Refers to any statistical complication or problem due to having few data.

learn more… | top users | synonyms

1
vote
1answer
24 views

Compare two small groups (population vs sample) over time

I am studying banks behaviour according to 6 financial rations throughout a 3-years period. I have 32 observations separated into two groups: large (6) and medium-sized banks (26). However, since in ...
19
votes
3answers
312 views

Can bootstrap be seen as a “cure” for the small sample size?

This question has been triggered by something I read in this graduate-level statistics textbook and also (independently) heard during this presentation at a statistical seminar. In both cases, the ...
2
votes
0answers
34 views

Bootstrap: the issue of overfitting

Suppose one performs the so-called non-parametric bootstrap by drawing $B$ samples of size $N$ each from the original $N$ observations with replacement. I believe this procedure is equivalent to ...
1
vote
0answers
54 views

small sample size, large number of variables (most categorical) - how to proceed?

I would be grateful for general guidance/advice about data analysis with some data that is problematic for me because of the small sample size, and the large number of categorical data. I realize this ...
1
vote
2answers
63 views

Given a series of past coin tosses from an unfair coin, how can I calculate the confidence for the next toss result?

So this is really difficult for me, but I would like to know if this is possible. Let's assume I have an unfair coin (absolutely no assumptions can be made about the coin), and my past result has ...
2
votes
3answers
253 views

Pattern mining on a small data set

I have a small data set 30 features/predictors and 30 observations. My target variable is Oil production and my predictors are well & reservoir properties (depth, trajectory, temperature, pressure ...
1
vote
0answers
7 views

Modification of categorical outcomes in small samples

I have a set of abnormal lab findings and a set of tenderness outcomes in a small sample of "cases" and "positive controls". We hypothesize there may be some lab findings which differentially affect ...
1
vote
1answer
58 views

Should a Poisson regression be carried out with only 3 data points?

I'm trying to test the relationship between the number of adults counted and the percentage heather cover over 3 areas. The data looks like this: ...
1
vote
0answers
37 views

What are appropriate validation methods for a Bayesian network model with low sample size?

I am currently using a Bayesian network model with 20 variables and 210 data points, with 15 locations measured at 14 different time points each. There are also some restrictions on what types of ...
0
votes
0answers
7 views

What are some guidelines for sample size when constructing a Bayesian Network?

Both general advice and advice specific to my case below is welcome. I'm trying to contruct a Bayesian network with 20-30 continuous variables. I have 15 locations sampled, with 14 time points each. ...
1
vote
1answer
17 views

Which non-parametric test should I run on ordinal data from a small sample?

I have one group of six raters who scored recordings of two separate six-person groups of participants, each group under separate conditions. While the participants were divided into two independent ...
0
votes
0answers
5 views

What test to use when analysing methylation differences with very small sample size?

I have not been capable of figuring out which test to use for my data, so I hope you can guide me in the right direction. I have array DNA methylation data for 5 families. From each family I have ...
3
votes
1answer
46 views

OLS regression - robust estimates for parameter's variance

I'm estimating a model for corporate social responsibility (not important). I have found my variable of interest significant at 5% confidence level. My sample is $N=84$, cross-section. For this I ...
0
votes
1answer
41 views

What are appropriate tests for goodness of fit on glm with a small sample size?

I've thought quite a lot on large sample size inference where the strong law of large numbers is easily validated. In my case however, I'm trying to infer the sign and magnitude of an outcome where ...
1
vote
0answers
22 views

Random sampling the data again to keep equal size across groups

I have an experiment with a between-group variable. It has 3 groups in total. When conducting the experiment, although we did random assignment for participants, the size of the 3 groups end up ...
6
votes
2answers
224 views

Is the sampling distribution for small samples of a normal population normal or t distributed? [closed]

If I know that the population is normally distributed, and then take small samples from this population, is it more correct to claim that the sampling distribution is normal or instead follows the t ...
1
vote
2answers
90 views

