Id stringlengths 1 6 | PostTypeId stringclasses 7
values | AcceptedAnswerId stringlengths 1 6 ⌀ | ParentId stringlengths 1 6 ⌀ | Score stringlengths 1 4 | ViewCount stringlengths 1 7 ⌀ | Body stringlengths 0 38.7k | Title stringlengths 15 150 ⌀ | ContentLicense stringclasses 3
values | FavoriteCount stringclasses 3
values | CreationDate stringlengths 23 23 | LastActivityDate stringlengths 23 23 | LastEditDate stringlengths 23 23 ⌀ | LastEditorUserId stringlengths 1 6 ⌀ | OwnerUserId stringlengths 1 6 ⌀ | Tags list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8685 | 2 | null | 7897 | 3 | null | Unless identification of the most relevant variables is a key aim of the analysis, it is often better not to do any feature selection at all and use regularisation to prevent over-fitting. Feature selection is a tricky procedure and it is all too easy to over-fit the feature selection criterion as there are many degre... | null | CC BY-SA 2.5 | null | 2011-03-23T18:01:20.987 | 2011-03-23T18:01:20.987 | null | null | 887 | null |
8687 | 2 | null | 8677 | 7 | null | Do you know the [qgraph](http://sites.google.com/site/qgraphproject/) project (and the related [R package](http://cran.r-project.org/web/packages/qgraph/index.html))? It aims at providing various displays for psychometric models, especially those relying on correlations. I discovered this approach for displaying correl... | null | CC BY-SA 2.5 | null | 2011-03-23T18:32:52.837 | 2011-03-23T18:32:52.837 | null | null | 930 | null |
8689 | 1 | 8713 | null | 19 | 12650 | In R, if I write
```
lm(a ~ b + c + b*c)
```
would this still be a linear regression?
How to do other kinds of regression in R? I would appreciate any recommendation for textbooks or tutorials?
| What does linear stand for in linear regression? | CC BY-SA 2.5 | null | 2011-03-23T19:48:25.340 | 2021-04-15T23:35:10.463 | 2021-01-11T22:33:33.700 | 11887 | 3870 | [
"r",
"regression",
"interaction",
"intuition"
] |
8690 | 1 | 8760 | null | 7 | 392 | Suppose I wanted to fit a model of the form
$$y_i = \beta_0 + \sum_{1 \le j \le k} \beta_j X_{i,j} + \gamma_i Z_i + \epsilon_i,$$
to some data, where the regressors $X$ and $Z$, and the regressand $y$ are observed, and where $\gamma_i$ is a Bernoulli random variable that equals one with (unknown) probability $p$ and is... | Linear model with random coefficient | CC BY-SA 2.5 | null | 2011-03-23T20:11:04.610 | 2011-03-28T12:08:49.257 | 2011-03-25T10:59:58.783 | null | 795 | [
"regression"
] |
8691 | 1 | null | null | 7 | 475 | I'm comparing scores for two small groups of individuals that competed in a tournament, and I'm being told that the comparison calls for a Mann-Whitney U test. It feels wrong to me, though: my two sets of scores are fundamentally interdependent because the two groups competed against one another.
Briefly: I have two gr... | Statistical analysis of competition data | CC BY-SA 2.5 | null | 2011-03-23T20:14:56.090 | 2011-03-24T10:34:54.860 | null | null | null | [
"hypothesis-testing",
"nonparametric"
] |
8692 | 1 | 8697 | null | 4 | 12695 | I want to transpose a data frame in R with `unstack`. Consider the two data frames, `a` and `b`:
```
> a
count state
1 199665 RSTO
2 4147 RSTR
3 31274 S1
4 1 S2
5 2522 S3
6 118009 SF
> b
count state
1 31956 RSTO
2 11689 RSTR
3 6702 S1
4 2838 S2
5 6268 S3
6 672561 SF
`... | Transposing data frames in R via unstack | CC BY-SA 2.5 | null | 2011-03-23T20:16:06.923 | 2017-04-23T09:34:18.440 | null | null | 1537 | [
"r",
"data-transformation"
] |
8693 | 2 | null | 8689 | 4 | null | I would be careful in asking this as an "R linear regression" question versus a "linear regression" question. Formulas in R have rules that you may or may not be aware of. For example:
[http://wiener.math.csi.cuny.edu/st/stRmanual/ModelFormula.html](http://wiener.math.csi.cuny.edu/st/stRmanual/ModelFormula.html)
Ass... | null | CC BY-SA 2.5 | null | 2011-03-23T20:23:54.697 | 2011-03-23T21:48:53.517 | 2011-03-23T21:48:53.517 | 2775 | 2775 | null |
8694 | 2 | null | 8691 | 6 | null | Yes. This situation is so complicated and the results are so interdependent that the applicability of almost any standard test has to be called into question.
Why not conduct a [permutation test](http://en.wikipedia.org/wiki/Resampling_%28statistics%29#Permutation_tests)? This is a natural situation for it: the null ... | null | CC BY-SA 2.5 | null | 2011-03-23T20:54:36.260 | 2011-03-23T21:19:11.903 | 2011-03-23T21:19:11.903 | 919 | 919 | null |
8695 | 1 | null | null | 2 | 62377 | I have some issues with an exploratory factor analysis.
Can anybody please tell me how to calculate the Average Variance Extracted (AVE) and the Composite Reliability from two factors, each with three items using SPSS? If not with SPSS, Stata might help too.
| AVE & composite reliability with SPSS | CC BY-SA 3.0 | null | 2011-03-23T20:57:27.787 | 2018-09-28T17:10:54.200 | 2014-01-21T23:07:27.623 | 7290 | null | [
"spss",
"factor-analysis",
"reliability",
"composite"
] |
8696 | 1 | 9956 | null | 10 | 3037 | UPDATE: caret now uses `foreach` internally, so this question is no longer really relevant. If you can register a working parallel backend for `foreach`, caret will use it.
---
I have the [caret](http://caret.r-forge.r-project.org/Classification_and_Regression_Training.html) package for R, and I'm interesting in us... | Parallelizing the caret package using doSMP | CC BY-SA 3.0 | null | 2011-03-23T21:04:15.040 | 2014-01-07T14:32:50.000 | 2014-01-07T14:32:50.000 | 2817 | 2817 | [
"r",
"parallel-computing"
] |
8697 | 2 | null | 8692 | 8 | null | Note that `rbind(a, b)` creates a single data frame, so that's not it. The unexpected behavior of `unstack(a)` results from the fact that you only have one observation (`count`) per factor level (`state`). To see what's going on, you have to look at the `unstack()` function.
```
# list source code for unstack()'s metho... | null | CC BY-SA 2.5 | null | 2011-03-23T21:15:39.913 | 2011-03-23T21:44:51.900 | 2011-03-23T21:44:51.900 | 1909 | 1909 | null |
8698 | 2 | null | 8692 | 2 | null | Caracal has answered the question. Here are some additional pieces of information.
