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8129 | 2 | null | 8089 | 7 | null | Recall (in combination with precision) is generally used in areas where one is primarily interested in finding the Positives. An example for such an area is e.g. Performance Marketing or (as already suggested by ch'ls link) the area of Information Retrieval.
So:
If you are primarily interested in finding the negatives,... | null | CC BY-SA 2.5 | null | 2011-03-10T14:38:23.600 | 2011-03-10T14:51:01.483 | 2011-03-10T14:51:01.483 | 264 | 264 | null |
8130 | 1 | null | null | 11 | 783 | I am a software designer by trade and I am working on a project for a client, and I would like to make sure that my analysis is statistically sound.
Consider the following: We have n advertisements (n < 10), and we simply want to know which ad performs the best. Our ad server will randomly serve one of these ads. Su... | Sample size required to determine which of a set of advertisements has the highest click through rate | CC BY-SA 2.5 | null | 2011-03-10T14:52:20.337 | 2011-03-15T02:41:01.220 | 2011-03-11T08:06:25.987 | 183 | 3658 | [
"anova",
"sample-size",
"t-test",
"rule-of-thumb"
] |
8131 | 2 | null | 8106 | 37 | null | That the author has forced someone as thoughtful as you to have ask a question like this is compelling illustration of why the practice -- still way too common -- of confining reporting of regression model results to a table like this is so unacceptable.
- You can, as pointed out, try to transform the logit coefficie... | null | CC BY-SA 3.0 | null | 2011-03-10T15:03:04.673 | 2017-03-02T09:41:19.690 | 2017-03-02T09:41:19.690 | 138830 | 11954 | null |
8132 | 2 | null | 8106 | 6 | null | Let me just stress the importance of what rolando2 and dmk38 both noted: significance is commonly misread, and there is a high risk of that happening with that tabular presentation of results.
Paul Schrodt [recently](http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1661045) offered a nice description of the issue:
> ... | null | CC BY-SA 2.5 | null | 2011-03-10T15:34:15.527 | 2011-03-10T15:34:15.527 | null | null | 3582 | null |
8133 | 1 | null | null | 4 | 1177 | I read from a textbook that Gauss-Newton regression is also called 'artificial regression'. Please give me an example, how does it work? And what's the relation with Newton's method? Thank you.
| Intuitive explanation of Gauss-Newton regression | CC BY-SA 2.5 | null | 2011-03-10T15:41:13.017 | 2011-03-11T04:05:28.043 | 2011-03-11T04:05:28.043 | 919 | 3525 | [
"econometrics",
"nonlinear-regression"
] |
8134 | 2 | null | 8096 | 3 | null |
- Obtain the five-number summary for your sample.
- Calculate the standard error for your sample.
- Select a level of confidence, based on the z-score.
- Calculate the lower and upper bound of the interval.
If you are doing this by hand, use the formulae provided by any statistics handbook, such as Agresti and Fi... | null | CC BY-SA 3.0 | null | 2011-03-10T15:50:11.723 | 2014-08-25T17:05:57.230 | 2014-08-25T17:05:57.230 | 25292 | 3582 | null |
8135 | 1 | null | null | 11 | 8263 | I am running a large OLS regression where all the independent variables (around 400) are dummy variables. If all are included, there is perfect multicollinearity (the dummy variable trap), so I have to omit one of the variables before running the regression.
My first question is, which variable should be omitted? I hav... | Dummy variable trap issues | CC BY-SA 2.5 | null | 2011-03-10T16:33:50.490 | 2014-12-03T18:10:49.713 | null | null | 1090 | [
"categorical-data"
] |
8136 | 2 | null | 8052 | 4 | null | Shouldn't you favour [Fisher's exact test](http://en.wikipedia.org/wiki/Fisher%27s_exact_test) on a 2x2 contingency table? The advantages of the Chi-squared test would be preserved, with the additional advantages of an exact test. Based on a few handbook readings, I believe that Fisher's exact test is recommended chief... | null | CC BY-SA 2.5 | null | 2011-03-10T17:37:32.670 | 2011-03-10T17:37:32.670 | null | null | 3582 | null |
8137 | 1 | 8235 | null | 7 | 36494 | I have a boxplot output in R using ggplot2:
```
p <- ggplot(data, aes(y = age, x = group))
p <- p + geom_boxplot()
p <- p + scale_x_discrete(name= "Group",)
p <- p + scale_y_continuous(name= "Age")
p
```
I need to add horisontal lines like on common boxplot (and... | How to add horizontal lines to ggplot2 boxplot? | CC BY-SA 2.5 | null | 2011-03-10T17:52:10.160 | 2015-11-17T03:45:07.367 | null | null | 3376 | [
"r",
"boxplot",
"ggplot2"
] |
8139 | 2 | null | 7982 | 3 | null | Assuming data are considered missing completely at random (cf. @whuber's comment), using an ensemble learning technique as described in the following paper might be interesting to try:
>
Polikar, R. et al. (2010).
Learn++.MF: A random subspace
approach for the missing feature
problem. Pattern Recognition,
43(1... | null | CC BY-SA 2.5 | null | 2011-03-10T21:29:22.377 | 2011-03-11T07:37:13.680 | 2011-03-11T07:37:13.680 | 930 | 930 | null |
8140 | 2 | null | 7982 | 1 | null | If the features in the subset are random you can still impute values. However, if you have that much missing data, I would think twice about whether or not you really have enough valid data to do any kind of analysis.
The multiple imputation FAQ page ---->
[http://www.stat.psu.edu/~jls/mifaq.html](http://www.stat.psu.e... | null | CC BY-SA 2.5 | null | 2011-03-10T21:50:11.123 | 2011-03-10T21:50:11.123 | null | null | 3489 | null |
8141 | 2 | null | 8135 | 4 | null | James, first of all why regression analysis, but not ANOVA (there are many specialists in this kind of analysis that could help you)? The pros for ANOVA is that all you actually interested in are differences in the means of different groups described by combinations of dummy variables (unique categories, or profiles). ... | null | CC BY-SA 2.5 | null | 2011-03-10T22:14:10.927 | 2011-03-10T22:14:10.927 | null | null | 2645 | null |
8142 | 1 | null | null | 2 | 194 | Is there an analytic form for the Hellinger distance between von Mises distributions?
| Is there an analytic form for the Hellinger distance between von Mises distributions? | CC BY-SA 2.5 | null | 2011-03-11T00:45:27.277 | 2021-11-11T03:00:46.740 | 2021-11-11T03:00:46.740 | 11887 | 3595 | [
"distributions",
"distance-functions",
"von-mises-distribution"
] |
8143 | 1 | null | null | 1 | 2070 | If, for example, I have `0011` as a set of known bits $x$, how do I determine the probability that a sequence of randomly generated bits is equal to $x$?
