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4
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1answer
97 views

Confidence intervals based on the CLT: ever useful?

Suppose, for concreteness, that I am trying to estimate the mean of a population using a random sample of size $N$. Many elementary books discuss forming a confidence interval for the population mean ...
1
vote
1answer
50 views

Use the Central Limit Theorem to calculate the approx probabilities of Gamma RVs?

If $X_i, i=1,...,$ are independent, identically distributed $\operatorname{N}(0,1)$ random variables, and $Y_i = X_i^2$ are independent $\operatorname{Gamma}(\frac{1}{2},\frac{1}{2})$ RVs, use the ...
1
vote
3answers
217 views

What's the distribution of $\bar{X}^{-1}$?

What's the distribution of $\bar{X}^{-1}$ with X being a continuous iid random variable that is uniformly distributed? Can I use the CLT here?
1
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0answers
32 views

Can the proof of the central limit theorem be expressed as the limit of a convolution with an operator

The central limit theorem, as I understand it (engineer, non-statistician), says that the distribution comprised of means of some other reasonably behaved distributions converges to a normal ...
8
votes
1answer
288 views

Central limit theorem and the law of large numbers

I have a very beginner's question regarding the Central Limit Theorem (CLT): I am aware that the CLT states that a mean of i.i.d. random variables is approximately normal distributed (for $n \to ...
0
votes
1answer
71 views

Berry-Esseen theorem

In the Berry-Essen theorem, why is the standard normal distribution used in the context of the closedness of two distributions? Why can't we use the general normal distribution where will things will ...
6
votes
1answer
133 views

Evaluate $\lim_{n \to \infty} \sum_{j=0}^{n}{{j+n-1} \choose j}\frac{1}{2^{j+n}}$

Using the Central Limit Theorem , Evaluate $$\lim_{n \to \infty} \sum_{j=0}^{n}{{j+n-1} \choose j}\frac{1}{2^{j+n}}$$ My solution: Let $\{X_n\}$ be a sequence of iid R.V's each having ...
1
vote
1answer
78 views

Find the limiting distribution of $Z_n$

Let $X_1,X_2, \dots$ be iid RVs with mean $\alpha$ and variance $\sigma^2$ , and let $Y_1,Y_2, \dots$ be iid RVs with mean $\beta(\neq 0)$ and variance $\tau^2$. Find the limiting distribution of ...
4
votes
1answer
289 views

Central limit theorem for sample medians

If I calculate the median of a sufficiently large number of observations drawn from the same distribution, does the central limit theorem state that the distribution of medians will approximate a ...
2
votes
0answers
72 views

Can we approximate the distribution of S?

I want to understand how the sampling distribution of the whole covariance matrix behaves for large $n$. I am trying to use the delta method and multivariate CLT. I am trying to show that when the ...
1
vote
1answer
293 views

When to use Central Limit Theorem?

Is the central-limit-theorem true for all distributions? For what sample size is it true (what is meant with "large")?
1
vote
0answers
86 views

Empirical coverage probabilities of confidence intervals

Can someone tell me how the type of distribution is related to an empirical coverage probability? (for some distributions the Central-limit-theorem seems to be more easily satisfied)
0
votes
2answers
130 views

Central limit theorem with unknown variance

In my experiment I compute the average Latency of operations per second. Now, I would like to define N, i.e: how many times do I need to run my experiment to compute a close to real average latency. ...
8
votes
1answer
255 views

Does the multivariate Central Limit Theorem (CLT) hold when variables exhibit perfect contemporaneous dependence?

The title sums up my question, but for clarity consider the following simple example. Let $X_i \overset{iid}{\backsim} \mathcal{N}(0, 1)$, $i = 1, ..., n$. Define: \begin{equation} S_n = \frac{1}{n} ...
0
votes
0answers
37 views

Central Limit Theorem [duplicate]

Possible Duplicate: What intuitive explanation is there for the central limit theorem? I am in an introductory statistics course, and I am having trouble understanding the Central Limit ...
2
votes
1answer
54 views

A limit theorem for non-independent variables

Let $X_n$ be a sequence of identically distributed (e.g., binomial $B(1,1/2)$) random variables which are not independent (say, for any $n$ and $m$, $corr(X_n,X_m)=c$). What can be said about the ...
2
votes
0answers
69 views

Is it OK to use the CLT to create a normal distribution where there is none?

I have some data that looks like this: Procrastinator has come up with one good suggestion for how to test hypotheses under this distribution, but it relies on some guesswork to fit constants. I ...
6
votes
3answers
791 views

Consider the sum of $n$ uniform distributions on $[0,1]$, or $Z_n$. Why does the cusp in the PDF of $Z_n$ disappear for $n \geq 3$?