How to choose predictors for regression model

I want to predict reaction times using several personality scores. I have 9 different personality scores. My sample consists of 23 participants. Aren't there too many predictors if I put all 9 in one ...
0
votes
0answers
27 views

Best estimator for small samples

I have a sample of an unknown distribution for which I would like an estimate of the true value and the expected error on that estimator. Since the underlying distribution is not necessarily Gaussian ...
1
vote
1answer
53 views

For a T-test, what would happen if one of my samples was made up of only one observation? [duplicate]

I must be missing something, or under-thinking what goes on with a basic T Test, but I was under the impression that if I do a T-test, and one of my samples was made up of only one observation, the ...
2
votes
1answer
53 views

Small sample, many observations. Is the sample large enough?

I am working on a project regarding the influence of temperature and other variables on the sales of 3 branches of one local bakery. The research goal is to be able to better predict bakery sales (in ...
1
vote
0answers
14 views

How to create a weekly alert system that works for different sample sizes?

I'm trying to build a weekly alert system to let me know when something unusual has happened in my analytics data that might require further investigation. Currently there is an outdated system in ...
3
votes
1answer
44 views

Can Poisson regression be run with a small sample?

I am just a beginner. I have a sample of 71. I wish to do a Poisson regression. Is this sufficient for estimating a Poisson model? Should I use only counts as $Y$ variable or should I use percentages ...
1
vote
0answers
14 views

Methods for analysing effects of percentage mortality on population data with zero/low abundances

I want to analyse the effects of percentage mortality from two sources (a predator and a disease) on the population abundance of a host measured at 12 sites for 8 years, with the main aim being to ...
1
vote
1answer
72 views

How to model a skewed Student's t disribution

I have a small number of samples (5) of a large population (~10,000). The samples are percentages and hence I know from the context that no answers are possible below 0% or above 100%. From this one ...
2
votes
0answers
42 views

How can I tell if I my sample size is large enough for reliable feature selection using LASSO regression?

I have a gene expression dataset with 20 samples, and am not going to be getting any more. There are ~28,000 genes and four clinical covariates associated with each sample. The gene expression values ...
1
vote
0answers
38 views

repeated measures design between subjects with non normal and small N

I’m examining the effects of a parent-delivered reading intervention on 11 child outcome variables at 3 different time points (pre, post-intervention and follow-up) with a control group. Total sample ...
2
votes
0answers
67 views

Big Data? Have we solved Small Data yet? [closed]

There has been a lot of attention on Big Data recently, where the problems are often more logistical (how to deal with large volumes of data) rather than statistical. At the other end of the spectrum ...
1
vote
1answer
31 views

How to expand sample subset with similar data

I would like to categorize a large sample and make some estimates for each category aka subset. The problem is that some subsets contain very few data points. How do I deal with that? For example: ...
1
vote
0answers
85 views

Why are small sample sized avoided in meta-analyses?

In most meta-analyses that I've read, the authors choose to exclude studies with really small sample sizes (e.g n=10). Why is that? Speculation I could speculate that one reason is that since the ...
1
vote
1answer
132 views

Suggest models for prediction based on small sample data

I am not a traditional statistics guy. I am from an electrical engineering background. So, spare me for lack of jargon. The model is to be used for predicting agricultural output based on previous ...
2
votes
2answers
65 views

Comparing different conditions on a binomial distribution

I have some data where I have tested a binomial random variable under 4 conditions. The null hypothesis is that they all have equal means, alternative hypothesis is that one or more means differ from ...
2
votes
1answer
39 views

What test of significance is best suited to compare concentrations, with only one sample of each population?

I have two large reservoirs of water with unknown concentrations of bacteria. I have only one sample of each reservoir: Sample of reservoir A: volume of the sample $=V_1$, number of bacteria in the ...
1
vote
1answer
36 views

(very basic) One-sample test for binary data

I've repeatedly measured a continuous variable and each measure has been assigned a populational percentile range it falls into (percentile ranges were estimated for general population in another ...
4
votes
3answers
296 views

Regression for really small data with high degree of multicollinearity and outliers

I'm working on a promotional response analysis. I have a really small real world dataset with 25 observations and 15 variables. The variables have a high degree of multicollinearity and some have ...
0
votes
1answer
81 views

Testing difference between two means. Skewed ( N1=21) vs Symmetric bell (N2=47). Wilcoxon rank sum test appropriate?