Try this:
```
require(stats)
formula(PlantGrowth)
x = PlantGrowth[c(1,11,21),]
y = PlantGrowth[c(1,2,11,12,21,22),]
x
unstack(x)
y
unstack(y)
```
The output:
```
> x
weight group
1 4.17 ctrl
11 4.81 trt1
21 6.31 trt2
> ... | null | CC BY-SA 2.5 | null | 2011-03-23T21:18:52.463 | 2011-03-23T21:30:36.963 | 2011-03-23T21:30:36.963 | 1351 | 1351 | null |
8699 | 2 | null | 8669 | 0 | null | Are you sure there's a Z variable? Since you have an equation of X's versus Y's, isn't one of the X's or Y's the dependent variable? For example:
$$X_1 = - newa_2X_2... - newa_{11}X_{11} + newb_0 + newb_1Y_1 + newb_2Y_2 + new b_3Y_3 + newb_4Y_4$$
| null | CC BY-SA 2.5 | null | 2011-03-23T21:45:18.903 | 2011-03-23T21:45:18.903 | null | null | 2775 | null |
8700 | 2 | null | 8690 | 1 | null | Maybe I'm missing something here, but couldn't you rearrange the equation and do a logit or probit analysis on gamma?
| null | CC BY-SA 2.5 | null | 2011-03-23T22:14:01.047 | 2011-03-23T22:28:41.923 | 2011-03-23T22:28:41.923 | 2775 | 2775 | null |
8701 | 2 | null | 7318 | 2 | null | Non-parametric tests are likely to be less powerful than parametric tests and thus require a larger sample size. This is annoying because if you had a large sample size, sample means would be approximately normally distributed by the central limit theorem, and you thus wouldn't need non-parametric tests.
Look at genera... | null | CC BY-SA 2.5 | null | 2011-03-23T22:47:02.427 | 2011-03-23T22:47:02.427 | null | null | 3874 | null |
8702 | 1 | null | null | 4 | 1104 | I am examining the difference between a physical feature of different species of animals. Due to the nature of my experiments I'm using a nonlinear mixed model with the following setup:
```
lme(log10(feature) ~ log10(Body.mass) + factor(Trial.Number), random = ~1 | IndividualID, data=animals, subset=Frfactor=="low", na... | Boxplot with glme | CC BY-SA 2.5 | null | 2011-03-23T23:00:11.000 | 2012-10-18T02:02:50.437 | 2011-03-24T07:07:50.403 | 449 | null | [
"r",
"repeated-measures",
"boxplot"
] |
8703 | 2 | null | 8562 | 4 | null | You might use a nested design (and a hierarchical/multilevel model). The top level would be Baseline v Non-Baseline, and the Non-Baseline would include your 2^3 factorial design.
I unfortunately can't post my pretty picture of the nesting structure because I don't have 10 reputation yet.
I'd have to read a bit to remem... | null | CC BY-SA 2.5 | null | 2011-03-23T23:01:21.810 | 2011-03-23T23:01:21.810 | null | null | 3874 | null |
8704 | 1 | 8721 | null | 3 | 107 | The title defines the question. May be the concept would do...like how to go about it? Thanks.
| Given pdf of $I$ and $R$ (both $I$ and $R$ are independent RV's), how to find pdf of $W =I^2\cdot R$? | CC BY-SA 2.5 | null | 2011-03-24T00:05:13.620 | 2011-03-24T14:24:39.583 | 2011-03-24T08:52:26.383 | 2645 | null | [
"self-study",
"independence",
"density-function"
] |
8706 | 2 | null | 8689 | 35 | null | Linear refers to the relationship between the parameters that you are estimating (e.g., $\beta$) and the outcome (e.g., $y_i$). Hence, $y=e^x\beta+\epsilon$ is linear, but $y=e^\beta x + \epsilon$ is not. A linear model means that your estimate of your parameter vector can be written $\hat{\beta} = \sum_i{w_iy_i}$, whe... | null | CC BY-SA 2.5 | null | 2011-03-24T01:32:10.797 | 2011-03-24T01:32:10.797 | null | null | 401 | null |
8709 | 2 | null | 8633 | 1 | null | If you're interested in parsing a measure of fatigue from your RT data for use as a covariate, then I'd suggest computing the slope of RT as a function of time. An additional measure of "noisiness" might be the variance of RT once the effect of time has been removed.
| null | CC BY-SA 2.5 | null | 2011-03-24T02:07:04.620 | 2011-03-24T02:07:04.620 | null | null | 364 | null |
8710 | 1 | 8730 | null | 6 | 298 | I have 2 alternative methods to solve a problem, and I was just wondering what people who know the math better than I think, and if there is a better method to use for this type of problem.
The problem: I have a list of lat/lon positions and a value for the time interval between position updates and wish to find the SO... | Estimating speed from position updates with uncertain time intervals | CC BY-SA 2.5 | null | 2011-03-24T02:28:44.653 | 2011-03-24T21:42:40.373 | 2011-03-24T21:42:40.373 | 919 | null | [
"regression",
"estimation",
"functional-data-analysis",
"measurement-error"
] |
8714 | 1 | null | null | 3 | 6046 | Is it possible to perform logarithmic regression on multiple variables with Excel? If I just have a single independent variable than it's very easy to do this using the best-fit line option (it lets me switch from linear to logarithmic). But this feature does not work for multiple variable regression and the regression... | Performing logarithmic multiple regression with Excel? | CC BY-SA 2.5 | null | 2011-03-24T05:30:59.240 | 2011-03-24T17:34:04.710 | 2011-03-24T16:10:25.313 | null | null | [
"regression",
"excel"
] |
8715 | 2 | null | 8714 | 6 | null | If by logarithmic regression you mean the model `log(y) = m1.x1 + m2.x2 + ... + b + (Error)`, you can use `LOGEST` and `GROWTH` with multiple independent variables. Note that if you want the estimated coefficients `m1, m2, ..., b` from `LOGEST`, you'll have to enter the formula into multiple cells as an array. See Exce... | null | CC BY-SA 2.5 | null | 2011-03-24T06:26:38.550 | 2011-03-24T06:37:46.187 | 2011-03-24T06:37:46.187 | 1569 | 1569 | null |
8716 | 1 | null | null | 5 | 312 | I have a basket of time series (stock prices). I want to find the N (fixed or not) time series that will best replicate the basket in the sense that combination of them will be best cointegrated with the basket.
