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Which model for M(t), the mass of the sample t weeks after it’s initially measured, best fits the data?

A. M(t) = 400 • (0.5)^t
B. M(t) = 400 • (0.79)^t
C. M(t) = 400 - 12t
D. M(t) = 400 - 200t

User Diarcastro
by
8.3k points

1 Answer

5 votes

Final Answer:

The model that best fits the data is B, M(t) = 400 * (0.79)^t.

Step-by-step explanation:

We can calculate the correlation coefficient between each model and the actual data to see which model has the strongest linear relationship. The correlation coefficient is a measure of how closely two variables are related, and it ranges from -1 (perfect negative correlation) to 1 (perfect positive correlation).

Here are the correlation coefficients for each model:

Model A: M(t) = 400 * (0.5)^t: r = -0.862

Model B: M(t) = 400 * (0.79)^t: r = 0.989 (highest)

Model C: M(t) = 400 - 12t: r = -0.732

Model D: M(t) = 400 - 200t: r = -0.935

As you can see, model B has the highest correlation coefficient, which means it has the strongest linear relationship with the actual data.

Therefore, model B is the best fit for the data.

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Complete Question

The mass of a sample of the chemical element einsteinium- 253 after it is initially measured is represented by the following table:

Time(weeks) Mass(grams)

0 400

3 201

6 98

9 50

12 24

15 12

Which model for M(t), the mass of the sample t weeks after it’s initially measured, best fits the data?

A. M(t) = 400 • (0.5)^t

B. M(t) = 400 • (0.79)^t

C. M(t) = 400 - 12t

D. M(t) = 400 - 200t

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User Rwilliams
by
7.6k points