Thanks for the help! I'm sure this is a dumb question, but probability has always been my weakness (which my algorithms class is highlighting!).
EDIT: This is what I ... | How to calculate the probability of a random sequence of bits being a specific sequence? | CC BY-SA 2.5 | null | 2011-03-11T03:01:15.340 | 2011-03-11T16:27:33.847 | 2011-03-11T16:27:33.847 | null | null | [
"probability"
] |
8144 | 2 | null | 7676 | 1 | null | While you didn't say anything about the actual condtions (experimental treatment), think of the following example: you measure the weight of 40 people at some point during the day, then set them the task to drink (as much as possible of) 5 quarts of water (experimental manipulation), and them weigh them again (hinting ... | null | CC BY-SA 2.5 | null | 2011-03-11T05:25:46.947 | 2011-03-11T05:25:46.947 | null | null | 3667 | null |
8145 | 1 | 8149 | null | 11 | 410 | I solve Rubik's cubes as a hobby. I record the time it took me to solve the cube using some software, and so now I have data from thousands of solves. The data is basically a long list of numbers representing the time each sequential solve took (e.g. 22.11, 20.66, 21.00, 18.74, ...)
The time it takes me to solve the ... | How do you tell whether good performances come in streaks? | CC BY-SA 2.5 | null | 2011-03-11T09:46:09.730 | 2020-11-29T13:42:14.743 | 2020-11-29T11:52:37.083 | 11887 | 2665 | [
"time-series",
"probability"
] |
8146 | 1 | null | null | 1 | 456 | Does any body know of a Java implementation of McNemar's Test?
| McNemar's test implementation in Java | CC BY-SA 3.0 | null | 2011-03-11T10:25:28.287 | 2012-12-28T18:06:28.233 | 2012-12-28T18:06:28.233 | 17662 | null | [
"java"
] |
8147 | 1 | null | null | 1 | 265 | I have almost the same question as:
[How can I efficiently model the sum of Bernoulli random variables?](https://stats.stackexchange.com/questions/5347/how-can-i-efficiently-model-the-sum-of-bernoulli-random-variables)
But:
(1) The number of random variables for summation is ~ N=20 (case 1) or N=90 (case 2).
(2) $p_i$ ... | How can I efficiently approximate the sum of Bernoulli random variables for any number of summands in partial sum? | CC BY-SA 4.0 | null | 2011-03-11T10:29:28.877 | 2023-04-29T06:27:37.467 | 2023-04-29T06:27:37.467 | 362671 | 3670 | [
"distributions",
"modeling"
] |
8148 | 1 | null | null | 18 | 17700 | Apologies for the rudimentary question, I am new to this form of analysis and have a very limited understanding of the principles so far.
I was just wondering if many of the parametric assumptions for multivariate/univariate tests apply for Cluster analysis? Many of the sources of information I have read regarding clus... | Assumptions of cluster analysis | CC BY-SA 2.5 | null | 2011-03-11T10:34:36.383 | 2011-06-02T10:51:50.320 | 2011-03-11T13:26:42.053 | null | 3619 | [
"clustering",
"assumptions"
] |
8149 | 2 | null | 8145 | 8 | null | The [Wald-Wolfowitz Runs Test](http://en.wikipedia.org/wiki/Wald%E2%80%93Wolfowitz_runs_test) seems to be a possible candidate, where a "run" is what you called a "streak". It requires dichotomous data, so you'd have to label each solve as "bad" vs. "good" according to some threshold - like the median time as you sugge... | null | CC BY-SA 2.5 | null | 2011-03-11T10:41:21.237 | 2011-03-11T14:42:16.717 | 2011-03-11T14:42:16.717 | 1909 | 1909 | null |
8150 | 1 | null | null | 3 | 228 | I have a prospective study with no data about estimated results, that could be used to get required sample size. Data looks like this:
```
caseID;groupID;value,result
1;1;12.3;0
2;1;15.6;1
3;2;11.3;0
4;2;13.4;1
...
```
Is it possible to determine how much observations should be made to complete the study after adding... | Dynamic estimation of required sample size in R | CC BY-SA 2.5 | null | 2011-03-11T10:44:36.757 | 2011-03-15T19:46:01.623 | 2011-03-15T19:46:01.623 | 3376 | 3376 | [
"r",
"estimation",
"sample-size"
] |
8151 | 1 | null | null | 4 | 5806 | Is there a way to easily create factors based on quantiles of selected variables in a dataframe? Say, in a datatset D, I have variables V1 to V10, which are all numeric. I would like to create dummies for V7 to V10 based on their respective quantiles.
| Quantile transformation in R | CC BY-SA 2.5 | null | 2011-03-11T11:42:59.117 | 2016-08-13T17:27:56.023 | 2016-08-13T17:27:56.023 | 919 | 3671 | [
"r",
"categorical-data"
] |
8152 | 1 | 8153 | null | 2 | 1536 | I have a few questions regarding multiple imputation for nested data.
Context: I have repeated measures (4 times) from a survey and these are clustered in workplaces (205 workplaces). There are about 180 items on this survey.
q1. Is it possible to take both the repeated measures and the workplace clustering into consi... | Multiple imputation for clustered data | CC BY-SA 2.5 | null | 2011-03-11T12:06:54.577 | 2022-11-28T05:33:13.907 | 2011-03-11T12:40:58.963 | 1871 | 1871 | [
"r",
"multilevel-analysis",
"panel-data",
"data-imputation"
] |
8153 | 2 | null | 8152 | 3 | null | Take a look at the [Amelia II](http://gking.harvard.edu/amelia/) package, by Honaker, King and Blackwell.
>
Amelia II "multiply imputes" missing data in a single cross-section (such as a survey), from a time series (like variables collected for each year in a country), or from a time-series-cross-sectional data set (s... | null | CC BY-SA 4.0 | null | 2011-03-11T13:24:39.780 | 2022-11-28T05:33:13.907 | 2022-11-28T05:33:13.907 | 362671 | 375 | null |
8154 | 2 | null | 8151 | 1 | null | To get the factors, use:
```
cut(dataset, quantile(dataset))
```
From the help:
```
## Default S3 method:
cut(x, breaks)
x a numeric vector which is to be converted to a factor by cutting.
breaks either a numeric vector of two or more cut points or a single number (greater than or equal to 2) giving the nu... | null | CC BY-SA 3.0 | null | 2011-03-11T13:38:19.330 | 2016-08-13T14:03:22.870 | 2016-08-13T14:03:22.870 | 93550 | 1351 | null |
8155 | 2 | null | 8148 | 1 | null | Cluster analysis does not involve hypothesis testing per se, but is really just a collection of different similarity algorithms for exploratory analysis. You can force hypothesis testing somewhat but the results are often inconsistent, since cluster changes are very sensitive to changes in parameters.
