Questions tagged [distributions]
A distribution is a mathematical description of probabilities or frequencies.
7,922
questions
496
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14answers
199k views
What is the intuition behind beta distribution?
Disclaimer: I'm not a statistician but a software engineer. Most of my knowledge in statistics comes from self-education, thus I still have many gaps in understanding concepts that may seem trivial ...
210
votes
4answers
298k views
When (and why) should you take the log of a distribution (of numbers)?
Say I have some historical data e.g., past stock prices, airline ticket price fluctuations, past financial data of the company...
Now someone (or some formula) comes along and says "let's take/use ...
188
votes
8answers
387k views
In linear regression, when is it appropriate to use the log of an independent variable instead of the actual values?
Am I looking for a better behaved distribution for the independent variable in question, or to reduce the effect of outliers, or something else?
167
votes
2answers
224k views
How to determine which distribution fits my data best?
I have a dataset and would like to figure out which distribution fits my data best.
I used the fitdistr() function to estimate the necessary parameters to ...
164
votes
6answers
95k views
Can a probability distribution value exceeding 1 be OK?
On the Wikipedia page about naive Bayes classifiers, there is this line:
$p(\mathrm{height}|\mathrm{male}) = 1.5789$ (A probability distribution over 1 is OK. It is the area under the bell curve ...
140
votes
3answers
197k views
Help me understand Bayesian prior and posterior distributions
In a group of students, there are 2 out of 18 that are left-handed. Find the posterior distribution of left-handed students in the population assuming uninformative prior. Summarize the results. ...
124
votes
10answers
84k views
Why does the Cauchy distribution have no mean?
From the distribution density function we could identify a mean (=0) for Cauchy distribution just like the graph below shows. But why do we say Cauchy distribution has no mean?
114
votes
4answers
33k views
Assessing approximate distribution of data based on a histogram
Suppose I want to see whether my data is exponential based on a histogram (i.e. skewed to the right).
Depending on how I group or bin the data, I can get wildly different histograms.
One set of ...
94
votes
10answers
65k views
Understanding “variance” intuitively
What is the cleanest, easiest way to explain someone the concept of variance? What does it intuitively mean? If one is to explain this to their child how would one go about it?
It's a concept that I ...
87
votes
5answers
209k views
Relationship between poisson and exponential distribution
The waiting times for poisson distribution is an exponential distribution with parameter lambda. But I don't understand it. Poisson models the number of arrivals per unit of time for example. How is ...
82
votes
7answers
137k views
Calculating the parameters of a Beta distribution using the mean and variance
How can I calculate the $\alpha$ and $\beta$ parameters for a Beta distribution if I know the mean and variance that I want the distribution to have? Examples of an R command to do this would be most ...
75
votes
4answers
10k views
What's so 'moment' about 'moments' of a probability distribution?
I KNOW what moments are and how to calculate them and how to use the moment generating function for getting higher order moments. Yes, I know the math.
Now that I need to get my statistics knowledge ...
65
votes
3answers
74k views
How is the minimum of a set of IID random variables distributed?
If $X_1, ..., X_n$ are independent identically-distributed random variables, what can be said about the distribution of $\min(X_1, ..., X_n)$ in general?
63
votes
5answers
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Intuition on the Kullback-Leibler (KL) Divergence
I have learned about the intuition behind the KL Divergence as how much a model distribution function differs from the theoretical/true distribution of the data. The source I am reading goes on to say ...
53
votes
4answers
39k views
How to identify a bimodal distribution?
I understand that once we plot the values as a chart, we can identify a bimodal distribution by observing the twin-peaks, but how does one find it programmatically? (I am looking for an algorithm.)
52
votes
6answers
38k views
How can a distribution have infinite mean and variance?
It would be appreciated if the following examples could be given:
A distribution with infinite mean and infinite variance.
A distribution with infinite mean and finite variance.
A distribution with ...
asked Mar 27 '14 at 4:49
user1205901 - Reinstate Monica
10.6k21 gold badges70 silver badges145 bronze badges
50
votes
6answers
238k views
How to perform a test using R to see if data follows normal distribution
I have a data set with following structure:
a word | number of occurrence of a word in a document | a document id
How can I perform a test for normal ...