I need to test to compare the means of two samples, one with size 21 and the other with size 47. Histograms show Sample 1 is skewed to the right while Sample 2 has a bell symmetrical shape. ...
0
votes
0answers
46 views

Chi-square / Fisher test variable independence for an individual

I have a data set of $\approx$100 individuals showing pulse rate before exercise, pulse rate after exercise, sex, smoker status, weight etc. for each individual. I've been asked to select an ...
3
votes
0answers
165 views

Mixed ANOVA: small and unbalanced samples

I have to analyze two samples ($n_1=10, n_2=18$) in a design in which there is a between-subject factor (Groups: 2 levels) and a within-subjects factor (...
1
vote
0answers
89 views

Alternatives to a train-test split with a small data set

Let's say I have a small data set (~50 observations) and 50 or so explanatory variables, and I want to develop a linear model for the sake of prediction. First, I want to construct a correlation ...
0
votes
1answer
81 views

Panel data regression specifications

I am currently working with a panel data in which I have 6 countries, and the analysis is for 10 years. That is $n=6$ and $t=10$. Is it a good panel? I am really getting confused as people question ...
0
votes
0answers
33 views

literature on small samples and parametric survival models

I have an abundance of small data sets with right-censored data. There are different groups in each data set and I'd like to get confidence intervals for the regression parameters. Each data set has ...
0
votes
0answers
57 views

Sample size for SEM. What are the alternatives

I have 3 latent variables with 3 measures each. I understand the conventional sample size would be 15 participants per measure (i.e. 9 x 15 = 135). I have 85 participants and don't think I will have ...
6
votes
4answers
3k views

Warning in R - Chi-squared approximation may be incorrect

I have data showing fire fighter entrance exam results. I am testing the hypothesis that exam results are dependent on ethnicity. To test this, I ran a Pearson chi-square test in R. The results show ...
4
votes
1answer
710 views

How to choose train/test sample ratio, for machine learning?

I am building a real time machine learning module, which is not based on a huge** sample size, with hyper parameter grid search and cross validation process. I am looking for any insight/advice, as ...
0
votes
0answers
48 views

Sample size for binary text classification

In my application as a Binary text classification, one class has around 36,000 sample and another one has around 300 samples. I under-sample the first class. So, each class will have ~ 300 samples. ...
3
votes
0answers
112 views

Bootstrapping fits to a small sample

I have a sample of experimentally measured survival times that are quite noisy and vary stochastically. The survival probability of these events (number of events with a survival time of t or more) is ...
0
votes
0answers
19 views

Applying the distribution of a large sample to estimate probability for a smaller sample

I have the sample size, mean and standard deviation for the number of births per year for my county, but I'd like to transfer that information to a smaller population within the county (ie. a school ...
0
votes
0answers
66 views

CLT in a Monte Carlo simulation, small sample

A CLT says that asymptotically the sampling distribution of the sampling mean converges to the Normal. I would like to run a Monte Carlo simulation using information on one of the model's variables ...
1
vote
3answers
127 views

Distribution of a sample from a normal population

If I were to collect ONE sample of size 20 from a normal population, how justified would I be in claiming that the sample is normally distributed? I'm getting a little confused since by the Central ...
0
votes
0answers
168 views

data mining/predictive modelling methods for small data sets

I have a small timeseries dataset that has 30 records with 6 predictor variable and 1 response variable. I would like to regress my time series response with 6 predictor variables. I have been using ...
2
votes
2answers
102 views

Bernoulli Confidence Intervals for p very close to 0

Let's say I have the following observations from many Bernoulli distributions with different p (p1, p2, ..): Observations from Distribution 1: 10 successes, 100,000 trials, p_hat = 0.0001 ...