[http://support.s... | null | CC BY-SA 2.5 | null | 2011-03-11T14:17:04.913 | 2011-03-11T14:17:04.913 | null | null | 3489 | null |
8156 | 1 | null | null | 1 | 297 | I work with a lot of bar charts. In particular, these bar charts are of basecalls along segments on the human genome. Each point along the x-axis is one of the four nitrogenous bases(A,C,T,G) that compose DNA and the y-axis is essentially how many times a base was able to be "called" (or recognized by a sequencer mach... | Assessing DNA sequencing quality | CC BY-SA 2.5 | null | 2011-03-11T15:08:43.463 | 2011-03-12T10:45:54.777 | 2011-03-12T10:45:54.777 | null | 3672 | [
"histogram",
"bioinformatics"
] |
8157 | 1 | 8395 | null | 10 | 2236 | I need to create random vectors of real numbers a_i satisfying the following constraints:
```
abs(a_i) < c_i;
sum(a_i)< A; # sum of elements smaller than A
sum(b_i * a_i) < B; # weighted sum is smaller than B
aT*A*a < D # quadratic multiplication with A smaller than D
where c_i, b_i, A, B, D are... | Generating random vectors with constraints | CC BY-SA 2.5 | null | 2011-03-11T15:32:55.813 | 2011-03-17T02:56:04.293 | 2011-03-15T18:07:51.207 | 3673 | 3673 | [
"random-generation"
] |
8159 | 1 | null | null | 1 | 299 | >
Possible Duplicate:
What is the difference between data mining, statistics, machine learning and AI?
How to compare
machine learning vs. data mining?
data mining vs. statistical analysis?
machine learning vs. statistical analysis?
| The relationship between machine learning, data mining and statistical analysis? | CC BY-SA 2.5 | null | 2011-03-11T16:57:52.407 | 2011-03-11T16:57:52.407 | 2017-04-13T12:44:39.283 | -1 | 3026 | [
"machine-learning",
"multivariate-analysis",
"data-mining"
] |
8160 | 1 | 8173 | null | 7 | 2076 | I have 3,000 observations (administrative communities) characterized by five variables. Four of them work in the direction 'the more, the worse' and one goes in the opposite.
I'd like to create one score or an ordered list of these observations that will best take into account all of those five variables.
I have tried ... | How to create one score from a mixed set of positive and negative variables? | CC BY-SA 2.5 | null | 2011-03-11T17:23:08.010 | 2011-03-30T18:54:57.467 | 2011-03-12T06:15:11.397 | 183 | 22 | [
"clustering",
"pca",
"composite"
] |
8161 | 1 | 8200 | null | 3 | 461 | Suppose I have two I(1) time series X and Y, and I want to know whether X and Y are "related" (for some definition of "related").
The standard cointegration approach defines relationship as cointegration, and says that X and Y are cointegrated if some linear combination of X and Y is stationary. To test whether X and Y... | Testing two I(1) vectors for a relationship | CC BY-SA 2.5 | null | 2011-03-11T17:25:48.310 | 2014-10-31T12:40:35.140 | 2011-03-12T10:53:24.833 | null | 1106 | [
"time-series",
"correlation",
"cointegration",
"stationarity"
] |
8162 | 2 | null | 8107 | 4 | null | Are you asking about these results in particular or the Breusch-Pagan test more generally? For these particular tests, see @mpiktas's answer. Broadly, the BP test asks whether the squared residuals from a regression can be predicted using some set of predictors. These predictors may be the same as those from the origin... | null | CC BY-SA 2.5 | null | 2011-03-11T17:42:32.797 | 2011-03-11T17:42:32.797 | null | null | 401 | null |
8163 | 2 | null | 8088 | 3 | null | Why are you worried about multicolinearity? The only reason that we need this assumption in regression is to ensure that we get unique estimates. Multicolinearity only matters for estimation when it is perfect---when one variable is an exact linear combination of the others.
If your experimentally-manipulated variables... | null | CC BY-SA 2.5 | null | 2011-03-11T17:47:46.867 | 2011-03-11T17:47:46.867 | null | null | 401 | null |
8165 | 2 | null | 8135 | 8 | null | You should get the "same" estimates no matter which variable you omit; the coefficients may be different, but the estimates of particular quantities or expectations should be the same across all the models.
In a simple case, let $x_i=1$ for men and 0 for women. Then, we have the model:
$$\begin{align*}
E[y_i \mid x_i... | null | CC BY-SA 3.0 | null | 2011-03-11T18:02:32.733 | 2012-12-04T16:28:20.270 | 2012-12-04T16:28:20.270 | 401 | 401 | null |
8166 | 1 | 8177 | null | 5 | 115 | The UN has a convention against corruption (UNCAC) that has been signed by some 140 countries and ratified by most ([link](http://www.unodc.org/unodc/en/treaties/CAC/signatories.html)).
Transparency International publishes an annual report on corruption. They have data for most countries for the period 2000-2010, each ... | Test for the effect of UN ratification on corruption in a set of countries | CC BY-SA 2.5 | null | 2011-03-11T18:17:02.197 | 2015-11-29T00:13:44.090 | 2015-11-29T00:13:44.090 | 805 | 3182 | [
"time-series",
"statistical-significance",
"t-test",
"mean",
"panel-data"
] |
8167 | 1 | 8174 | null | 8 | 3596 | I have a set of around 500 responses to a online survey that offered an incentive to complete. While most of the data appears to be valid, it's clear that some people were able to get around the (inadequate) browser cookie-based duplicate survey protection. Some respondents clearly randomly clicked through the survey t... | How to identify invalid online survey responses? | CC BY-SA 2.5 | null | 2011-03-11T18:27:08.630 | 2011-03-11T19:48:07.653 | 2011-03-11T18:45:41.050 | 1220 | 1220 | [
"classification",
"survey"
] |
8168 | 1 | null | null | 9 | 1037 | Building on the post [How to efficiently manage a statistical analysis project](https://stats.stackexchange.com/questions/2910/how-to-efficiently-manage-a-statistical-analysis-project) and the [ProjectTemplate package](http://www.johnmyleswhite.com/notebook/2010/08/26/projecttemplate/) in R...