50
votes
5answers
57k views
If the t-test and the ANOVA for two groups are equivalent, why aren't their assumptions equivalent?
I'm sure I've got this completely wrapped round my head, but I just can't figure it out.
The t-test compares two normal distributions using the Z distribution. That's why there's an assumption of ...
49
votes
5answers
15k views
What is the advantages of Wasserstein metric compared to Kullback-Leibler divergence?
What is the practical difference between Wasserstein metric and Kullback-Leibler divergence? Wasserstein metric is also referred to as Earth mover's distance.
From Wikipedia:
Wasserstein (or ...
49
votes
6answers
13k views
Motivation for Kolmogorov distance between distributions
There are many ways to measure how similar two probability distributions are. Among methods which are popular (in different circles) are:
the Kolmogorov distance: the sup-distance between the ...
48
votes
13answers
142k views
Mean absolute deviation vs. standard deviation
In the text book "New Comprehensive Mathematics for O Level" by Greer (1983), I see averaged deviation calculated like this:
Sum up absolute differences between single values and the mean. Then
...
46
votes
3answers
16k views
Which has the heavier tail, lognormal or gamma?
(This is based on a question that just came to me via email; I've added some context from a previous brief conversation with the same person.)
Last year I was told that the gamma distribution is ...
46
votes
3answers
7k views
How does saddlepoint approximation work?
How does saddlepoint approximation work? What sort of problem is it good for?
(Feel free to use a particular example or examples by way of illustration)
Are there any drawbacks, difficulties, things ...
45
votes
3answers
18k views
Empirical relationship between mean, median and mode
For a unimodal distribution that is moderately skewed, we have the following empirical relationship between the mean, median and mode:
$$
\text{(Mean - Mode)}\sim 3\,\text{(Mean - Median)}
$$
How ...
45
votes
4answers
11k views
Kullback–Leibler vs Kolmogorov-Smirnov distance
I can see that there are a lot of formal differences between Kullback–Leibler vs Kolmogorov-Smirnov distance measures.
However, both are used to measure the distance between distributions.
Is there a ...
44
votes
5answers
23k views
Generic sum of Gamma random variables
I have read that the sum of Gamma random variables with the same scale parameter is another Gamma random variable. I've also seen the paper by Moschopoulos describing a method for the summation of a ...
44
votes
5answers
26k views
Probability distribution for different probabilities
If I wanted to get the probability of 9 successes in 16 trials with each trial having a probability of 0.6 I could use a binomial distribution. What could I use if each of the 16 trials has a ...
44
votes
8answers
58k views
How can I test if given samples are taken from a Poisson distribution?
I know of normality tests, but how do I test for "Poisson-ness"?
I have sample of ~1000 non-negative integers, which I suspect are taken from a Poisson distribution, and I would like to test that.
43
votes
4answers
22k views
Approximate order statistics for normal random variables
Are there well known formulas for the order statistics of certain random distributions? Particularly the first and last order statistics of a normal
random variable, but a more general answer would ...
43
votes
5answers
4k views
Fake uniform random numbers: More evenly distributed than true uniform data
I'm looking for a way to generate random numbers that appear to be uniform distributed -- and every test will show them to be uniform -- except that they are more evenly distributed than true uniform ...
42
votes
2answers
29k views
Understanding the parameters inside the Negative Binomial Distribution
I was trying to fit my data into various models and figured out that the fitdistr function from library MASS of ...
40
votes
2answers
50k views
Test for bimodal distribution
I wonder if there is any statistical test to "test" the significance of a bimodal distribution. I mean, How much my data meets the bimodal distribution or not? If so, is there any test in the R ...
39
votes
10answers
8k views
Why are survival times assumed to be exponentially distributed?
I am learning survival analysis from this post on UCLA IDRE and got tripped up at section 1.2.1. The tutorial says:
... if the survival times were known to be exponentially distributed, then the ...
39
votes
9answers
11k views
How can I efficiently model the sum of Bernoulli random variables?
I am modeling a random variable ($Y$) which is the sum of some ~15-40k independent Bernoulli random variables ($X_i$), each with a different success probability ($p_i$). Formally, $Y=\sum X_i$ where $\...
