What is the answer after convergence in TI-Nspire CX CAS?

In summary, the content of the conversation is about evaluating an answer from the TI-Nspire CX CAS calculator, specifically the sum of a geometric series. The answer is found to be $-\frac{1}{36}$ using the formula for a geometric series. The IP addresses of the individuals involved are also mentioned.
  • #1
karush
Gold Member
MHB
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$\text{Evaluate answer from }\textit{ TI-Nspire CX CAS}$
\begin{align*}
\displaystyle
S_k&=\sum_{k=1}^{\infty}
\left[\frac{(-2)}{9^{k+1}}\right]
=\frac{-2}{99} \\
\end{align*}
ok wasn't sure what weapon of choice to use
$\tiny{206.10.3.75}$
☕
 
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  • #2
\(\displaystyle S=\sum_{k=1}^{\infty}\left(\frac{-2}{9^{k+1}}\right)=-\frac{2}{81}\sum_{k=1}^{\infty}\left(\left(\frac{1}{9}\right)^{k-1}\right)=-\frac{2}{81}\cdot\frac{1}{1-\dfrac{1}{9}}=-\frac{2}{81}\cdot\frac{9}{8}=-\frac{1}{36}\)
 
  • #3
$\text{Evaluate }$
$$\displaystyle
S_k=\sum_{k=1}^{\infty}
\left[\frac{(-2)}{9^{k+1}}\right]
=\frac{-2}{99} $$
$\text{geometric series}$
$$\sum_{k=1}^{\infty}ar^{k-1}=\frac{a}{(1-r)},
\ \ \left| r \right|< 1$$
$$\displaystyle S_k=-\frac{2}{81}\sum_{k=1}^{\infty}
\left(\frac{1}{9}\right)^{k-1}
=\frac{1}{1-\dfrac{1}{9}}
=-\frac{2}{81}\cdot\frac{9}{8}=-\frac{1}{36}$$
$\tiny{206.10.3.71}$
☕
 
Last edited:
  • #4
$\text{Evaluate }$
$$\displaystyle
S_k=\sum_{k=1}^{\infty}
\left[\frac{(-2)}{9^{k+1}}\right]
=\frac{-1}{3} $$
$\text{geometric series}$
$$\sum_{k=1}^{\infty}ar^{k-1}=\frac{a}{(1-r)},
\ \ \left| r \right|< 1$$
$$\displaystyle S_k=-\frac{2}{81}\sum_{k=1}^{\infty}
\left(\frac{1}{9}\right)^{k-1}
=\frac{1}{1-\dfrac{1}{9}}
=-\frac{2}{81}\cdot\frac{9}{8}=-\frac{1}{36}$$
$\tiny{206.10.3.75}$
☕
 

FAQ: What is the answer after convergence in TI-Nspire CX CAS?

What is the "method after convergence" in scientific research?

The "method after convergence" refers to the process of analyzing and interpreting data after a scientific experiment has been completed and the data has been collected. It involves using statistical tests and other methods to draw conclusions from the data and make predictions about the phenomenon being studied.

Why is the method after convergence important in scientific research?

The method after convergence is important because it allows scientists to draw meaningful and accurate conclusions from their research. It helps to ensure that the results of an experiment are valid and reliable, and that any conclusions drawn from the data are supported by evidence.

What types of statistical tests are commonly used in the method after convergence?

There are many different types of statistical tests that may be used in the method after convergence, depending on the type of data being analyzed and the specific research question being addressed. Some common examples include t-tests, ANOVA, chi-square tests, and regression analysis.

How do scientists determine if their results are statistically significant?

Scientists determine whether their results are statistically significant by comparing the observed data to what would be expected by chance. This is usually done using a p-value, which indicates the likelihood of obtaining the observed results if there is no real effect. If the p-value is below a certain threshold (typically 0.05), the results are considered statistically significant.

Is the method after convergence the final step in scientific research?

No, the method after convergence is not necessarily the final step in scientific research. After the data has been analyzed and conclusions have been drawn, scientists may use their findings to develop new hypotheses and design further experiments to continue their research.

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