Q: How do you build your... | Statistical project directory structure with multiple languages (e.g., R and Splus)? | CC BY-SA 2.5 | null | 2011-03-11T18:50:29.743 | 2011-09-29T03:21:10.087 | 2017-04-13T12:44:37.583 | -1 | 3577 | [
"r",
"project-management",
"splus"
] |
8169 | 1 | 8193 | null | 1 | 879 | Given the prior probability of 2 distributions, $N(x,y)$ and $N(a,b)$, where $N(\mu,\sigma^2)$:
How do you make a decision rule to minimize the probability of error, if the prior probabilities are equal? Can you give an example?
What if the prior probabilities are different, such as
$P(\text{Distribution 1}) = 0.70$
$P... | Bayes classifier | CC BY-SA 2.5 | null | 2011-03-11T19:29:25.397 | 2016-05-06T13:29:48.270 | 2011-03-12T10:41:39.367 | null | 3681 | [
"machine-learning",
"naive-bayes"
] |
8170 | 2 | null | 8052 | 2 | null | Fisher's exact was once only recommended for low cell counts because back in "the dark times" it was computationally infeasible to use it for large counts. Indeed, with some approximations doing small counts properly demands a correction be applied.
No matter, the hypergeometric tests involved are good and powerful. ... | null | CC BY-SA 2.5 | null | 2011-03-11T19:33:09.387 | 2011-03-11T20:05:12.323 | 2011-03-11T20:05:12.323 | 3437 | 3437 | null |
8171 | 5 | null | null | 0 | null | "Regression" is a general term for a wide variety of techniques to analyze the relationship between one (or more) dependent variables and independent variables. Typically the dependent variables are modeled with probability distributions whose parameters are assumed to vary (deterministically) with the independent var... | null | CC BY-SA 2.5 | null | 2011-03-11T19:34:18.293 | 2011-03-11T19:34:18.293 | 2011-03-11T19:34:18.293 | 919 | 919 | null |
8172 | 4 | null | null | 0 | null | Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables. | null | CC BY-SA 2.5 | null | 2011-03-11T19:34:18.293 | 2011-03-11T19:34:18.293 | 2011-03-11T19:34:18.293 | 919 | 919 | null |
8173 | 2 | null | 8160 | 7 | null | You might consider u-scores as defined in [1] Wittkowski, K. M., Lee, E., Nussbaum, R., Chamian, F. N. and Krueger, J. G. (2004), Combining several ordinal measures in clinical studies. Statistics in Medicine, 23: 1579–1592. ([PDF](http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=46258B9F5D853340BDE8FAF578CFE5C... | null | CC BY-SA 2.5 | null | 2011-03-11T19:47:59.110 | 2011-03-13T01:08:30.113 | 2011-03-13T01:08:30.113 | 183 | 279 | null |
8174 | 2 | null | 8167 | 9 | null | 1) Flag all responses with duplicate IP addresses. Create a new variable for this purpose -- say FLAG1, which takes on values of 1 or 0.
2) Choose a threshold for an impossibly fast response time based on common sense (e.g., less than 1 second per question) and the aid of a histogram of response times -- flag people fa... | null | CC BY-SA 2.5 | null | 2011-03-11T19:48:07.653 | 2011-03-11T19:48:07.653 | null | null | 3432 | null |
8176 | 2 | null | 7979 | 1 | null | There is an estimator for the minimum (or the maximum) of a set of numbers given a sample. See Laurens de Haan, "Estimation of the minimum of a function using order statistics," JASM, 76(374), June 1981, 467-469.
| null | CC BY-SA 2.5 | null | 2011-03-11T20:26:09.263 | 2011-03-11T20:26:09.263 | null | null | 3437 | null |
8177 | 2 | null | 8166 | 5 | null | It's probably not a good idea without digging deeper into the source surveys. TI themselves note that changes in a country's index can come from either a change in corruption or just a change in methodology of the sources that they use. The sources themselves change over time as well, so comparing the index from year t... | null | CC BY-SA 2.5 | null | 2011-03-11T20:45:47.983 | 2011-03-11T20:45:47.983 | null | null | 26 | null |
8179 | 2 | null | 8146 | 1 | null | I do not know such a library, but the statistics part of the [apache commons math library](http://commons.apache.org/math/userguide/stat.html) (written in java) provides a series of distributions, including chi2. Since the McNemar's Test does not seem to be thaaat complicated, you may figure an implementation out on yo... | null | CC BY-SA 2.5 | null | 2011-03-11T21:15:49.980 | 2011-03-11T21:15:49.980 | null | null | 264 | null |
8180 | 1 | null | null | 3 | 2796 | Does any body know how to run a post hoc comparison in a 2X2 ANOVA with covariate in R. multcomp package seems very nice but I could not find clear answer or example to my question with this package. Thanks so much in advance
| Post hoc comparison in two way ANOVA with covariate using R | CC BY-SA 2.5 | null | 2011-03-11T21:24:19.273 | 2011-03-12T19:35:02.983 | null | null | 3682 | [
"r",
"multiple-comparisons",
"contrasts"
] |
8181 | 2 | null | 8180 | 5 | null | This is data from Maxwell & Delaney (2004), artificially extended to include a second between-subjects IV, yielding a 3x2 design. Using `multcomp`'s `glht()` function is easier once you switch to the associated one-factorial design by combining your two IVs into one with `interaction()`.
DV is depression scores pre-tre... | null | CC BY-SA 2.5 | null | 2011-03-11T22:06:14.867 | 2011-03-12T19:35:02.983 | 2011-03-12T19:35:02.983 | 1909 | 1909 | null |
8182 | 1 | null | null | 10 | 8407 | Is it possible to use kernel principal component analysis (kPCA) for Latent Semantic Indexing (LSI) in the same way as PCA is used?
I perform LSI in R using the `prcomp` PCA function and extract the features with highest loadings from the first $k$ components. By that I get the features describing the component best.
I... | Is it possible to use kernel PCA for feature selection? | CC BY-SA 3.0 | null | 2011-03-11T22:58:23.873 | 2015-08-11T16:46:11.983 | 2015-08-11T16:45:44.310 | 28666 | 3683 | [
"r",
"pca",
"feature-selection",
"kernel-trick"
] |
8183 | 2 | null | 8146 | 1 | null | I found this on [Google](http://www.google.com/search?sourceid=chrome&ie=UTF-8&q=Mcnemar+test+java):
[http://www.jsc.nildram.co.uk/api/jsc/contingencytables/McNemarTest.html](http://www.jsc.nildram.co.uk/api/jsc/contingencytables/McNemarTest.html)
Does it do anything for you? McNemar's Test is implemented in the Java S... | null | CC BY-SA 2.5 | null | 2011-03-11T23:19:14.227 | 2011-03-11T23:19:14.227 | null | null | 1118 | null |
8184 | 1 | 12221 | null | 8 | 1002 | It's well established that both Anderson-Darling and Shapiro-Wilk have a much higher power to detect departures from normality than a KS-Test.