Beside using the N series that have the best cointegration scores (ADF test) and regressing these variables ... | Cointegration-based feature selection | CC BY-SA 2.5 | null | 2011-03-24T08:39:25.643 | 2011-04-23T20:26:08.810 | 2011-03-24T18:21:05.500 | 2116 | 3362 | [
"cointegration"
] |
8717 | 1 | null | null | 2 | 410 | Let $X_1, X_2, ..., X_n$ be a random sample from a distribution with p.d.f.,
$$f(x;\theta)=\theta^2xe^{-x\theta} ; 0<x<\infty, \theta>0$$ Obtain minimum variance unbiased estimator of $\theta$ and examine whether it is attained?
MY WORK:
Using MLE i have found the estimator for $\theta=\frac{2}{\bar{x}}$
Or as $$X\sim ... | What will be minimum variance unbiased estimator? | CC BY-SA 2.5 | null | 2011-03-24T08:44:11.823 | 2011-03-24T16:11:25.250 | 2011-03-24T16:11:25.250 | null | 3846 | [
"probability",
"estimation"
] |
8718 | 1 | null | null | 13 | 12274 | I've developed a logit model to be applied to six different sets of cross-sectional data. What I'm trying to uncover is whether there are changes in the substantive effect of a given independent variable (IV) on the dependent variable (DV) controlling for other explanations at different times and across time.
My questi... | Comparing logistic regression coefficients across models? | CC BY-SA 3.0 | null | 2011-03-24T09:06:46.867 | 2021-04-03T17:11:25.097 | 2021-04-03T17:11:25.097 | 11887 | 3883 | [
"regression",
"logistic",
"spss",
"regression-coefficients"
] |
8719 | 2 | null | 8718 | 3 | null | Are there changes across data sets? I can answer that without seeing the data! Yes. There are. How big are they? That's key. For me, the way to see is by looking. You will have odds ratios for each independent variable for each data set - are they different in ways people would find interesting? Now, it's true e... | null | CC BY-SA 2.5 | null | 2011-03-24T10:20:54.480 | 2011-03-24T10:20:54.480 | null | null | 686 | null |
8721 | 2 | null | 8704 | 3 | null | Maybe you know that if $X$ and $Y$ are independent then the pdf of $X+Y$ is given by a convolution.
You can generalize the idea of a convolution to another group than $(+,\mathbb{R})$ and the idea that pdf of $X\cdot Y$ (where $\cdot$ is the operation of the group) is given by the convolution is still valid. For the co... | null | CC BY-SA 2.5 | null | 2011-03-24T10:46:20.527 | 2011-03-24T14:24:39.583 | 2020-06-11T14:32:37.003 | -1 | 223 | null |
8723 | 2 | null | 6920 | 7 | null | You can always just perform gradient descent on the sum of squares cost $E$ wrt the parameters of your model $W$. Just take the gradient of it but don't go for the closed form solution but only for the search direction instead.
Let $E(i; W)$ be the cost of the i'th training sample given the parameters $W$. Your updat... | null | CC BY-SA 2.5 | null | 2011-03-24T10:57:37.647 | 2011-03-24T10:57:37.647 | null | null | 2860 | null |
8724 | 1 | 8727 | null | 2 | 186 | I have a database with many attributes. I would like to know which attributes has the minimum variation in the data. Is there some standard technique? It should be like clustering without split records in clusters. I would like to know what the records in particular cluster have in common.
I was going to compute the m... | Exploring data attributes | CC BY-SA 2.5 | null | 2011-03-24T11:04:28.350 | 2011-03-24T12:42:28.827 | null | null | 2719 | [
"clustering"
] |
8725 | 1 | null | null | 4 | 1346 | I tried to use the Kernel Density plot method from [Hayfield and Racine (2008)](http://www.jstatsoft.org/v27/i05/paper/) [np package](http://cran.r-project.org/web/packages/np/vignettes/np.pdf) for my own data, but somehow ended up with different type of plots and I have no idea what the difference is between my data a... | Conditional kernel density plot with R's np package | CC BY-SA 3.0 | null | 2011-03-24T11:50:53.710 | 2015-04-23T05:57:15.093 | 2015-04-23T05:57:15.093 | 9964 | 704 | [
"r",
"nonparametric",
"conditional-probability",
"kernel-smoothing"
] |
8726 | 2 | null | 8663 | 0 | null | $p-value=Pr(E||H)$ where E is the "data at least as extreme as what was observed" event, and $H$ is the hypothesis, usually of the form "some set of the parameters are zero". I have used the double lines $||$ to indicate that it is not a conditional probability per se, rather a probability based on the the assumption ... | null | CC BY-SA 2.5 | null | 2011-03-24T12:20:57.903 | 2011-03-24T12:20:57.903 | null | null | 2392 | null |
8727 | 2 | null | 8724 | 2 | null | It reminds me of what is implemented in the [caret](http://caret.r-forge.r-project.org/) package for data pre-processing. It is fully described in one of the accompanying vignette, namely [Data Sets and Miscellaneous Functions in the caret Package](http://cran.r-project.org/web/packages/caret/vignettes/caretMisc.pdf). ... | null | CC BY-SA 2.5 | null | 2011-03-24T12:42:28.827 | 2011-03-24T12:42:28.827 | null | null | 930 | null |
8728 | 2 | null | 8695 | 5 | null | The following is shamelessly extracted from the following [link](http://findarticles.com/p/articles/mi_qa3713/is_199704/ai_n8770931/pg_10/).
>
\begin{shamelesscopyandpaste}
Finally, the "average variance extracted" measures the amount of variance that is captured by the construct in relation to the amount of variance ... | null | CC BY-SA 3.0 | null | 2011-03-24T13:52:21.373 | 2014-01-21T23:11:57.833 | 2014-01-21T23:11:57.833 | 7290 | 656 | null |
8729 | 1 | null | null | 6 | 4391 | I'm trying to gain a better understanding of kmeans clustering and am still unclear about colinearity and scaling of data. To explore colinearity, I made a plot of all five variables that I am considering shown in the figure below, along with a correlation calculation.
![colinearity](https://i.stack.imgur.com/W5MZJ.jpg... | Colinearity and scaling when using k-means | CC BY-SA 2.5 | null | 2011-03-24T14:51:27.800 | 2014-01-08T01:52:15.047 | 2011-03-24T16:12:33.673 | null | 2635 | [
"r",
"clustering"
] |
8730 | 2 | null | 8710 | 4 | null | Because you trust the GPS positions (and therefore the distances computed from them) but the times have errors, regress the times against the cumulative distances.
