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F(1)=-12, f(n)=2f(n-1) <br> find first 4 terms

amid [387]

<h3>First four terms are: -12, -24, -48, -96</h3>

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Explanation:

The notation f(1) = -12 tells us that the first term is -12.

The equation f(n) = 2*f(n-1) indicates that we're multiplying the (n-1)th term by 2 to get the nth term. Basically we multiply each term by 2 to get the next term.

-12*2 = -24

-24*2 = -48

-48*2 = -96

So the first four terms are -12, -24, -48, -96.

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Alternative Approach

f(1) = -12 .... first term

f(n) = 2*f(n-1) ... nth term recursive formula

f(2) = 2*f(2-1) ... plug in n = 2

f(2) = 2*f(1)

f(2) = 2*(-12) ... plug in f(1) = -12

f(2) = -24 ... second term

f(n) = 2*f(n-1) .... resetting for the next computation

f(3) = 2*f(3-1) ... plug in n = 3

f(3) = 2*f(2)

f(3) = 2*(-24) ... plug in f(2) = -24

f(3) = -48 .... third term

f(n) = 2*f(n-1) ... one more reset

f(4) = 2*f(4-1) .... plug in n = 4

f(4) = 2*f(3)

f(4) = 2*(-48) ... plug in f(3) = -48

f(4) = -96 ... fourth term

We get the first four terms to be -12, -24, -48, -96, which was the same as earlier.

4 0

2 years ago

Asked what the central limit theorem says, a student replies, As you take larger and larger samples from a population, the histo

Arada [10]

Answer:

A. No, the student is not right. The central limit theorem says nothing about the histogram of the sample values. It deals only with the distribution of the sample means.

Step-by-step explanation:

No, the student is not right. The central limit theorem says nothing about the histogram of the sample values. It deals only with the distribution of the sample means. The central limit theorem says that if we take a large sample (i.e., a sample of size n > 30) of any distribution with finite mean $\mu$ and standard deviation $\sigma$ , then, the sample average is approximately normally distributed with mean $\mu$ and variance $\sigma^2/n$ .