I have been told that Shapiro-Wilk is usually the best test to use if you want to test if a distribution is normal because it has one of the highest powers to detect lack of nor... | Most powerful GoF test for normality | CC BY-SA 2.5 | null | 2011-03-11T23:36:27.563 | 2011-06-22T19:13:01.430 | 2011-03-12T10:43:08.117 | null | 1118 | [
"goodness-of-fit"
] |
8185 | 1 | null | null | 9 | 6159 | From basic statistics and hearing "correlation is not causation" all the time, I tend to think it's fine to say that "X and Y are correlated" even if X and Y aren't in a causal relationship. For example, I'd normally think it's perfectly okay to say that ice cream sales and swimsuit sales are correlated, since high swi... | "Correlation" terminology in time series analysis | CC BY-SA 2.5 | null | 2011-03-11T23:54:24.433 | 2011-03-12T16:37:12.907 | 2011-03-12T10:39:22.473 | null | null | [
"time-series",
"correlation"
] |
8186 | 2 | null | 8185 | 7 | null | In order to avoid the spurious correlation problem, you should regress two stationary time series against one another. This can (potentially) provide a causal story. It is non-stationary series that lead to spurious correlation. See the reasoning given by my answer to [this question](https://stats.stackexchange.com/que... | null | CC BY-SA 2.5 | null | 2011-03-12T00:04:38.953 | 2011-03-12T00:04:38.953 | 2017-04-13T12:44:37.793 | -1 | 401 | null |
8187 | 1 | 8279 | null | 4 | 460 | I am a beginner in statistics. I have these unpublished data (cases and deaths) of a disease for 7 years (2004-2010) from 2 neighbouring states. The study was started in 2004. State 1 and State 2 received different treatments. The death rate is high in one State. I want to prove that treatment given in State 1 is super... | How to assess effect of intervention in one state versus another using annual death rate data? | CC BY-SA 2.5 | null | 2011-03-12T01:05:02.263 | 2012-12-19T13:34:54.220 | 2011-03-13T04:16:15.557 | 2956 | 2956 | [
"meta-analysis",
"experiment-design",
"effect-size",
"odds-ratio",
"relative-risk"
] |
8188 | 2 | null | 8145 | 2 | null | Calculate [correlogram](http://en.wikipedia.org/wiki/Correlogram) for your process. If your process is gaussian (by the looks of your sample it is) you can establish lower/upper bounds (B) and check if the correlations at given lag are significant. Positive autocorrelation at lag 1 would indicate existence of "streaks ... | null | CC BY-SA 2.5 | null | 2011-03-12T03:35:21.030 | 2011-03-12T03:35:21.030 | null | null | null | null |
8189 | 2 | null | 8185 | 2 | null | As to your main question, my answer is No. If you've seen such a distinction between the way the terms are used in time series contexts vs. cross-sectional contexts, it must be due to one or two idiosyncratic authors you've read. Rigorous authors would never be correct in using "correlation" to mean "causation." You... | null | CC BY-SA 2.5 | null | 2011-03-12T03:46:28.557 | 2011-03-12T03:46:28.557 | null | null | 2669 | null |
8190 | 2 | null | 8145 | 5 | null | A few thoughts:
- Plot the distribution of times.
My guess is that they will be positively skewed, such that some solution times are really slow. In that case you might want to consider a log or some other transformation of solution times.
- Create a scatter plot of trial on the x axis and solution time (or log solut... | null | CC BY-SA 2.5 | null | 2011-03-12T05:40:11.007 | 2011-03-12T05:40:11.007 | null | null | 183 | null |
8191 | 2 | null | 8160 | 6 | null |
### Data or Theory Driven?
The first issue is whether you want the composite to be data driven or theory driven?
If you are wishing to form a composite variable, it is likely that you think that each component variable is important in measuring some overall domain.
In this case, you are likely going to prefer a the... | null | CC BY-SA 2.5 | null | 2011-03-12T06:02:41.313 | 2011-03-13T01:06:48.167 | 2011-03-13T01:06:48.167 | 183 | 183 | null |
8192 | 1 | null | null | 2 | 1420 | I want to test whether a correlation coefficient is greater than 0.5.
- What should the null and alternative hypothesis be?
- Should I do a two tailed test or one tailed test?
Thanks
| Hypothesis test for whether correlation coefficient is greater than specified value? | CC BY-SA 2.5 | null | 2011-03-12T06:59:04.090 | 2011-03-13T03:40:01.790 | 2011-03-12T07:18:23.997 | 183 | 3725 | [
"hypothesis-testing",
"correlation"
] |
8193 | 2 | null | 8169 | 4 | null | Let's say we have to classes $C$, i.e. $c_1$ and $c_2$ and further that the points of the class $c_1$ are drawn from N(a,b) and the points of $c_2$ from N(c,d) respectively (note the changes in notation). The point variable shall be X, a value of this variable x.
Here is the Bayes-Theorem:
$p(C|X)=\frac{p(X|C)*p(C)}{p... | null | CC BY-SA 3.0 | null | 2011-03-12T08:08:58.610 | 2016-05-06T13:29:48.270 | 2016-05-06T13:29:48.270 | 107098 | 264 | null |
8194 | 2 | null | 8192 | 1 | null | I came up with the following by taking a look at some video lectures. Are they correct?
The null hypothesis : correlation = 0.5
The alternative hypothesis : correlation > 0.5
Please confirm if they are correct.
| null | CC BY-SA 2.5 | null | 2011-03-12T08:18:32.070 | 2011-03-12T09:21:54.810 | 2011-03-12T09:21:54.810 | 3725 | 3725 | null |
8195 | 2 | null | 8185 | 7 | null | There is a good definition of spurious relationship in [wikipedia](http://en.wikipedia.org/wiki/Spurious_relationship). Spurious means that there is some hidden variable or feature which causes both of the variables. In both time-series and in usual regression then terminology means the same, the relationship between t... | null | CC BY-SA 2.5 | null | 2011-03-12T08:51:13.900 | 2011-03-12T11:44:43.593 | 2011-03-12T11:44:43.593 | 2116 | 2116 | null |
8196 | 1 | null | null | 25 | 5437 | This is somewhat related to [another question](https://stats.stackexchange.com/questions/8192/hypothesis-test-for-whether-correlation-coefficient-is-greater-than-specified-val) that I asked. The question I have is, when doing hypothesis testing, when the alternative hypothesis is a range, the null hypothesis is still a... | Why is the null hypothesis always a point value rather than a range in hypothesis testing? | CC BY-SA 2.5 | null | 2011-03-12T09:27:27.410 | 2013-07-19T14:26:19.000 | 2017-04-13T12:44:44.767 | -1 | 3725 | [
"hypothesis-testing"
] |
8197 | 2 | null | 8166 | 4 | null | One problem with your pre-post paired t-test idea is that it chould give a small p-value if there's a general upward (or downward) trend in the corruption score over time regardless of ratification. You need some sort of comparison group in which the ratification status did not change between the two time points.