38
votes
2answers
39k views
What exactly is the alpha in the Dirichlet distribution?
I'm fairly new to Bayesian statistics and I came across a corrected correlation measure, SparCC, that uses the Dirichlet process in the backend of it's algorithm. I have been trying to go through the ...
38
votes
5answers
56k views
How does linear regression use the normal distribution?
In linear regression, each predicted value is assumed to have been picked from a normal distribution of possible values. See below.
But why is each predicted value assumed to have come from a normal ...
37
votes
4answers
2k views
Intuitive explanation of Kolmogorov Smirnov Test
What is the cleanest, easiest way to explain someone the concept of Kolmogorov Smirnov Test? What does it intuitively mean?
It's a concept that I have difficulty in articulating - especially when ...
37
votes
2answers
4k views
Why should we use t errors instead of normal errors?
In this blog post by Andrew Gelman, there is the following passage:
The Bayesian models of 50 years ago seem hopelessly simple (except, of
course, for simple problems), and I expect the Bayesian ...
37
votes
3answers
29k views
Why is a likelihood-ratio test distributed chi-squared?
Why is the test statistic of a likelihood ratio test distributed chi-squared?
$2(\ln \text{ L}_{\rm alt\ model} - \ln \text{ L}_{\rm null\ model} ) \sim \chi^{2}_{df_{\rm alt}-df_{\rm null}}$
36
votes
6answers
3k views
How can I analytically prove that randomly dividing an amount results in an exponential distribution (of e.g. income and wealth)?
In this current article in SCIENCE the following is being proposed:
Suppose you randomly divide 500 million in income among 10,000
people. There's only one way to give everyone an equal, 50,000 ...
36
votes
3answers
21k views
Why is RSS distributed chi square times n-p?
I would like to understand why, under the OLS model, the RSS (residual sum of squares) is distributed $$\chi^2\cdot (n-p)$$ ($p$ being the number of parameters in the model, $n$ the number of ...
35
votes
5answers
14k views
Is there an explanation for why there are so many natural phenomena that follow normal distribution?
I think this is a fascinating topic and I do not fully understand it. What law of physics makes so that so many natural phenomena have normal distribution? It would seem more intuitive that they would ...
35
votes
3answers
53k views
Help me understand the quantile (inverse CDF) function
I am reading about the quantile function, but it is not clear to me. Could you provide a more intuitive explanation than the one provided below?
Since the cdf $F$ is a monotonically increasing ...
35
votes
2answers
118k views
What is the difference between the Shapiro-Wilk test of normality and the Kolmogorov-Smirnov test of normality?
What is the difference between the Shapiro-Wilk test of normality and the Kolmogorov-Smirnov test of normality? When will results from these two methods differ?
34
votes
5answers
11k views
Intuitive explanation of convergence in distribution and convergence in probability
What is the intuitive difference between a random variable converging in probability versus a random variable converging in distribution?
I've read numerous definitions and mathematical equations, ...
34
votes
7answers
32k views
What is normality?
In many different statistical methods there is an "assumption of normality". What is "normality" and how do I know if there is normality?
34
votes
4answers
64k views
How is Poisson distribution different to normal distribution?
I have generated a vector which has a Poisson distribution, as follows:
x = rpois(1000,10)
If I make a histogram using hist(x)...
33
votes
3answers
5k views
I know the 95% confidence interval for ln(x), do I also know the 95% confidence interval of x?
Suppose the 95% confidence interval for $\ln(x)$ is $[l,u]$. Is it true that the 95% CI for $x$ is simply $[e^l, e^u]$?
I have the intuition the answer is yes, because $\ln$ is a continuous function. ...
33
votes
6answers
4k views
Can somebody offer an example of a unimodal distribution which has a skewness of zero but which is not symmetrical?
In May 2010 Wikipedia user Mcorazao added a sentence to the skewness article that "A zero value indicates that the values are relatively evenly distributed on both sides of the mean, typically but not ...
33
votes
3answers
25k views
What distribution does my data follow?
Let us say that I have 1000 components and I have been collecting data on how many times these log a failure and each time they logged a failure, I am also keeping track of how long it took my team to ...
