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Before you begin reading, I want to say thank you for helping, or attempting to help me. I really appreciate any help you can give me! Also, warning: Wall of Text approaching fast.
I've been informed that I am misusing the term Confidence Interval. I have been told that what I am actually looking for is the "Prediction... |
Does anyone know an implementation in R (or other) of a decision tree for censored outcomes? I would like to utilize a decision tree in order to discretize/bin continuous variables before a survival analysis in some sort of principled manner. I am left with only a traditional decision tree using a binary target (event/... |
I am not a statistician and hope someone can point me towards the right direction. I have some time series data grouped into three classes like this:
Time Period 1 Time Period 2 Time Period 3
-------------------------------------------------
[1,2,3,4,5,6...] [12,13,14,15] [17,3,1,3,4...]
[1,3,5,6,8,9..... |
Two random variables are defined as subindependent if their covariance is zero--in other words, if they are uncorrelated. The latter link notes that "not all uncorrelated variables are independent. For example, if $X$ is a continuous random variable uniformly distributed on $[−1, 1]$ and $Y = X^2$, then $X$ and $Y$ are... |
I just read: http://www.r-statistics.com/2010/02/post-hoc-analysis-for-friedmans-test-r-code/
Here is the example from the blog post:
Let’s make up a little story: let’s say we have three types of wine (A, B and C), and we would like to know which one is the best one (in a scale of 1 to 7). We asked 22 friends to tast... |
My data takes the form of a stream of events for each customer in my sample. For a given customer, the stream takes the form of a list of events over time:
At T1, customer C1 bought 1 unit of product X
At T2, customer C2 bought 1 unit of product X
At T3, customer C1 contacted customer service
At T9, customer C1 boug... |
Thanks to Tormod question (posted here) I came across the Parallel Sets plot. Here is an example for how it looks:
(It is a visualization of the Titanic dataset. Showing, for example, how most of the women that didn't survive belonged to the third class...)
I would love to be able to reproduce such a plot with R. I... |
I have read the Wikipedia pages for Friedman's and Kruskal-Wallis' test, but I am not sure which one to use. Are there differences in the assumptions?
|
I am new to CrossValidated so hope this question is appropriate... apologies if not.
I am studying the stability of a molecule 'B' and have data on the recorded level at different time points. Molecule B actually increases over time due to the fact that its parent molecule, AB, is decaying releasing it (and A): AB -> A... |
I have a data table detailing various histological parameters among 3 groups of patients- DLE, SCLE and ACLE.
I would like to know how we could do an analysis on the strenghth of the association of a parameter with a particular group.
|
I am looking for the formula of the confidence interval for the difference between means in a one sample t-test. I have only been able to locate the formula for a two sample t-test.
Let me give an example: I have the following ten scores
10,12,13,11.5,9,11,11.1,11.9,12.1,9.3
I want to know if the mean of these scor... |
I quote this question from "All of Statistics":
Suppose a gene can be type A or type
a. There are three types of people
(called genotypes): AA, Aa, and aa.
Let (p, q, r) denote the fraction of
people of each genotype. We assume
that everyone contributes one of their
two copies of the gene at random to
th... |
I'm writing Python code to use the Kalman State-space approach to estimate ARMA model coefficients using MLE however, I'm not too clear on how to derive the coefficient estimates standard errors from the process.
I know you have to use the information matrix, invert it to get the variance-covariance matrix and you can ... |
Is there a way that once a complex classification tree is constructed using rpart (in R), to organize the decision rules produced for each class? So instead of getting one huge tree, we get a set of rules for each of the classes?
(if so, how?)
Here is a simple code example to show examples on:
fit <- rpart(Kyphosis ~ ... |
I have a series of observations $\{X_i,Y_i,Z_i\}$ for random variable $X$, $Y$ and $Z$. Now I want to test if $X$, $Y$ and $Z$ are mutual independent, can anyone help me?
Some pairwise independence tests like this one http://www.gatsby.ucl.ac.uk/~gretton/indepTestFiles/indep.htm are available, but I haven't found such ... |
Using a logarithmic regression tool found at xuru.org ( http://www.xuru.org/rt/LnR.asp#CopyPaste ) and the data from below, the curve of the graph for this data is roughly described by y = 31.78303295ln(x) - 36.17569359, which has an RSS value of 10877.59526. My goal is to find an equation that describes the data accu... |
how can I add a label to the max value of this plot:
qplot(c, data=subset(df,c < 3000),geom="freqpoly")
c is just integers
|
I've learnt that I must test for normality not on the raw data but their residuals. Should I calculate residuals and then do the Shapiro–Wilk's W test?