To account for acceleration and deceleration, consider a model of the form
$$\text{Time} = t = \beta_0 + \beta_1 X + \beta_2 X^2 + \varepsilon$$
where $X$ i... | null | CC BY-SA 2.5 | null | 2011-03-24T15:33:25.113 | 2011-03-24T15:33:25.113 | 2017-04-13T12:44:53.777 | -1 | 919 | null |
8732 | 1 | null | null | 8 | 5746 | I am new to time series analysis, and would appreciate any suggestions on how best to approach the following time-series regression problem: I have hourly temperature measurements at approximately 20 locations across one site over three years, along with static ancillary information (slope, elevation, aspect, canopy co... | How to model time-series temperature data at multiple sites as a function of data at one site? | CC BY-SA 2.5 | null | 2011-03-24T18:26:43.530 | 2022-08-24T18:36:34.137 | 2011-03-25T15:08:06.370 | null | null | [
"time-series",
"regression",
"multivariate-analysis",
"spatio-temporal"
] |
8733 | 1 | null | null | 3 | 1407 | Most repeated measures ANOVAs have time as the repeated measure; I was wondering about using a repeated measure that is not time.
Say we fed two groups of animals different diets. At the end of the experiment, we sample the tissues, and measure ~30 different compounds (e.g. different fatty acids [FA]). Animals are sam... | Repeated measures with correlated measures (not time) | CC BY-SA 2.5 | null | 2011-03-24T19:02:00.630 | 2011-03-24T21:27:29.747 | 2011-03-24T21:27:29.747 | 485 | 3886 | [
"pca",
"repeated-measures",
"manova"
] |
8734 | 1 | 8740 | null | 13 | 15689 | Is there a well founded rule for the number of significant figures to publish?
Here are some specific examples / questions:
- Is there any way to relate the number of significant figures to the coefficient of variation? For example, if the estimate is 12.3 and the CV is 50%, does that mean that the information repres... | Number of significant figures to put in a table? | CC BY-SA 2.5 | null | 2011-03-24T19:15:34.247 | 2011-03-26T23:21:47.630 | 2011-03-26T23:21:47.630 | 1381 | 1381 | [
"tables"
] |
8736 | 2 | null | 8734 | 0 | null | I'd suggest 12 (1.2, 123.4). Omit the .3 since it's nearly meaningless, but many people when they see (1.2, 120) will assume that the last '0' in 120 is significant.
| null | CC BY-SA 2.5 | null | 2011-03-24T19:47:02.827 | 2011-03-24T19:47:02.827 | null | null | 2658 | null |
8737 | 2 | null | 8733 | 0 | null | It's interesting... how do you compare the compounds with each other? Repeated measures don't have to be necessarily over time, but they need to be measures of the same thing or things that can be treated as if they are the same. You could certainly measure the same compound in different areas of the body and that wo... | null | CC BY-SA 2.5 | null | 2011-03-24T20:08:10.450 | 2011-03-24T20:08:10.450 | null | null | 601 | null |
8738 | 1 | 8741 | null | 9 | 832 | It's pretty tough to search the Web for info on something when you don't know what words are commonly used to describe it. In this case, I'm wondering what it's called when you include another predictor in a time series.
As an example, say I'm modeling a variable $X$ using AR(3):
$ X_t = \varphi_1 X_{t-1} + \varphi_2 X... | What is the term for a time series regression having more than one predictor? | CC BY-SA 2.5 | null | 2011-03-24T20:25:16.957 | 2011-04-07T21:01:14.247 | null | null | 1583 | [
"time-series",
"terminology"
] |
8739 | 2 | null | 8733 | 1 | null | Have a look in a Multivariate text for MANOVA--multivariate ANOVA. Here is a website...
[http://faculty.chass.ncsu.edu/garson/PA765/manova.htm](http://faculty.chass.ncsu.edu/garson/PA765/manova.htm)
Though, that's a lot of dependent variables and it could be hard to interpret. It might be simpler to do some sort of d... | null | CC BY-SA 2.5 | null | 2011-03-24T20:29:46.690 | 2011-03-24T21:05:57.457 | 2011-03-24T21:05:57.457 | 485 | 485 | null |
8740 | 2 | null | 8734 | 19 | null | I doubt there's a universal rule so I'm not going to make any up. I can share these thoughts and the reasons behind them:
- When summaries reflect the data themselves--max, min, order statistics, etc.--use the same number of significant figures used to record the data in the first place. This provides a consistent r... | null | CC BY-SA 2.5 | null | 2011-03-24T20:37:17.667 | 2011-03-24T20:37:17.667 | null | null | 919 | null |
8741 | 2 | null | 8738 | 7 | null | ARIMAX (Box-Tiao) is what it is called when you add covariates to Arima models, is is basically arima + X.
[http://www.r-bloggers.com/the-arimax-model-muddle/](http://www.r-bloggers.com/the-arimax-model-muddle/)
Also search for Panel data or TSCS: 'Time-series–cross-section (TSCS) data consist of comparable time serie... | null | CC BY-SA 2.5 | null | 2011-03-24T20:41:18.543 | 2011-03-24T20:54:54.370 | 2011-03-24T20:54:54.370 | 1893 | 1893 | null |
8742 | 1 | 8745 | null | 2 | 2800 | There is a bayesian network Asia:
I am computing based on
```
A (visit to Asia)
S (smoker)
T (tuberculosis)
L (lung cancer)
B (bronchitis)
E (tuberculosis versus lung cancer/bronchitis)
D (dyspnoea)
X (chest X-ray)
P(A)=0.01
P(S)=0.50
P(T)=0.0104
... | Bayes Network computing conditional probabilities | CC BY-SA 2.5 | null | 2011-03-24T21:12:58.117 | 2011-03-27T01:30:17.867 | 2011-03-27T01:30:17.867 | 3681 | 3681 | [
"bayesian",
"conditional-probability"
] |
8743 | 2 | null | 8742 | 1 | null | You have to compute [joint probabilities](http://en.wikipedia.org/wiki/Joint_probability) first, and then the [marginal probabilities](http://en.wikipedia.org/wiki/Marginal_distribution) you are interested in, thanks to [sum-product](http://en.wikipedia.org/wiki/Belief_propagation).
| null | CC BY-SA 2.5 | null | 2011-03-24T22:58:02.023 | 2011-03-25T15:18:57.543 | 2011-03-25T15:18:57.543 | 1351 | 1351 | null |
8744 | 1 | null | null | 32 | 23591 | I have some points $X=\{x_1,...,x_n\}$ in $R^p$, and I want to cluster the points so that:
- Each cluster contains an equal number of elements of $X$. (Assume that the number of clusters divides $n$.)
- Each cluster is "spatially cohesive" in some sense, like the clusters from $k$-means.
It's easy to think of a lot... | Clustering procedure where each cluster has an equal number of points? | CC BY-SA 3.0 | null | 2011-03-24T23:07:21.220 | 2018-05-07T02:46:47.837 | 2018-01-14T21:04:04.177 | 7828 | 3891 | [
"machine-learning",
"clustering",
"k-means",
"unsupervised-learning"
] |
8745 | 2 | null | 8742 | 3 | null | For your four example questions, it looks rather easy, if I am reading this correctly.
The first asks for the probability the individual has tuberculosis or cancer given not having tuberculosis and not having cancer. That should be 0.