In pr... | null | CC BY-SA 2.5 | null | 2011-03-12T09:34:31.413 | 2011-03-12T09:34:31.413 | null | null | 449 | null |
8198 | 2 | null | 8196 | 21 | null | First, it is not always the case. There might be a composite null.
Most standard tests have a simple null because in the framework of Neyman and Pearson the aim is to provide a decision rule that permits you to control the error of rejecting the null when it is true. To control this error you need to specify one distr... | null | CC BY-SA 3.0 | null | 2011-03-12T10:13:40.070 | 2013-07-19T14:26:19.000 | 2013-07-19T14:26:19.000 | 17230 | 223 | null |
8199 | 2 | null | 8196 | 2 | null | I don't think that the null hypothesis should always be something like correlation=0.5. At least in the problems which I have come across that wasn't the case. For example in information theoretic statistics the following problem is considered. Suppose that $X_1, X_2, \cdots, X_n$ are coming from an unknown distributio... | null | CC BY-SA 2.5 | null | 2011-03-12T10:24:55.427 | 2011-03-12T10:31:47.807 | 2011-03-12T10:31:47.807 | 3485 | 3485 | null |
8200 | 2 | null | 8161 | 4 | null | If time series are cointegrated they admit VECM representation according to Granger Representation theorem. This is scantily explained in [this wikipedia page](http://en.wikipedia.org/wiki/Johansen_test). So if we have I(1) process:
$$X_t=\mu+\Phi D_t+\Pi_1 X_{t-1}+...+\Pi_p X_{t-p}+\varepsilon_t$$
it admits VECM repre... | null | CC BY-SA 3.0 | null | 2011-03-12T12:25:42.250 | 2014-10-31T12:40:35.140 | 2014-10-31T12:40:35.140 | 2116 | 2116 | null |
8201 | 1 | 8205 | null | 7 | 319 | EDIT: I reduced my problem to a more specific question:
[https://math.stackexchange.com/questions/26573/](https://math.stackexchange.com/questions/26573/)
But I am still interested in other ideas.
Let's say our data is generated by
$$Y_i = f(X_i) + \epsilon_i$$
where $X_i$ are observed vectors, and $f$ is an unknown fu... | Learning from unordered tuples? | CC BY-SA 2.5 | null | 2011-03-12T15:58:35.533 | 2019-12-03T20:36:38.550 | 2019-12-03T17:19:59.853 | 11887 | 3567 | [
"regression",
"modeling",
"functional-data-analysis"
] |
8204 | 1 | null | null | 2 | 445 | I have used factor analysis with regression method. I was trying to develop an index using this regression equation by using the output of the component score coefficient matrix (SPSS) generated for each factor. Should I include the residuals found under the "Reproduced Correlations Table" (SPSS) in the regression equa... | Factor analysis: regression equation and residuals | CC BY-SA 2.5 | null | 2011-03-12T16:38:34.327 | 2011-03-12T19:26:13.213 | 2011-03-12T19:26:13.213 | null | null | [
"spss",
"factor-analysis"
] |
8205 | 2 | null | 8201 | 4 | null | For regression models, one way would be to generate derived variables that are invariant to permutation of the labelling of the $x_i$s.
E.g. in your three-variable example, considering only polynomials of total order up to 3, such combinations would be:
- $w_1 = x_1 + x_2 + x_3$
- $w_2 = x_1x_2 + x_1x_3 + x_2x_3$
- ... | null | CC BY-SA 2.5 | null | 2011-03-12T17:21:16.623 | 2011-03-12T17:33:03.023 | 2011-03-12T17:33:03.023 | 449 | 449 | null |
8206 | 1 | null | null | 11 | 55793 | I need to build a boxplot without any axes and add it to the current plot (ROC curve), but I need to add more text information to the boxplot: the labels for min and max. Current line of code is below (current graph also).
Thanks a lot for assistance.
```
boxplot(data, horizontal = TRUE, range = 0, axes=FALSE, col = "g... | Labeling boxplots in R | CC BY-SA 2.5 | null | 2011-03-12T17:31:58.277 | 2018-02-24T05:07:17.837 | 2011-03-12T22:36:01.140 | 919 | 3345 | [
"r",
"boxplot"
] |
8207 | 2 | null | 8201 | 3 | null | To add to onestop's response, it was confirmed on math.SE that the polynomials
$$w_1 = x_1 + \cdots + x_n$$
$$w_2 = x_1^2 + \cdots + x_n^2$$
$$\cdots$$
$$w_n = x_1^n + \cdots + x_n ^n$$
give you all the information needed to determine the original $X=(x_1, \cdots, x_n)$.
This is a neat result because it also applies to... | null | CC BY-SA 2.5 | null | 2011-03-12T18:08:32.600 | 2011-03-12T18:08:32.600 | null | null | 3567 | null |
8208 | 2 | null | 7946 | 2 | null | To echo everyone else: MORE DETAILS ABOUT YOUR DATA. Please give a qualitative description of what your independent and dependent variable(s) is/are.
EDIT: Yes this is confusing; hopefully it's cleared up now.
In general, you probably want to avoid using sample statistics to estimate population parameters if you have t... | null | CC BY-SA 2.5 | null | 2011-03-12T18:10:30.497 | 2011-03-21T03:33:02.500 | 2011-03-21T03:33:02.500 | 2660 | 2660 | null |
8209 | 2 | null | 8148 | 5 | null | There is a very wide variety of clustering methods, which are exploratory by nature, and I do not think that any of them, whether hierarchical or partition-based, relies on the kind of assumptions that one has to meet for analysing variance.
Having a look at the [MV] documentation in Stata to answer your question, I fo... | null | CC BY-SA 2.5 | null | 2011-03-12T18:11:59.990 | 2011-03-12T18:24:45.247 | 2011-03-12T18:24:45.247 | 3582 | 3582 | null |
8210 | 2 | null | 8187 | 2 | null | I might have wrongly understood the data (see my comment above), but what would be so wrong in simply t-testing the difference in means of the deaths-to-cases ratios between the two series, assuming that the states are clearly independent from each other?