Are residuals calculated as: $X_i - \text{mean}$ ?
Please see this previous question for my data and the design.
|
I fit a cubic function (in mathematica)
$$
y(x) = a + b x + c x^2 + d x^3
$$
to my data and obtained a function.
I have the error in each coefficient ($\sigma_a$, $\sigma_b$, $\sigma_c$, $\sigma_d$). Now since I need the model to predict $y$ values for a given $x$ value, I also need a corresponding error for the $y$ ... |
Why are the percentages in the y-axis of this bar chart displayed incorrectly (values larger than 100%) and how can I fix it?
qplot(tctype,tccount,data=categ,xlab="Type",ylab="",geom = "bar")+ scale_y_continuous(formatter="percent")
This is the data frame
categ
tctype tccount
1 inthread (10 or less... |
I have a dataset:
X variable is date (from April to October)
Y variable is vegetation biomass data
In my study area, growing season starts around April when vegetation biomass is low and peaks around at the end of August when biomass is highest, and finishes around October.
The purpose is to determine the exactly ... |
Feature or bug? Why is it that the tick marker for zero projects is after the bar that represents the count for zero in this plot (instead of being in the middle as I'd have expected):
> qplot(projects,data=subset(df,projects<1000),geom="bar")
stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this... |
What are the most widely used measures of predictive power of attributes in scoring models?
Motivation: I have a lot of attributes, more than I can study by myself and I want to select somehow the most promising ones. Is IV a good criterion for that? Are there any alternatives?
|
I've described a typical design for my experiments in this question. Well, 1-way RM ANOVA assumes a Gaussian distributed vector.
I try $y=\arcsin{\sqrt{x}}$. But for some data it works, for some doesn't... So the next step is to find the most powerful/general statistics. Freeman — Tukey's transformation with $y=\sqrt{x... |
I am using libsvm (which is meant for solving binary classification problems) for multi-class classification. How can I get classification scores / confidences for each class to effectively compare them given that libsvm can only produces scores for two classes. Desired output:
Class 1: score1
Class 2: score2
Class 3... |
This is for a friend of mine. As an econometrician used to rely on large samples for inference, I find myself unsure whether the answer I have in mind is the best.
Suppose we have four continuous random variables, X, Y, W and Z. We have a small (5 to 10 observations) iid sample from each.
We want to test whether $\frac... |
Assume $X$, $Y$ are independent zero mean random variables. Define $Z_1=X+Y$ and $Z_2=X-Y$. Then, their mean values are the same.
How does one check that $Z_1$ and $Z_2$ are not the same random variables?
And how to describe their variances?
|
I want to estimate $n+m$ parameters with the equation:
$$\hat\theta=\left[\frac{1}{N}\sum_{t=1}^N \varphi(t)\varphi^T(t)\right]^{-1}\left[\frac{1}{N}\sum_{t=1}^N\varphi(t)y(t)\right]$$
where $\varphi$ is a vector of regressors and $\theta$ the vector of parameters.
Then my book derive an expression for the estimation e... |
I work in the loss forecasting area and would like to know a little bit more about the theory and implementation of age-period-cohort models. Several papers pop up in google search but I need a more comprehensive material relating to identification/estimation. Thank you.
|
I am planning to perform an online behavioral survey across a nationwide sample, and I expect several thousand responses. I expect to have not that many questions (perhaps 3 pages, 8 qs each), require skip logic, and would like it to redirect back to a page of my choice. I also need it to be hosted, as local webhosti... |
I have some data which is clearly truncated on the left. I wish to fit it with a density estimation that will handle it in some way instead of trying to smooth it down.
What known methods (as usual, in R) can address this?
Sample code:
set.seed(1341)
x <- c(runif(30, 0, 0.01), rnorm(100,3))
hist(x, br = 10, freq = F)
... |
I have two groups (G1, n=10; G2, n = 10) each representing a separate condition.
Participants in each group answered 20 questions and each question is a dichotomous variable coded 0 and 1 (VDD).
I want to compare the group 1 with group 2.
I am having some trouble understanding if I have it right, for every participant... |
I want to measure the inner correlation of the occurrences of events i.e. I want to distinguish between the two (drawn) and say "in the second sample events occur more conglomerate compared to the first":
Isn't this different from burstiness (i.e. easier to compute as it doesn't invole traffic-values)?
I have drawn a ... |
X,Y are independent random variables.
