problem with this solution is that a regression model is not recommended to extrapolate because we do not know if the linear relation that we calculated for a specific range of x values still holds outside this range.

Step-by-step explanation:

We have a linear regression model, with a range of the independent variable "x" that goes from 0 to 6.

The regression model finds a good fit (r=0.8582).

As it has a good fit, it is proposed to use this model to extrapolate and calculate the value of y for x=50.

It is not recommended to extrapolate a regression model unless we are really sure that the model is still valid within the range within we are extrapolating.

This means that if we have no proof that y has a linear relation in a range of x that includes x, the extrapolation has no validity and can lead to serious errors.

A linear regression model is only suitable for interpolation or extrapolating within the range we are sure that the relation between y and x is linear within a certain acceptable error.

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A small bar of gold measure 40 mm by 25 mm. by 2 mm. Find the volume in cubic millimeters.
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Answer:

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Read 2 more answers
A father wishes to give his son P200, 000 ten years from now. What amount should he invest if it will earn interest at 10% compo
Archy [21]

Answer:

C. P69,256.82

Step-by-step explanation:

We know that,

The amount formula in compound interest is,

A=P(1+\frac{r_1}{n_1})^{n_1t_1} (1+\frac{r_2}{n_2})^{n_2t_2}.......

Where, P is the principal amount,

r_1, r_2.... are the annual rate for the different periods,

t_1, t_2,..... are the number of year for different periods,

n_1, n_2, n_3... are the number of periods,

Given,

A = P 200,000,

r_1=10%=0.1, n_1=4, t_1=5,r_2=12%=0.12, n_2=1, t_2=5

Thus, by the above formula the final amount would be,

200000=P(1+\frac{0.1}{4})^{4\times 5}(1+\frac{0.12}{1})^{1\times 5}

200000=P(1+0.025)^{20}(1+0.12)^5

200000=P(1.025)^{20}(1.12)^5

\implies P=69,256.824\approx 69,256.82

Option C is correct.

8 0
3 years ago
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