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Aleonysh [2.5K]
2 years ago
6

If f(1) = 5 and f(n) = 4f(n − 1) - 2 then find the value of f(5).​

Mathematics
1 answer:
MakcuM [25]2 years ago
3 0

Hi,

This is the same situation as a sequence case.

You have two informations :

\left \{ {{f(1)=5} \atop {f(n)=4f(n-1)-2}} \right.

You need to solve this rank by rank for n = 1, 2, 3, 4 and 5.

We already have f(n) for n = 1 : it is f(1) = 5.

n = 2 :

f(2) = 4 * f(2-1) - 2 = 4 * f(1) - 2 = 4 * 5 - 2 = 20 - 2 = 18 because f(1) = 5

n=3 :

f(3) = 4 * f(3-1) -2 = 4 * f(2) -2 = 4 * 18 -2 = 72 - 2 = 70

n = 4 :

f(4) = 4 * f(4-1) -2 = 4* f(3) - 2 = 4* 70 - 2 = 280 - 2 = 278

n = 5 :

f(5) = 4 * f(5-1) - 2 = 4*f(4) - 2 = 4 * 278 - 2 = 1112 - 2 = 1110

so f(5) = 1110

Good Luck

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When we test Upper H 0​: muequals0 against Upper H Subscript a​: mugreater than​0, we get a​ P-value of 0.03. a. What would the
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Answer:

(a) The null hypothesis will be rejected.

(b) Type I error

(c) The null hypothesis will not be rejected. The error is type II error.

Step-by-step explanation:

The hypothesis provided is:

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The p-value of the test obtained is 0.03

(a)

Decision rule for hypothesis testing, based on p-value, states that if the p-value is less than the significance level (α) then the null hypothesis is rejected and vice versa.

The significance level is α = 0.10

Then,

p-value = 0.03 < \alpha  = 0.10

Thus, the null hypothesis will be rejected.

Conclusion:

The null hypothesis is rejected stating that the value of μ is more than 0.

(b)

If the decision in​ (a) is an​ error, i.e. the null hypothesis is rejected when in fact it is true, this type of error is known as type I error.

(c)

The significance level is α = 0.01

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p-value = 0.03 > \alpha  = 0.01

Thus, the null hypothesis will not be rejected.

Conclusion:

The null hypothesis was not rejected stating that the value of μ is 0.

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3 years ago
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The total bottle sold on monday is so i'm gonna assume that 40 people were in the cafeteria that day. The cafeteria had 80 customers, which is double the amount of customers from yesterday. If we want to make predictions from monday's data, we should double all the values in the table (so basically apple juice is now 22, cranberry is 14, etc.) so it's more fitting to the number of customers on tuesday.

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8 0
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\huge\underline{\red{A}\blue{n}\pink{s}\purple{w}\orange{e}\green{r} -}

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We know that ,

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