X's pdf = f(x)
Y's pdf = g(x)
if Z= X+Y
what is the Z's pdf?
Can it be calculated?
|
Why $z=f(x)$ does not imply $E[z]=f(E[x])$ when f is not linear?
I can give an example, but I couldn't derive the general form.
Let $z = {x^2}$
Let $g(x)$ be the pdf of $x$. Then:
$ E\left[ z \right] = E\left[ {{x^2}} \right] = \int\limits_{ - \infty }^\infty {\left( {{x^2}} \right)g\left( x \right)dx} $
$f\left( {E\l... |
My textbook gives an example, that normal distribution family $\{N(0,\sigma^2):\sigma\in R^+\}$ is not complete, but a complete statistic, $T_n=\sum_{i=1}^n X_i^2$, can still be constructed from samples $(X_1,\cdots,X_n)$.
So under what (sufficient / necessary) conditions can we draw complete statistics from an incompl... |
I have data which consist of three longitudinal series of financial data. The hypothesis is that two of the series are "caused" (in a loose sense) by the third. It is fine to investigate this as two separate hypotheses. All the series are about the relationship between two specific countries. There are data for abo... |
I'm reading an article, The commonality of neural networks for verbal and visual short-term memory (Majerus et al., J Cogn Neurosci 2010 22(11): 2570), about brain imaging in which the results are analysed with multiple analyses.
One of them is a null conjunction analysis.
I've tried googling a bit but I didn't come up... |
I read that in Bayes rule, the denominator $\Pr(\textrm{data})$ of
$$\Pr(\text{parameters} \mid \text{data}) = \frac{\Pr(\textrm{data} \mid \textrm{parameters}) \Pr(\text{parameters})}{\Pr(\text{data})}$$
is called a normalizing constant. What exactly is it? What is its purpose? Why does it look like $\Pr(data)$? Why... |
The definition for the $k$-th lag auto correlation is $Cov(y_t,y_{t-k})/Var(y_t)$.
My question is why should not it be $Cov(y_t,y_{t-k})/[Var(y_t)\cdot Var(y_{t-k})]^{0.5}$.
In another words, what is it different from the correlation coefficient between $y_t$ and $y_{t-k}$?
|
Following the design and data described in this question, I did a simple one-way within-subjects repeated-measures (RM) ANOVA and found some significant p-values. I then applied non-orthogonal post-hoc Tukey's HSD tests, and when I got significant results I applied Holm-Bonferroni (1979) correction. Whenever some p-val... |
I want to estimate the parameters of a function of general form $y = a \cdot x^b$. I applied a log-log transformation to obtain a linear function of the form $\log y = \log a + b \times \log x$. I have fitted the linear model in MATLAB.
MATLAB computes the goodness of a fit in terms of sum of squares error (SSE) and (a... |
I have the following function $Y = \alpha\ln(x)$, $\alpha$ is a constant. Question:
(a) What is the expression for the derivative of Y with respect to x?
(b) what is the elasticity of Y wrt. x?
|
I'm trying to interpret a significant three-way interaction. Basically, I've used hierarchical regression to analyse my data, and I have come up with a significant three-way interaction.
My DV is continuous. My 3 IVs are continuous, categorical (2 levels), and another categorical (3 levels). My sample size is 194.
I kn... |
In other contexts, orthogonal means "at right angles" or "perpendicular".
What does orthogonal mean in a statistical context?
Thanks for any clarifications.
|
I would like to estimate the distribution of a very large population of known size but unknown mean and variance. I cannot assume anything about the shape of the underlying distribution (although I am relatively certain that it is not normal). However, I am certain that the values in the population are non-negative, no... |
How to reproduce MS Excel's CHIDIST function in MATLAB?
Returns the one-tailed probability of the chi-squared distribution. The χ2 distribution is associated with a χ2 test. Use the χ2 test to compare observed and expected values. For example, a genetic experiment might hypothesize that the next generation of plants w... |
Say I have n sets of data where each set of data has a binomial distribution. The n sets of data are then combined into one set.
If I take the combined set of data, how would I go about detecting that this set is made up from n individual sets ?
I have only a limited background in statistics, so here is an example to ... |
Can anyone explain the primary differences between conditional inference trees (ctree from party package in R) compared to the more traditional decision tree algorithms (such as rpart in R)?
What makes CI trees different?
Strengths and weaknesses?