The second, third and fourth ask for the probability the individual has tuberculosis... | null | CC BY-SA 2.5 | null | 2011-03-24T23:54:20.790 | 2011-03-24T23:54:20.790 | null | null | 2958 | null |
8746 | 2 | null | 8738 | 5 | null | This is called a Transfer Function Model. It has also been referred to as a Dynamic Regression Model.
| null | CC BY-SA 2.5 | null | 2011-03-24T23:59:50.460 | 2011-03-24T23:59:50.460 | null | null | 3382 | null |
8747 | 1 | null | null | 4 | 304 | I am working on something to test advertisements. I have 3 independent variables I want to test (with mixed numbers of variations of each variable), and I would like to find the best combination of the three by looking at their effect on a single dependent variable (the percentage who purchase).
```
TITLE IMAGE D... | A test for assessing advertisement efficiency | CC BY-SA 3.0 | null | 2011-03-25T01:15:45.307 | 2011-04-12T04:34:57.197 | 2011-04-12T04:34:57.197 | 183 | null | [
"chi-squared-test",
"conjoint-analysis"
] |
8748 | 1 | 8758 | null | 8 | 272 | I am working in hospital processing infection data, and start to read more and more articles on regressions and statistics, having realized that my mathematics background is not sufficient for me to handle all the maths inside the article. I plan to do some self-study.
I have seen from [here](http://www.biostat.jhsph.e... | Introduction to maths for a junior in epidemiology | CC BY-SA 2.5 | null | 2011-03-25T02:55:34.180 | 2011-03-25T12:14:55.213 | 2011-03-25T09:29:26.643 | null | 588 | [
"references"
] |
8749 | 1 | 8928 | null | 22 | 1322 | I need to implement a program that will classify records into 2 categories (true/false) based on some training data, and I was wondering at which algorithm/methodology I should be looking at. There seem to be a lot of them to choose from -- Artificial Neural Network, Genetic Algorithm, Machine Learning, Bayesian Optimi... | How to choose between learning algorithms | CC BY-SA 2.5 | null | 2011-03-25T03:04:24.757 | 2011-03-29T15:52:01.003 | 2011-03-25T13:48:01.460 | 919 | 800 | [
"machine-learning",
"bayesian",
"optimization",
"genetic-algorithms"
] |
8750 | 1 | 8751 | null | 13 | 23587 | If I have an arima object like `a`:
```
set.seed(100)
x1 <- cumsum(runif(100))
x2 <- c(rnorm(25, 20), rep(0, 75))
x3 <- x1 + x2
dummy = c(rep(1, 25), rep(0, 75))
a <- arima(x3, order=c(0, 1, 0), xreg=dummy)
print(a)
```
.
```
Series: x3
ARIMA(0,1,0)
Call: arima(x = x3, order = c(0, 1, 0), xreg ... | How can I calculate the R-squared of a regression with arima errors using R? | CC BY-SA 2.5 | null | 2011-03-25T03:29:12.967 | 2017-11-12T17:20:50.220 | 2017-11-12T17:20:50.220 | 11887 | 179 | [
"r",
"regression",
"time-series",
"arima",
"r-squared"
] |
8751 | 2 | null | 8750 | 24 | null | Once you have ARMA errors, it is not a simple linear regression any more. So you would have to define what you mean by $R^2$. Perhaps the squared correlation of fitted to actuals? In that case:
```
cor(fitted(a),x3)^2
```
The `fitted()` function will only work if you have loaded the `forecast` package, but it looks li... | null | CC BY-SA 2.5 | null | 2011-03-25T05:19:58.357 | 2011-03-25T05:19:58.357 | null | null | 159 | null |
8752 | 1 | null | null | 9 | 385 | I want to perform quadrat count analysis on several point processes (or one marked point process), to then apply some dimensionality reduction techniques.
The marks are not identically distributed, i.e., some marks are appearing quite often, and some are pretty rare. Thus, I cannot simply divide my 2D space in a regula... | How to construct quadrats for point processes that differ greatly in frequency? | CC BY-SA 3.0 | 0 | 2011-03-25T06:00:09.103 | 2017-06-29T16:53:05.470 | 2015-12-20T18:52:58.673 | 7290 | 3699 | [
"multivariate-analysis",
"normalization",
"ecology",
"point-process"
] |
8753 | 2 | null | 8747 | 4 | null | In marketing-oriented statistics the analysis you need is called conjoint analysis. You construct a number of product "scenarios" which are various "mixes" of attributes such your 3 attributes, each being allowed to vary across some "levels". The Conjoint will tell you what's the best scenario and what are "utility" co... | null | CC BY-SA 2.5 | null | 2011-03-25T07:09:32.060 | 2011-03-25T07:09:32.060 | null | null | 3277 | null |
8754 | 1 | 8768 | null | 24 | 5040 | An interim analysis is an analysis of the data at one or more time points prior the official close of the study with the intention of, e.g., possibly terminating the study early.
According to Piantadosi, S. ([Clinical trials - a methodologic perspective](http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0471727814.html... | Why is bias affected when a clinical trial is terminated at an early stage? | CC BY-SA 2.5 | null | 2011-03-25T07:45:24.537 | 2011-03-25T16:18:10.147 | null | null | 3019 | [
"clinical-trials",
"bias"
] |
8755 | 1 | 8773 | null | 6 | 35580 | I have some data to analyze where $y$ is dependent of $x$ - a linear regression was used.
It's a question from an exam, so I think it should be solvable. The regression was used to estimate the mean miles per gallon (response) from the amount of miles driven (predictor).
I have the following statistics available:
- Co... | Calculating the mean using regression data | CC BY-SA 2.5 | null | 2011-03-25T08:22:34.893 | 2011-04-29T00:56:50.313 | 2011-04-29T00:56:50.313 | 3911 | 1205 | [
"regression",
"self-study",
"mean"
] |
8757 | 2 | null | 8692 | 3 | null | To get unstacking of `a` similar to `rbind(a,b)` you can simply transpose the result:
```
> t(unstack(a))
RSTO RSTR S1 S2 S3 SF
res 199665 4147 31274 1 2522 118009
```
You will get a `matrix` instead of `data.frame` though.