I've been wondering about this one for a while; I find it a little weird how abruptly it happens. Basically, why do we need just three uniforms for $Z_n$ to smooth out like it does? And why does the ...
1
vote
1answer
87 views

Weak convergence of an empirical process. Demonstration

The empirical process $B_n(x) = \sqrt{n}(F_n(x) − F(x))$ converges weakly to a zero-mean Gaussian process, $B$, with covariance function: $\mbox{cov}(B(x), B(y)) = F(\min\{x, y\}) − F(x)F(y)$. How I ...
14
votes
4answers
454 views

Where does $\sqrt{n}$ come from in central limit theorem (CLT)?

A very simple version of central limited theorem as below $$ \sqrt{n}\bigg(\bigg(\frac{1}{n}\sum_{i=1}^n X_i\bigg) - \mu\bigg)\ \xrightarrow{d}\ \mathcal{N}(0,\;\sigma^2) $$ which is Lindeberg–Lévy ...
0
votes
2answers
101 views

Cental limit theorem for average of iid variables

The Wikipedia entry on the CLT states at one point: "For fixed large $n$ one can also say that the distribution of $S_n$ is close to the normal distribution with mean $\mu$ and variance ...
9
votes
1answer
252 views

“Central limit theorem” for weighted sum of correlated random variables

I'm reading a paper which claims that $$\hat{X}_k=\frac{1}{\sqrt{N}}\sum_{j=0}^{N-1}X_je^{-i2\pi kj/N},$$ (i.e. the Discrete Fourier Transform, DFT) by the C.L.T. tends to a (complex) gaussian random ...
2
votes
4answers
1k views

Which test to choose when the results from t-test and Wilcoxon test are different?

I have a sample of 48. According to the central limit theorem, I may consider means of every continuous variable in my sample to have a normal distribution. However, one variable has a mean of 14 +/- ...
5
votes
3answers
215 views

Information theoretic central limit theorem

The simplest form of the information theoretic CLT is the following: Let $X_1, X_2,\dots$ be iid with mean $0$ and variance $1$. Let $f_n$ be the density of the normalized sum $\frac{\sum_{i=1}^n ...
9
votes
1answer
474 views

Error in normal approximation to a uniform sum distribution

One naive method for approximating a normal distribution is to add together perhaps $100$ IID random variables uniformly distributed on $[0,1]$, then recenter and rescale, relying on the Central Limit ...
0
votes
2answers
180 views

How/Why does resampling from “any” distribution lead to a normal distribution?

I was performing some Monte-Carlos on historical data and irrespective of the distribution of the data I would always get a normal distribution owing to resampling with replacement. That made it easy ...
14
votes
4answers
268 views

The operation of chance in a deterministic world

In Steven Pinker's book Better Angels of Our Nature, he notes that Probability is a matter of perspective. Viewed at sufficiently close range, individual events have determinate causes. Even a ...
4
votes
3answers
187 views

CLT and stable distributions

I have a few questions about generalizations of the CLT and stable distributions. I'm trying to correct my understanding and make it precise. Please forgive my naivete, I am not a professional ...
0
votes
1answer
154 views

Accuracy in approximation with central limit theorem

I have set of random values with the same distribution $y_1, \ldots, y_N$ $$T = \frac{1}{N}\sum_{j = 1}^{N} y_j$$ I want to find the confidence interval for the mathematical expectation $E(Y)$ ...
4
votes
1answer
181 views

Proofs of the central limit theroem

I know there are different versions of the central limit theorem and consequently there are different proofs of it. The one I am most familiar with is in the context of a sequence of identically ...
0
votes
1answer
265 views

Whether to use nonparametric tests to compare two groups when sample size is large but assumptions are violated

I have a data set that has 600 observations divided in two groups. I am going to compare the central tendencies (e.g., the means) of these two groups. However, there are violations of classical ...
20
votes
3answers
1k views

Why law of large numbers does not apply in the case of Apple share price?

Here is the article in NY times called "Apple confronts the law of large numbers". It tries to explain Apple share price rise using law of large numbers. What statistical (or mathematical) errors does ...
2
votes
3answers
2k views

Central limit theorem versus law of large numbers

The central limit theorem states that the mean of i.i.d. variables, as $N$ goes to infinity, becomes normally distributed. This raises two questions: Can we deduce from this the law of large ...
2
votes
1answer
445 views

Understanding central limit theorem

What is wrong with the following sentence: The Central Limit Theorem implies that, as the sample size grows, the error distribution approaches normality. Am I correct by saying that it should ...
2
votes
2answers
87 views

Assess density of a function in non-closed form

I am working with Rice's Mathematical Statistics and Data Analysis and on page 179 it introduces Monte Carlo integration. This question is a smallish revision based on comments from @Iterator (in R ...
10
votes
3answers
225 views

How many of the biggest terms in $\sum_{i=1}^N |X_i|$ add up to half the total?