Update: I have looked at the paper by Horthorn et al that Chi refers t... |
I am doing a review of statistical methodology used for microRNA data obtained from Affymetrix platform. I have data from 178 patients and their prognosis information as well as recurrence of disease and survival outcome (dead/alive).
I learnt that I can treat recurrence rate to separate patients into two groups (recur... |
I have been using a statistic to measure "influence" or some analogous concept in the following way:
First calculate the mean for a given sample, then calculate the mean for the given sample excluding each observation in turn. Subtract the latter from the former. The result is a vector measuring the amount by which the... |
If the model does not satisfy ANOVA assumptions (normality in particular), if one-way, Kruskal-Wallis non-parametric test is recommended. But, what if you have multiple factors?
|
As a means of motivating the question, consider a regresison problem where we seek to estimate $Y$ using observed variables $\{ a, b \}$
When doing multivariate polynomial regresison, I try to find the optimal paramitization of the function
$$f(y)=c_{1}a+c_{2}b+c_{3}a^{2}+c_{4}ab+c_{5}b^{2}+\cdots$$
which best fit the... |
When running the Metropolis-Hastings algorithm with uniform candidate distributions, what is the rationale of having acceptance rates around 20%?
My thinking is: once the true (or close to true) parameter values are discovered, then no new set of candidate parameter values from the same uniform interval would increase... |
I have a large data.frame in R. I would like to double if its distribution fit normal distribution or extreme value distribution better
Here is my simplified data.frame.
x <- data.frame(A=c(1,3,1,5,4,5,5,7,3,2,2,1,1,1,4,9,10))
Could you mind to let me know how to do so? Can I did this analysis with R?
|
I have a binary dependent variable, say food security status, where 0 = food insecure and 1 = food secure, and this response variable is recorded for two categories of households, small farmers and land less rural house holds. Both these household categories may have food secure or food insecure.
These dependant varia... |
In machine learning and in statistics there exist plenty of measures which estimate the performance of a predictive model. For example, classification accuracy, area under ROC curve ... for classification or $R^2$ for regression models.
Is there any generalisation of such measures for multiple dependent variables in or... |
I am wondering if somebody has used or has any reference to point as to how a neural network in conjunction with PROC logistic can be used in sas. A code would be an ideal thing for me but if unavailable, if somebody can pass me a link as to how can I benefit myself from using neural network alongside logistic ?
|
We sometimes use spectral density plot to analyze periodicity in time series. Normally we analyze the plot by visual inspection and then try to draw a conclusion about the periodicity. But have the statisticians developed any test to check whether any spikes in the plot are statistically different from white noise? Hav... |
I am currently bothered on how to statistically analyze my simple data as shown below.
Date Spatial Features
1 2 3 4 5 6
----------------------------------------------
1988 0.7784 0.8310 0.8726 0.9307 0.9189 0.8814
1998 0.8956 0.9036 0.9368 0.9575 0.9283 0.9045
2009 0.92... |
Inspired by Peter Donnelly's talk at TED, in which he discusses how long it would take for a certain pattern to appear in a series of coin tosses, I created the following script in R. Given two patterns 'hth' and 'htt', it calculates how long it takes (i.e. how many coin tosses) on average before you hit one of these p... |
I was a bit confused with the meaning of $\beta$, and thought its usage was rather loose. In fact, it seems that $\beta$ is used to express two distinct concepts:
The generalisation of the sample "b coefficient" to the population concerned.
The standardized regression coefficients (regression coefficients obtained whe... |
I would like to estimate the distribution of a very large population of known size but unknown mean and variance.
I cannot assume anything about the shape of the underlying distribution. However, I am certain that the values in the population are non-negative, non-zero integers. I believe that the distribution is natu... |
I'm hoping someone here is able to help me refine a linear regression model I'm working on at work. I am in no way a statistician, but I guess I have the most experience (basic stats course and decently capable with excel) in my office.
I've been tasked with creating a model that would help predict condo prices (depend... |
I am reading a text, "Probability and Statistics" by Devore. I am looking at 2 items on page 740: the expected value and variance of the estimation of $\beta_1$, which is the slope parameter in the linear regression $Y_i = \beta_0 + \beta_1 X_i + \epsilon_i$. $\epsilon_i$ is a Gaussian($\mu = 0, variance=\sigma^2$) ran... |
Nearly every decision tree example I've come across happens to be a binary tree. Is this pretty much universal? Do most of the standard algorithms (C4.5, CART, etc.) only support binary trees? From what I gather, CHAID is not limited to binary trees, but that seems to be an exception.