It is also possible to use the `cast` function from package reshape:
```
> cas... | null | CC BY-SA 2.5 | null | 2011-03-25T09:15:16.203 | 2011-03-25T09:15:16.203 | null | null | 2116 | null |
8758 | 2 | null | 8748 | 5 | null | Jeff Gill has a good book, on Essential Mathematics for Social and Political Research: [http://www.amazon.com/Essential-Mathematics-Political-Research-Analytical/dp/052168403X/ref=sr_1_2?ie=UTF8&s=books&qid=1301047912&sr=8-2](http://rads.stackoverflow.com/amzn/click/052168403X)
I found it quite useful for getting a goo... | null | CC BY-SA 2.5 | null | 2011-03-25T10:13:50.523 | 2011-03-25T10:13:50.523 | null | null | 656 | null |
8759 | 2 | null | 8754 | 1 | null | Well, my knowledge on this comes from the Harveian oration in 2008 [http://bookshop.rcplondon.ac.uk/details.aspx?e=262](http://bookshop.rcplondon.ac.uk/details.aspx?e=262)
Essentially, to the best of my recollection the results will be biased as 1) stopping early usually means that either the treatment was more or less... | null | CC BY-SA 2.5 | null | 2011-03-25T10:18:25.167 | 2011-03-25T10:18:25.167 | null | null | 656 | null |
8760 | 2 | null | 8690 | 7 | null | I will try to answer the questions 2 to 4. Suppose that we observe sample $(y_i,\mathbf{x}_i,z_i,\gamma_i,\varepsilon_i)$. Suppose that our model is
$$y_i=\mathbf{x}_i\beta+\gamma_iz_i+\varepsilon_i$$
and
$$E(\varepsilon_i|\mathbf{x}_i,z_i,\gamma_i)=0.$$
The least squares estimate of the regression will be
\begin{al... | null | CC BY-SA 2.5 | null | 2011-03-25T10:26:13.193 | 2011-03-28T12:08:49.257 | 2011-03-28T12:08:49.257 | 2116 | 2116 | null |
8762 | 2 | null | 8744 | 2 | null | I suggest the recent paper [Discriminative Clustering by Regularized Information Maximization](http://las.ethz.ch/files/gomes10discriminative.pdf) (and references therein). Specifically, Section 2 talks about class balance and cluster assumption.
| null | CC BY-SA 2.5 | null | 2011-03-25T11:07:50.053 | 2011-03-26T09:01:37.207 | 2011-03-26T09:01:37.207 | 3785 | 3785 | null |
8763 | 2 | null | 8754 | 1 | null | I would disagree with that claim, unless by "bias" Piantadosi means that part of the accuracy which is commonly called bias. The inference won't be "biased" because you chose to stop per se: it will be "biased" because you have less data. The so called "likelihood principle" states that inference should only depend o... | null | CC BY-SA 2.5 | null | 2011-03-25T11:15:05.500 | 2011-03-25T11:15:05.500 | null | null | 2392 | null |
8764 | 2 | null | 8748 | 3 | null | As far as learning the information on slide 6 in the slideshow you linked to, I would suggest [A Mathematical Primer for Social Statistics](http://www.sagepub.com/books/Book232153) by John Fox (not free but cheap, [Google book link](http://books.google.com/books?id=S4_VhrdIKS4C)). All of those sage green books are aime... | null | CC BY-SA 2.5 | null | 2011-03-25T12:14:55.213 | 2011-03-25T12:14:55.213 | null | null | 1036 | null |
8766 | 2 | null | 8380 | 1 | null | This sounds like something very similar to a method I have seen Jerry Reiter using multiple imputation for missing data. However I can't quite remember the name of the paper. But these terms will probably be able to get you in the right(er) direction (pardon the pun).
So basically you have three variables $X$, $Y$, a... | null | CC BY-SA 2.5 | null | 2011-03-25T13:18:27.827 | 2011-03-25T13:18:27.827 | null | null | 2392 | null |
8767 | 2 | null | 8754 | 0 | null | there will be bias (in "statistical sense") if termination of studies is not random.
In a set of experiments run to conclusion, the "early on" results of (a) some experiments that ultimately find "no effect" will show some effect (as a result of chance) and (b) some experiments that ultimately do find an effect will s... | null | CC BY-SA 2.5 | null | 2011-03-25T13:53:13.750 | 2011-03-25T13:58:46.677 | 2011-03-25T13:58:46.677 | 11954 | 11954 | null |
8768 | 2 | null | 8754 | 13 | null | First of all, you have to note the context: this only applies when the trial was stopped early due to interim monitoring showing efficacy/futility, not for some random outside reason. In that case the estimate of the effect size will be biased in a completely statististical sense. If you stopped for efficacy, the estim... | null | CC BY-SA 2.5 | null | 2011-03-25T14:10:28.553 | 2011-03-25T14:56:53.367 | 2011-03-25T14:56:53.367 | 279 | 279 | null |
8769 | 1 | null | null | 4 | 373 | I am taking a course in data mining. I am not sure how a non linear SVM when transformed to high dimensional space becomes a linear classification problem. It would be good if someone can provide me an intuition on this.
| Linear behaviour of nonlinear SVM in higher dimensional space | CC BY-SA 2.5 | null | 2011-03-25T14:54:47.357 | 2012-06-04T21:12:22.990 | 2011-03-25T14:58:14.440 | null | 3897 | [
"svm"
] |
8770 | 2 | null | 8769 | 2 | null | You should look at the problem the other way arround. SVM algorithms solve Linear classification problems in feature space. Depending on the kernel you use, the boundaries in the original space might not be linear.
| null | CC BY-SA 2.5 | null | 2011-03-25T15:09:20.313 | 2011-03-25T15:09:20.313 | null | null | 3362 | null |
8771 | 1 | null | null | 1 | 1673 | Given a factor with a number of levels, say for example, versions of a banner advertisement on a web page, where the measurement of interest is the click through rate (# clicks / # of times banner add was viewed), is there a principled way to determine the best performing ad, controlling for multiple testing?
Hsu's [M... | Multiple comparisons with binary data: Hsu's MCB method | CC BY-SA 2.5 | null | 2011-03-25T15:10:02.870 | 2011-03-26T17:18:46.097 | 2011-03-26T17:18:46.097 | null | 2040 | [
"r",
"multiple-comparisons",
"binary-data"
] |
8772 | 2 | null | 8742 | 1 | null | @darkcminor: I wonder if the following short tutorial would help you (look especially at the chain rule and the section on inference). I have not looked at these for a long time, but I believe with a few principles you can figure out the values of any query. Some of them will just be onerous done by hand.
[http://www.c... | null | CC BY-SA 2.5 | null | 2011-03-25T15:13:51.963 | 2011-03-25T15:13:51.963 | null | null | 2040 | null |
8773 | 2 | null | 8755 | 7 | null | Contrary to @whuber's claim, the mean of x and y are contained in the information given.
Okay, so you have the line equation
$$y_i=\alpha +x_i\beta + e_i$$
estimates $\hat{\beta}=r\frac{s_y}{s_x}$ and $\hat{\alpha}=\overline{y}-\hat{\beta}\overline{x}$.
where $r$ is the correlation. The question doesn't state whether ... | null | CC BY-SA 2.5 | null | 2011-03-25T15:28:23.537 | 2011-03-25T15:28:23.537 | null | null | 2392 | null |
8774 | 1 | null | null | 5 | 3350 | What is the difference between `independence.test` in R and CATT (Cochrane and Armitage) tests?
