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Tasya [4]
2 years ago
14

Use the initial term and the recursive formula to find an explicit formula for the sequence an. Write your answer in simplest fo

rm.
Mathematics
1 answer:
Ipatiy [6.2K]2 years ago
4 0

Answer:

a_n = -11-14n

Step-by-step explanation:

Given

a_1 = -25

a_n = a_{n-1}-14

Required

The explicit formula

First, calculate a_2

Set n=2; So:

a_2 = a_{2-1}-14

a_2 = a_{1}-14

Substitute -25 for a_1

a_2 = -25-14

a_2 = -39

Calculate the common difference (d)

d = a_2 - a_1

d = -39 --25

d = -14

So, the nth term is:

a_n = a_1 + (n - 1)d

a_n = -25+ (n - 1)*-14

Open bracket

a_n = -25-14n + 14

Collect like terms

a_n = 14-25-14n

a_n = -11-14n

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*nervous laugh* SO ummm geometry isnt my thing actually im rather bad it please help!
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3 years ago
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2 years ago
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Given the probability distributions shown to the​ right, complete the following parts.
Elan Coil [88]

Answer:

a) Expected Value for distribution A, E(X) = 3.020

Expected Value for distribution B, E(X) = 0.980

b) Standard deviation of distribution A = 1.157

Standard deviation of distribution B = 1.157

c) In distribution A, the bigger values of x have a higher probability of occurring than the values of distribution B (whose smaller values of x have a higher chance of occurring, hence, the expected value for distribution A is more than that of distribution B.

But according to the corresponding distribution of values, the two distributions have the same exact spread, A in ascending order (with higher values with bigger probability) and B in descending order (lower values have higher probabilities). But the same spread regardless, hence, the standard deviation which shows how data values spread around the mean (centre point) of a distribution is the same for the two distributions.

Step-by-step explanation:

Expected values is given as

E(X) = Σ xᵢpᵢ

where xᵢ = each possible sample space

pᵢ = P(X=xᵢ) = probability of each sample space occurring.

Distributions A and B is given by

X P(X) X P(x)

0 0.04 0 0.47

1 0.09 1 0.25

2 0.15 2 0.15

3 0.25 3 0.09

4 0.47 4 0.04

For distribution A

E(X) = Σ xᵢpᵢ = (0×0.04) + (1×0.09) + (2×0.15) + (3×0.25) + (4×0.47) = 3.02

For distribution B

E(X) = Σ xᵢpᵢ = (0×0.47) + (1×0.25) + (2×0.15) + (3×0.09) + (4×0.04) = 0.98

b) Standard deviation = √(variance)

But Variance is given by

Variance = Var(X) = Σx²p − μ²

where μ = E(X)

For distribution A

Σx²p = (0²×0.04) + (1²×0.09) + (2²×0.15) + (3²×0.25) + (4²×0.47) = 10.46

Variance = Var(X) = 10.46 - 3.02² = 1.3396

Standard deviation = √(1.3396) = 1.157

For distribution B

Σx²p = (0²×0.47) + (1²×0.25) + (2²×0.15) + (3²×0.09) + (4²×0.04) = 2.30

Variance = Var(X) = 2.30 - 0.98² = 1.3396

Standard deviation = √(1.3396) = 1.157

c) In distribution A, the bigger values of x have a higher probability of occurring than the values of distribution B (whose smaller values of x have a higher chance of occurring, hence, the expected value for distribution A is more than that of distribution B.

But according to the corresponding distribution of values, the two distributions have the same exact spread, A in ascending order (with higher values with bigger probability) and B in descending order (lower values have higher probabilities). But the same spread regardless, hence, the standard deviation which shows how data values spread around the mean (centre point) of a distribution is the same for the two distributions.

7 0
3 years ago
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Answer:

The first picture and 28.2 square units

Step-by-step explanation:

Equation: A+1/2ps

A = area of the base

p = perimeter of the base

s = slant height

3²+1/2(12)(3.2)=28.2

7 0
3 years ago
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