Consider $\sum_{i=1}^N |X_i|$ where $X_1, \ldots, X_N$ are i.i.d. and the CLT holds. How many of the biggest terms add up to half the total sum ? For example, 10 + 9 + 8 $\approx$ (10 + 9 + 8 $\dots$ ...
0
votes
2answers
409 views

How to demonstrate failure of CLT in R?

I was assigned to demonstrate the Central Limit Theorem (CLT) in R in my statistics class. I already made some progress with simulation using simple.sim in R. I want to prepare 3 examples of the CLT ...
6
votes
2answers
2k views

How to test for differences between two group means when the data is not normally distributed?

I'll eliminate all the biological details and experiments and quote just the problem at hand and what I have done statistically. I would like to know if its right, and if not, how to proceed. If the ...
5
votes
2answers
333 views

Putting a confidence interval on the mean of a very rare event

I'm simulating an extremely rare event (the detection of weighted photon packets in a highly absorbing material). For example, I may simulate the transmission of 1e9 photons and only detect 10 of them ...
2
votes
1answer
642 views

Central limit theorem for sample quantiles

I am reading Ruppert's Statistics and Data Analysis for Financial Engineering, which contains the following theorem: Let $Y_1$, $...$ , $Y_n$ be an i.i.d. sample with a CDF $F$. Suppose that ...
4
votes
1answer
373 views

Random walks in multinomial case

Model: A vector $X=(X_1, X_2, X_3)$ that follows a trinomial distribution with parameters $p=1/3$ and $n$. (I have a coin with three sides $S1$, $S2$, $S3$). I flip the coin $n$ times. The coin has ...
4
votes
1answer
135 views

Does the Central Limit Theorem allow one to create confidence intervals from a web traffic dataset?

I'm a journalist turned developer who hobbies in APIs and analysis of web traffic. I've always enjoyed learning about stats but as I learned, I learned that I have misapplied some basic concepts in ...
4
votes
1answer
365 views

Conditions for Central Limit Theorem for dependent sequences

Cumbersome technical assumptions (e.g., mixing properties) are used in the literature to prove Central Limit Theorems for dependent sequences. I sketched a proof that does not require any of these ...
1
vote
1answer
499 views

Summing normal instead of beta distributions, consequences for the density function of the sum?

Background: I've modeled a project effort prediction as a Google Spreadsheet template. Details of the Model: http://sites.google.com/site/effortprediction/methodology .Google Spreadsheet does not ...
3
votes
2answers
283 views

Central limit theorem for sum from varied distributions

The central limit theorem as I am familiar with it applies to the limiting (rescaled) distribution of $n$ convolutions of a single probability distribution as $n$ goes to infinity, or equivalently, to ...
6
votes
1answer
163 views

Estimate the nearest of N random points in a box in E^d?

I have N uniform-random points $p_j$ in a box in $E^d$, $a_i \le x_i \le b_i$, and want to estimate the expected distance of the point nearest the origin in $L_q$: $\quad$ nearest( points $p_j$, box ...
6
votes
1answer
230 views

Limiting distribution of a squared sum of random variables

Let $S_n = \frac{1}{n}\sum_{i=1}^n X_i$, and $T_n = \frac{1}{n}\sum_{j=1}^nY_i$, where The $X_i$ are iid, the $Y_i$ are iid (with a different law) $X_i$, and $Y_i$ are dependent For $i\neq j$, ...
10
votes
3answers
630 views

What is the sum of squared t variates?

Let $t_i$ be drawn i.i.d from a Student t distribution with $n$ degrees of freedom, for moderately sized $n$ (say less than 100). Define $$T = \sum_{1\le i \le k} t_i^2$$ Is $T$ distributed nearly as ...
2
votes
1answer
248 views

Central Limit Theorem Tails

I'm trying to compute some p-values for samples from a distribution of sums of ~1000 random variables. The exact distribution of these random variables isn't known, but I have empirical estimates that ...
13
votes
2answers
382 views

How to know which probability distribution to expect?

Currently I am analyzing social networks (not virtual) and I am observing the connections between people. If a person would choose another person to connect with randomly, the number of connections ...

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