How these tests are calculated?
Where do we and how do we define x=0.0 0.5 1.0 (genetic studies) for both of the tests?
| What is the difference between independence.test in R and Cochrane and Armitage trend test? | CC BY-SA 3.0 | null | 2011-03-25T16:15:37.153 | 2012-03-15T15:11:13.880 | 2012-03-15T15:11:13.880 | 930 | 3870 | [
"ordinal-data",
"genetics",
"association-measure"
] |
8775 | 2 | null | 8754 | 3 | null | Here is an illustration of how bias might arise in conclusions, and why it may not be the full story. Suppose you have a sequential trial of a drug which is expected to have a positive (+1) effect but may have a negative effect (-1). Five guinea pigs are tested one after the other. The unknown probability of a posit... | null | CC BY-SA 2.5 | null | 2011-03-25T16:18:10.147 | 2011-03-25T16:18:10.147 | null | null | 2958 | null |
8776 | 2 | null | 8718 | 1 | null | Another tool that may be useful is the standardarized regression coefficient, or at least a rough-and-ready pseudo-version. You can obtain one such version by multiplying your obtained coefficient by the standard deviation of the predictor. (There are other versions and some debate about the best one, e.g. see Menard... | null | CC BY-SA 3.0 | null | 2011-03-25T16:37:41.953 | 2013-10-02T16:54:52.130 | 2013-10-02T16:54:52.130 | 7290 | 2669 | null |
8777 | 1 | null | null | 25 | 21498 | In [genome-wide association studies](https://en.wikipedia.org/wiki/Genome-wide_association_study) (GWAS):
- What are the principal components?
- Why are they used?
- How are they calculated?
- Can a genome-wide association study be done without using PCA?
| In genome-wide association studies, what are principal components? | CC BY-SA 4.0 | null | 2011-03-25T16:39:10.923 | 2020-09-14T18:12:48.993 | 2018-11-13T13:12:32.697 | 28666 | 3870 | [
"pca",
"genetics",
"gwas"
] |
8778 | 2 | null | 8380 | 1 | null | One approach would be to use the second dataset to make a secondary model that predicts the exact variables as a function of the noisy variables and use this in operation to provide the inputs for the primary model trained on the first dataset (which predicts the target given the exact variables). However, to do this ... | null | CC BY-SA 2.5 | null | 2011-03-25T16:48:20.410 | 2011-03-25T16:48:20.410 | null | null | 887 | null |
8779 | 1 | null | null | 20 | 11452 | This problem is actually about fire detection, but it is strongly analogous to some radioactive decay detection problems. The phenomena being observed is both sporadic and highly variable; thus, a time series will consist of long strings of zeroes interrupted by variable values.
The objective is not merely capturing ev... | Analysis of time series with many zero values | CC BY-SA 2.5 | null | 2011-03-25T18:35:44.733 | 2017-11-08T11:21:00.140 | 2017-11-08T11:21:00.140 | 1352 | 3898 | [
"time-series",
"correlation",
"crostons-method",
"intermittent-time-series"
] |
8780 | 2 | null | 8777 | 30 | null | In this particular context, PCA is mainly used to account for population-specific variations in alleles distribution on the SNPs (or other DNA markers, although I'm only familiar with the SNP case) under investigation. Such "population substructure" mainly arises as a consequence of varying frequencies of minor alleles... | null | CC BY-SA 4.0 | null | 2011-03-25T19:32:21.563 | 2020-09-14T18:12:48.993 | 2020-09-14T18:12:48.993 | 930 | 930 | null |
8781 | 2 | null | 4276 | 1 | null | Since there is quite some variation in how the steps look,
you could try a statistical approach. Which could, for example, be done
in the following steps:
- Generate the feature vector.
Filter the signal by a number of filters, each having a different
frequency response. A set foo (haar)-wavelets might be a reasonable... | null | CC BY-SA 2.5 | null | 2011-03-25T20:20:58.920 | 2011-03-25T20:20:58.920 | null | null | 3867 | null |
8782 | 2 | null | 8779 | 12 | null | To restate your question “ How does the analyst deal with long periods of no demand that follow no specific pattern?”
The answer to your question is Intermittent Demand Analysis or Sparse Data Analysis. This arises normally when you have "lots of zeros" relative to the number of non-zeros.The issue is that there are tw... | null | CC BY-SA 2.5 | null | 2011-03-25T23:55:45.633 | 2011-03-25T23:55:45.633 | null | null | 3382 | null |
8783 | 1 | null | null | 3 | 3949 | I am wondering that how one can calculate [KL-divergence](http://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence) on two probability distributions. For example, if we have
```
t1 = 0.4, 0.2, 0.3, 0.05, 0.05
t2 = 0.23, 0, 0.14, 0.17
```
The formula is bit complicated for me :(
| KL divergence calculation | CC BY-SA 2.5 | null | 2011-03-26T00:33:57.720 | 2011-04-08T20:44:20.170 | 2011-04-08T20:44:20.170 | 919 | 3900 | [
"distributions",
"machine-learning",
"distance-functions",
"information-retrieval"
] |
8784 | 1 | null | null | 14 | 4303 | This is a follow up question from [the one I asked a couple of days ago](https://stats.stackexchange.com/questions/8718/comparing-logistic-regression-coefficients-across-models/). I feel it puts a different slant on the issue, so listed a new question.
The question is: can I compare the magnitude of coefficients across... | Comparing logistic coefficients on models with different dependent variables? | CC BY-SA 2.5 | null | 2011-03-26T01:07:46.037 | 2011-04-28T00:05:39.210 | 2017-04-13T12:44:23.203 | -1 | 3883 | [
"regression",
"logistic"
] |
8785 | 2 | null | 8783 | 4 | null | Using brute force and the first formula [here](http://en.wikipedia.org/wiki/Jensen%E2%80%93Shannon_divergence) based on the first formula for the [Kullback-Leibler divergence](http://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence), you are starting from two multisets each with 5 values, 3 of which are shared... | null | CC BY-SA 2.5 | null | 2011-03-26T01:09:49.170 | 2011-03-26T01:09:49.170 | null | null | 2958 | null |
8786 | 2 | null | 8749 | 8 | null | I would use probability theory to start with, and then pick whichever algorithm best calculates what probability theory tells you to do. So you have training data $T$, and some new precursors $X$, and an object to classify $Y$, as well as your prior information $I$.
So you want to know about $Y$. Then probability the... | null | CC BY-SA 2.5 | null | 2011-03-26T05:43:34.727 | 2011-03-27T00:34:48.983 | 2011-03-27T00:34:48.983 | 2392 | 2392 | null |
8787 | 1 | null | null | 5 | 548 | I'm looking for any reference about Generalized Linear Latent and Mixed Model (GLLAMM) for Crossed Factors involving both Measurement Model and Structured Model of GLLAMM (See the problem below). Any help in this regard will be highly appreciated.