A two-way split followed by ano... |
I am looking to do a canonical correlations analysis (CCA) in R, using the CCA package, on a multiply imputed dataset (obtained from the mice package).
I know that the mice package allows you to pool the complete data sets and do linear models and general linear models using formulas, e.g.:
mice.data <- mice(data, m = ... |
Generating n random variables whose summation will be 1. [I got the answer.]
EDIT
On genetic algorithm, we have to maintain population. Say, I have two individuals a and b. Every individual consists of $n$ pairs of ($x_i, \theta_i$), where $ 0 \leq i < n$. A fitness function evaluates fitness, $f$ of every individual. ... |
I have bivariate data from which I have generated thousands of bootstrapped estimates within each of two conditions (pink & blue):
I'd like to determine whether these conditions' bivariate distributions have different central tendencies.
If I were dealing with univariate data, I'd compute, within each point, the .025... |
If one wanted to use Kernel Regression in a Bayesian Framework, any ideas on how one would go about it?
Kernel Regression
|
I'v been playing around with back propagation, trying to see if I can find a solution to the XOR problem using a 2-2-1 network. Based on my simulations and calculations, a solution is not possible without implementing a bias for every neuron. Is this correct?
|
Suppose we have $N$ measurable variables, $(a_1, a_2, \ldots, a_N)$, we do a number $M > N$ of measurements, and then wish to perform singular value decomposition on the results to find the axes of highest variance for the $M$ points in $N$-dimensional space. (Note: assume that the means of $a_i$ have already been sub... |
Let's say that I have a population of 10000, and I have a sample of 300 that have responded to an online survey. Of 10000 invitations, 300 hundred have replied. Would I be able to use the finite population correction for margin of error?
Population: 10000
Sample: 300
Response: 3%
|
I was wondering, given two normal distributions with $\sigma_1,\ \mu_1$ and $\sigma_2, \ \mu_2$
how can I calculate the percentage of overlapping regions of two distributions?
I suppose this problem has a specific name, are you aware of any particular name describing this problem?
Are you aware of any implementation ... |
My logistic regression model seems to identify successes very well (about 85% - 94%), but fails to identify the failures (only identifying 18% - 32% correctly).
I have thought of weighting the success and failures differently, but I am not sure of how to do this R. I have tried:
Fr <- ifelse (y==0, 2, 1)
model <- glm(... |
I've been looking at attendance data for a college library taken during finals week when the library was open for 24 hours. However the staff only took head counts during the hours of 12am to 6am (7 data points per night, for about 11-12 nights, 3 semesters worth of similar counts). I was wondering if, because the data... |
I am trying to figure out how to control the smoothing parameters in an mgcv::gam model.
I have a binomial variable I am trying to model as primarily a function of x and y coordinates on a fixed grid, plus some other variables with more minor influences. In the past I have constructed a reasonably good local regressio... |
My shortened data is:
y <- c (2,2,1,5,6,7,1,2,1,6,6,7,3,2,4,4,4,4,3,3,9,1,1,9)
I firstly normalize my data:
y_scale <- scale(y)
Then, I generate a model dataset with normal distribution based on y_scale's mean and stdev:
y_norm <- rnorm(n=24, m=mean(y_scale), sd=sd(y_scale))
To check if my data fits the normal distr... |
I have a data set with a dependent variable on a scale from 0 to 100 (n=198). The problem is that many subjects (25) scored exactly 100 but below 100 every score is achieved only once.
This distorts the histogram as you can see on the following link:
I'm trying to run an ANOVA (regression with two contrast coded pred... |
How can I calculate the $\alpha$ and $\beta$ parameters for a Beta distribution if I know the mean and variance that I want the distribution to have? Examples of an R command to do this would be most helpful.
|
I know goodness-of-fit can be used to check the goodness between one dataset and a distribution type. I wonder if it is possible to get the goodness for two dataframe in R?
e <- c(1,1,1,1,3,3)
f <- c(2,2,2,2,4,5)
g <- goodfit(e,f, method="MinChisq")
Error in match.arg(type) : 'arg' must be NULL or a character vector
|
Apologies for newbie question but have failed to understand what I've read about in this area so pointers to the correct methods would focus my attention.
I have a piece of software which when tested repeatedly in the same way fails occasionally - say once in 20 runs.
If I make a change to fix the problem, how many tim... |
I have a large set of data points of the form (mean, stdev). I wish to reduce this to a single (better) mean, and a (hopefully) smaller standard deviation.