A t-test shows that State 2 performs far better than State 1 in ... | null | CC BY-SA 2.5 | null | 2011-03-12T18:45:14.493 | 2011-03-13T02:49:01.330 | 2011-03-13T02:49:01.330 | 3582 | 3582 | null |
8211 | 2 | null | 8206 | 8 | null | Try something like this for a standalone version:
```
bxp <- boxplot(rnorm(100), horizontal=TRUE, axes=FALSE)
mtext(c("Min","Max"), side=3, at=bxp$stats[c(1,5)], line=-3)
```
Note that you can get some information when calling `boxplot`, in particular the "five numbers".
If you want it to be superimposed onto another ... | null | CC BY-SA 2.5 | null | 2011-03-12T18:55:43.080 | 2011-03-12T18:55:43.080 | null | null | 930 | null |
8212 | 2 | null | 8206 | 9 | null | I think you will find this produces something like your hand-drawn diagram.
```
data <- c(0.4, 0.7, 0.75, 0.82, 0.9)
endaxis <- c(0, 1) # endpoints of axis
datamm <- c(min(data), max(data))
boxplot(data, horizontal = TRUE, range = 0, ylim = endaxis,
axes = FALSE, col = "grey", add = FALSE)
ar... | null | CC BY-SA 2.5 | null | 2011-03-12T19:06:21.527 | 2011-03-13T09:09:30.617 | 2011-03-13T09:09:30.617 | 930 | 2958 | null |
8213 | 1 | 8214 | null | 11 | 3911 | For some volume reconstruction algorithm I'm working on, I need to detect an arbitrary number of circular patterns in 3d point data (coming from a LIDAR device). The patterns can be arbitrarily oriented in space, and be assumed to lie (although not perfectly) in thin 2d planes. Here is an example with two circles in th... | Detect circular patterns in point cloud data | CC BY-SA 2.5 | null | 2011-03-12T19:50:46.497 | 2019-02-28T07:11:56.823 | 2011-03-12T20:39:07.317 | 3693 | 3693 | [
"clustering",
"image-processing"
] |
8214 | 2 | null | 8213 | 10 | null | A generalized [Hough transform](http://en.wikipedia.org/wiki/Hough_transform) is exactly what you want. The difficulty is to do it efficiently, because the space of circles in 3D has six dimensions (three for the center, two to orient the plane, one for the radius). This seems to rule out a direct calculation.
One po... | null | CC BY-SA 2.5 | null | 2011-03-12T22:32:41.720 | 2011-03-12T22:32:41.720 | null | null | 919 | null |
8215 | 2 | null | 125 | 15 | null | My favourite first undergraduate text for bayesian statistics is by Bolstad, [Introduction to Bayesian Statistics](http://rads.stackoverflow.com/amzn/click/0470141158). If you're looking for something graduate level, this will be too elementary, but for someone who is new to statistics this is ideal.
| null | CC BY-SA 2.5 | null | 2011-03-12T23:55:47.807 | 2011-03-12T23:55:47.807 | null | null | 3694 | null |
8216 | 2 | null | 125 | 9 | null | I've at least glanced at most of these on this list and none are as good as the new [Bayesian Ideas and Data Analysis](http://rads.stackoverflow.com/amzn/click/1439803544) in my opinion.
Edit: It is easy to immediately begin doing Bayesian analysis while reading this book. Not just model the mean from a Normal distrib... | null | CC BY-SA 3.0 | null | 2011-03-13T00:58:39.420 | 2012-07-28T20:29:52.300 | 2012-07-28T20:29:52.300 | 2310 | 2310 | null |
8217 | 2 | null | 8160 | 2 | null | For a non-ordinal measure, you could try MDS (multi-dimensional scaling). This can be done easily in R. This will try to arrange the points on a line (1d in your case) in such a way that distances between points will be preserved.
Some general comments: as you probably realize, the question is pretty vague, and not muc... | null | CC BY-SA 2.5 | null | 2011-03-13T03:12:26.717 | 2011-03-13T03:12:26.717 | null | null | 3369 | null |
8218 | 2 | null | 8192 | 1 | null | One thing which may be difficult to determine using sampling theory is $P(data|\rho>0.5)$. I don't know of a sampling theory based decision problem which evaluates this directly (that is not to say it is impossible, I may just be ignorant).
You usually have to take a "minimax" approach. That is, find the "most favora... | null | CC BY-SA 2.5 | null | 2011-03-13T03:40:01.790 | 2011-03-13T03:40:01.790 | null | null | 2392 | null |
8220 | 1 | null | null | 3 | 321 | I'd like to perform semi-supervised LDA (Latent Dirichlet Allocation) in the following sense:
I have several topics that I'd like to use, and have seed documents that relate to these topics. I'd like to run LDA to classify other documents, and potentially discover other topics.
I would guess there is work done on that,... | References on semi-supervised LDA | CC BY-SA 3.0 | null | 2011-03-13T07:09:44.603 | 2020-02-07T16:15:35.063 | 2020-02-07T16:15:35.063 | 11887 | 3696 | [
"references",
"text-mining",
"unsupervised-learning",
"semi-supervised-learning"
] |
8222 | 1 | null | null | 9 | 4665 | I have been looking for computer game datasets, but so far I've only been able to find the 'Avatar History' dataset for WoW.
Are there any other interesting datasets out there, possibly for other genres?
| Computer game datasets | CC BY-SA 2.5 | null | 2011-03-13T09:58:02.480 | 2011-03-13T13:13:15.433 | 2011-03-13T11:54:19.637 | null | 37 | [
"data-mining",
"dataset"
] |
8223 | 2 | null | 4099 | 6 | null | Multicollinearity problem is well studied in actually most econometric textbooks. Moreover there is a good article in [wikipedia](http://en.wikipedia.org/wiki/Multicollinearity) which actually summarizes most of the key issues.
In practice one starts to bear in mind the multicollinearity problem if it causes some visua... | null | CC BY-SA 2.5 | null | 2011-03-13T10:44:00.427 | 2011-03-13T10:44:00.427 | null | null | 2645 | null |
8224 | 2 | null | 8222 | 7 | null | Starcraft I
- Starcraft Data Mining Project, providing some game data.
- Starcraft AI Competition, does not directly provide data, but allows you to connect a program written by you with the game. Although I did not try it, I expect that data collection is possible this way ;).