Problem: A researcher observed four responses Y1, Y2, Y3, and Y4 along w... | Generalized linear latent and mixed model (GLLAMM) for crossed factors | CC BY-SA 2.5 | null | 2011-03-26T05:58:44.600 | 2012-09-20T00:48:23.793 | 2012-09-20T00:31:58.377 | 5739 | 3903 | [
"mixed-model",
"stata",
"gllamm"
] |
8788 | 1 | null | null | 2 | 2733 | I have a problem when I run the Komogorov-Smirnov test.
I have to samples of daily prices distributions estimated with density(). Now I would like to compare these two distributions with each other.
data.1:
```
Date price
01.01.2010 1.2
02.01.2010 1.5
etc.
```
data.2:
```
Date price
01.01.2... | Goodness-of-fit test using Kolmogorov-Smirnov | CC BY-SA 2.5 | null | 2011-03-25T11:57:14.800 | 2011-04-08T20:44:41.933 | 2011-04-08T20:44:41.933 | 919 | null | [
"r",
"distributions"
] |
8789 | 2 | null | 8788 | 5 | null | ks.test receives values, not densities. So you don't need to call density().
Probably what you should do is simply:
```
ks.test(data.1$return, data.2$return)
```
and the reason why you get p=1 is that you passed `return.density.1$x` instead of `return.density.1$y`.
`density(foo)$x` is the n coordinates of the points w... | null | CC BY-SA 2.5 | null | 2011-03-25T12:23:49.427 | 2011-03-26T14:54:51.527 | 2011-03-26T14:54:51.527 | 919 | 2280 | null |
8790 | 2 | null | 8788 | 7 | null | First of all, you don't calculate the ks on an estimated density, as the ks test works on the empiric cumulative distribution function (ecdf). So you add the raw data:
```
ks.test(data.1$return, data.2$return)
```
Second, the `$x` is not the density, but the uniformly distributed grid constructed by the density functi... | null | CC BY-SA 2.5 | null | 2011-03-25T12:29:53.250 | 2011-03-25T12:29:53.250 | null | null | 1124 | null |
8791 | 1 | null | null | 6 | 104 | The best way I can think to describe this question is by example: Imagine there is a ship sailing around the pacific ocean on an unknown path (possibly random.) Other ships passing by sometimes see this ship and radio in its location to me. Some of these scout ships have better instruments or a more trustworthy crew th... | Weighted discrete measurements of a value changing over time | CC BY-SA 2.5 | null | 2011-03-26T01:54:14.677 | 2011-03-30T19:16:40.193 | 2011-03-30T19:16:40.193 | 919 | 180918 | [
"time-series",
"predictive-models"
] |
8792 | 2 | null | 8791 | 2 | null | Sounds like you might want to look at [(Weighted) Moving Average](http://en.wikipedia.org/wiki/Moving_average).
| null | CC BY-SA 2.5 | null | 2011-03-26T01:59:01.030 | 2011-03-26T01:59:01.030 | null | null | null | null |
8793 | 2 | null | 8784 | 1 | null | Let us say the interest lies in comparing two groups of people: those with $X_{1} = 1$ and those with $X_{1} = 0$.
The exponential of $\beta_{1}$, the corresponding coefficient, is interpreted as the ratio of the odds of success for those with $X_{1} = 1$ over the odds of success for those with $X_{1} = 0$, conditional... | null | CC BY-SA 2.5 | null | 2011-03-26T10:34:21.970 | 2011-03-26T10:34:21.970 | null | null | 3019 | null |
8794 | 2 | null | 8784 | 2 | null | I assume that by "my independent variable is the economy" you're using shorthand for some specific predictor.
At one level, I see nothing wrong with making a statement such as
>
X predicts Y1 with an odds ratio of _ and a 95% confidence interval of [ _ , _ ]
while
X predicts Y2 with an odds ratio of _ and a 95%... | null | CC BY-SA 3.0 | null | 2011-03-26T12:21:03.737 | 2011-04-23T15:38:48.887 | 2011-04-23T15:38:48.887 | 2669 | 2669 | null |
8795 | 1 | 8809 | null | 9 | 602 | If you flip a coin and get 268 heads and 98 tails, you can calculate the probability that coin is fair several ways. A simple, heuristic observation would have most likely conclude that such a coin is unfair. I've calculated the p-value in R with:
```
> coin <- pbinom(98, 366, 0.5)
> coin*2
[1] 2.214369e-19
```
This v... | Can a fair coin test be applied to a coin that often lands on its edge? | CC BY-SA 2.5 | null | 2011-03-26T13:29:21.417 | 2011-03-27T23:31:20.117 | 2011-03-27T23:31:20.117 | 3306 | 3306 | [
"probability"
] |
8796 | 2 | null | 5997 | 1 | null | You can try playing with spam filtering, that's quite a common use of Naive Bayesian Classifiers.
| null | CC BY-SA 2.5 | null | 2011-03-26T14:30:20.593 | 2011-03-26T14:30:20.593 | null | null | 3442 | null |
8797 | 1 | null | null | 2 | 1265 | I've made a little questionnaire where participants can rate an answer between 1 and 5. I calculated the mean value, the average value and the standard deviation.
Now I was asking myself if it is possible to calculated a confidence interval for these results and if yes, if this would tell me anything. So I just tested ... | Understanding confidence interval | CC BY-SA 2.5 | null | 2011-03-26T15:37:23.837 | 2011-03-28T13:54:58.437 | 2011-03-26T17:16:41.450 | null | 3908 | [
"confidence-interval"
] |
8798 | 1 | 14644 | null | 11 | 6363 | In the absence of good a priori guesses about the number of components to request in Independent Components Analysis, I'm looking to automate a selection process. I think that a reasonable criterion might be the number that minimizes the global evidence for correlation amongst the computed components. Here's pseudocod... | How do I select the number of components for independent components analysis? | CC BY-SA 2.5 | null | 2011-03-26T15:55:40.037 | 2016-08-31T17:10:38.983 | 2011-03-26T17:16:12.450 | null | 364 | [
"independent-component-analysis"
] |
8799 | 1 | null | null | 4 | 17943 | I have made a very simple questionnaire that asks questions that are independent of each other. Every question can be answered with a rating between 1 and 5 where 1 means I strongly disagree and 5 I strongly agree.
Now I was wondering with statistical methods I could use to evaluate the results. I know maybe I should h... | How to evaluate a simple questionnaire with statistical methods? | CC BY-SA 2.5 | null | 2011-03-26T15:57:41.113 | 2011-03-26T19:04:16.593 | 2011-03-26T16:46:53.343 | 930 | 3908 | [
"survey"
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.