Clearly I could simply compute $\frac{\sum data_{mean}}{N}$, however this does not take in to account the fact that some of the data points are significantly more a... |
Select $n$ numbers without replacement from the set $\{1,2,...,m\}$, and generate the set $S=\{a_1,a_2,...,a_n\}$. I want to calculate the expectation of the variance for the sampling set $\mathbb{E}[Var(S)]$ and the maximum variance among all samples : $\max{Var(S)}$.
Besides, what's the distribution of the sample var... |
I have a mixed model with a continuous outcome variable and a certain number of predictors. Some need to be included in the model no matter what (sex, age, and a "main factor"), and others must be selected from a list of potential confounders.
I know some software packages have very well developed procedures to do prop... |
I have a large dataset (500000 data, V1 column include all the data).
x <- read.csv("mydata.csv", header=F)
hist(x)
Which gives:
Looking at the data, I believe it is not a normal distribution. As a further check, I constructed a qqplot:
x_norm <- (x$V1 - mean(x$V1))/sd(x$V1)
qqnorm(x_norm); abline(0, 1)
which gave:
... |
I've got a weird question. Assume that you have a small sample where the dependent variable that you're going to analyze with a simple linear model is highly left skewed. Thus you assume that $u$ is not normally distributed, because this would result in normally distributed $y$. But when you compute the QQ-Normal plot ... |
Does anybody know a good book/webpage to start learning the techniques of cross validation?
|
It seems to me that to choose the right statistical tools, I have to firstly identify if my dataset is discrete or continuous.
Could you mind to teach me how can I test whether the data is discrete or continuous with R?
|
My data has following distribution:
I wish to determine if it is a Normal distribution, so:
> library(nortest)
Warning message:
package 'nortest' was built under R version 2.12.2
> sf.test(y)
Error in sf.test(y) : sample size must be between 5 and 5000
> ad.test(y)
Anderson-Darling normality test
data: y... |
Linear systems of equations are pervasive in computational statistics. One special system I have encountered (e.g., in factor analysis) is the system
$$Ax=b$$
where $$A=D+ B \Omega B^T$$
Here $D$ is a $n\times n$ diagonal matrix with a strictly positive diagonal, $\Omega$ is an $m\times m$ (with $m\ll n$) symmetric pos... |
I am trying to forecast time series of stock for a particular case in which closing value of the stock depends on independent factors which is in which infact another time series.
Situation is like I have to predict value for tomorrow's stock based on some independent variables which are also defined for each day. One ... |
Problem
I am writing an R function that performs a Bayesian analysis to estimate a posterior density given an informed prior and data. I would like the function to send a warning if the user needs to reconsider the prior.
In this question, I am interested in learning how to evaluate a prior. Previous questions have co... |
I know ad.test() can be used for testing normality.
Is it possible to get ad.test to compare the distributions from two data samples?
x <- rnorm(1000)
y <- rgev(2000)
ad.test(x,y)
How can I perform the Anderson-Darling test on 2 samples?
|
I have a vague sense of what a message passing method is: an algorithm that builds an approximation to a distribution by iteratively building approximations of each of the factors of the distribution conditional on all the approximations of all the other factors.
I believe that both are examples Variational Message Pa... |
I'm trying to report the results of my chi-square test for independence in APA format but these results don't resemble the examples I've seen especially the 4 digits before the period in the chi-square test results i.e. 9355.19 and 9556.44. Am I doing this right?
"the χ2 tests showed significant
results in the as... |
Suppose 10 people conduct a 10 studies which rank people's top five favorite colors. For instance, one survey may produce a list 1) red 2) blue 3) green 4) yellow 5) orange, where red is the favorite color on the list and orange is the least favorite on the list.
The methodology of the 10 surveys are completely differ... |
I have the admission for 4 different hospitals (coded as binary) which are regressed on a list of independent variables.
The multinomial logistic provides the odds ratio (O.R.) for independent variable for each hospital and then compare this to a reference hospital.
Can I add each of the O.R. from each independent vari... |
I am trying to control a binomial proportion that hovers pretty close around 0.1% - 1.0%. Since it seems like dropping from 0.1% to 0.05% is equally as severe as increasing to 0.2% (halving the occurrences, doubling the occurrences), it makes sense to me to use geometric mean / standard deviation. Also, by using geom... |
I'm building a system to alert when the proportion of successes to attempts goes out of control. To visualize the data, I've produced some rolling control charts to get an idea of when things would have alerted.
A sample of one such chart is here, roughly labeled in photoshop for some clarification:
Since each interv... |
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