If you are generally interested in da... | null | CC BY-SA 2.5 | null | 2011-03-13T11:20:58.870 | 2011-03-13T11:20:58.870 | null | null | 264 | null |
8225 | 1 | 8230 | null | 188 | 722977 | I have R data frame like this:
```
age group
1 23.0883 1
2 25.8344 1
3 29.4648 1
4 32.7858 2
5 33.6372 1
6 34.9350 1
7 35.2115 2
8 35.2115 2
9 35.2115 2
10 36.7803 1
...
```
I need to get data frame in the following form:
```
group mean sd
1 34... | How to summarize data by group in R? | CC BY-SA 2.5 | null | 2011-03-13T12:02:38.533 | 2015-11-11T08:03:29.147 | 2011-03-13T15:20:27.067 | 3376 | 3376 | [
"r",
"data-transformation"
] |
8226 | 2 | null | 8225 | 103 | null | One possibility is to use the [aggregate function](http://stat.ethz.ch/R-manual/R-patched/library/stats/html/aggregate.html).
For instance,
```
aggregate(data$age, by=list(data$group), FUN=mean)[2]
```
gives you the second column of the desired result.
| null | CC BY-SA 3.0 | null | 2011-03-13T12:12:54.217 | 2013-10-23T16:11:05.887 | 2013-10-23T16:11:05.887 | 7290 | 3019 | null |
8227 | 2 | null | 8225 | 8 | null | Edited: According to chl's suggestions
The function you are looking for is called "tapply" which applies a function per group specified by a factor.
```
# create some artificial data
set.seed(42)
groups <- 5
agedat <- c()
groupdat <- c()
for(group in 1:groups){
agedat <- c(agedat,rnorm(100,mean=0 + group,1/group)... | null | CC BY-SA 2.5 | null | 2011-03-13T12:15:29.533 | 2011-03-13T18:21:19.523 | 2017-04-13T12:44:25.283 | -1 | 264 | null |
8228 | 2 | null | 1352 | 2 | null | Answering with an aphorism, I believe that your study design will be successful as soon as it actually exists in its full-fledged form. The game of reviewing as it is played in academia is primarily a game of academics showing to each other that they have not completed that step in its full depth, e.g. by violating ass... | null | CC BY-SA 2.5 | null | 2011-03-13T12:26:51.003 | 2011-03-13T12:26:51.003 | null | null | 3582 | null |
8229 | 2 | null | 8225 | 11 | null | In addition to existing suggestions, you might want to check out the `describe.by` function in the `psych` package.
It provides a number of descriptive statistics including the mean and standard deviation based on a grouping variable.
| null | CC BY-SA 2.5 | null | 2011-03-13T12:38:57.817 | 2011-03-13T12:38:57.817 | null | null | 183 | null |
8230 | 2 | null | 8225 | 144 | null | Here is the plyr one line variant using ddply:
```
dt <- data.frame(age=rchisq(20,10),group=sample(1:2,20,rep=T))
ddply(dt,~group,summarise,mean=mean(age),sd=sd(age))
```
Here is another one line variant using new package data.table.
```
dtf <- data.frame(age=rchisq(100000,10),group=factor(sample(1:10,100000,rep=T)))... | null | CC BY-SA 3.0 | null | 2011-03-13T12:44:13.913 | 2014-10-25T10:16:17.373 | 2014-10-25T10:16:17.373 | 2116 | 2116 | null |
8231 | 2 | null | 8222 | 1 | null |
- John Myles White has a dataset and analysis of Canabalt scores as posted on Twitter
- Stats at Berkeley has a dataset for a Video Games Survey.
| null | CC BY-SA 2.5 | null | 2011-03-13T12:45:03.647 | 2011-03-13T13:13:15.433 | 2011-03-13T13:13:15.433 | 183 | 183 | null |
8232 | 1 | null | null | 3 | 933 |
I'm trying to figure out the usage of the $\chi^2$ distribution. In other words, in what kind of situations it occurs and how is it useful in that situations.
I read the wikipedia definition of $\chi^2$. Can someone give an example of a $\chi^2$ distribution so that I can better understand it?
| What is an example of a chi-squared distribution? | CC BY-SA 2.5 | null | 2011-03-13T13:17:04.273 | 2021-02-02T12:08:06.727 | 2021-02-02T12:08:06.727 | 11887 | 3725 | [
"chi-squared-distribution"
] |
8233 | 2 | null | 8232 | 2 | null | I found [this video](http://www.youtube.com/watch?v=dXB3cUGnaxQ) useful in finding the solution to my question.
| null | CC BY-SA 2.5 | null | 2011-03-13T14:09:18.563 | 2011-03-13T14:09:18.563 | null | null | 3725 | null |
8235 | 2 | null | 8137 | 8 | null | Found solution myself. Maybe someone could use it:
```
#step 1: preparing data
ageMetaData <- ddply(data,~group,summarise,
mean=mean(age),
sd=sd(age),
min=min(age),
max=max(age),
median=median(age),
Q1=summary(age)['1st Qu.'],
Q3=summar... | null | CC BY-SA 2.5 | null | 2011-03-13T14:51:25.300 | 2011-03-13T19:22:24.783 | 2011-03-13T19:22:24.783 | 3376 | 3376 | null |
8236 | 1 | 8275 | null | 10 | 875 | I have a dataset of events that happened during the same period of time. Each event has a type (there are few different types, less then ten) and a location, represented as a 2D point.
I would like to check if there is any correlation between types of events, or between the type and the location. For example, maybe eve... | How to find relationships between different types of events (defined by their 2D location)? | CC BY-SA 2.5 | null | 2011-03-13T14:52:13.300 | 2011-03-15T16:27:00.380 | 2011-03-15T16:27:00.380 | 3699 | 3699 | [
"correlation",
"pca",
"multivariate-analysis",
"point-process"
] |
8237 | 1 | null | null | 19 | 12559 |
I'm trying to understand the logic behind the ANOVA F-test in Simple Linear Regression Analysis. The question I have is like follows. When the F value, i.e.
`MSR/MSE` is large we accept the model as significant. What is the logic behind this?
| Logic behind the ANOVA F-test in simple linear regression | CC BY-SA 2.5 | null | 2011-03-13T15:15:05.713 | 2011-03-13T21:38:19.687 | 2011-03-13T20:22:49.233 | null | 3725 | [
"regression",
"anova"
] |
8238 | 2 | null | 290 | 3 | null | I have listed some resources on my [Stata page](http://f.briatte.org/teaching/quanti/stata.html). It includes links to the UCLA and Princeton tutorials, as well as a few more resources in several formats. The "[Stata Guide](http://f.briatte.org/teaching/quanti/stata.html#download)" document, which is very much a work i... | null | CC BY-SA 2.5 | null | 2011-03-13T15:23:49.450 | 2011-03-13T15:23:49.450 | null | null | 3582 | null |
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