Questions tagged [eda]

EDA stands for "Exploratory data analysis". Developed by Tukey to contrast with Confirmatory Data Analysis or CDA (the formal testing of hypotheses). EDA is typically concerned with describing data numerically and graphically to make the data easier to understand and to yield new insights.

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Identifying health profiles from a large datset

I have three concepts that I am trying to relate to each other. Health/Cognition/Lifestyle For each of the concepts I have over twenty variables from about 20,000 participants. Lets use memory as an ...
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143 views

time series model selection in exploratory research

I work in the field of behavioural interventions and I use dynamic models to gain better insight into (explain) the process of behaviour change and to help inform future behavioural interventions (...
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876 views

Has the journal Science endorsed the Garden of Forking Pathes Analyses?

The idea of adaptive data analysis is that you alter your plan for analyzing the data as you learn more about it. In the case of exploratory data analysis (EDA), this is generally a good idea (you are ...
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251 views

Classification eda

I am constructing a 2-class classifier and using cross validation to tune certain parameters in my model. The predictor variables are both continuous and one is ordinal. Based on looking at the ...
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277 views

Is a higher correlation coefficient always “better” or “more appropriate”?

I have a question (reproduced below) from an exam. It seems to be presumed that the greater the (product moment) correlation coefficient, the "more appropriate" and the "better" the model. Is such a ...
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110 views

Statistical analysis for replication in very small experimental datasets

A colleague does replication on a quite coslty experiments. There are four different conditions, each one duplicated. The outcome with $4\times 2 = 8$ points is illustrated below: The analysis is ...
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74 views

The meaning of Classification Accuracy

I'm working on San Francisco Crime dataset, and only get about 20% classification accuracy. I used Random Forest Method. So how I can Interpret the result? I did EDA firstly, but how can I use EDA to ...
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22 views

Label reduction on dataset

This question related to this other one, for which I have devised a strategy and now want some feedback on it. My data consists of 434042 rows, each corresponding to an observation tagged with 1 of ...
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1answer
137 views

Relationships of missing values for exploratory analysis

I have a survey with 30 questions on a seven item likert scale Not all of the questions were answered. I can use a heat map to visualize the missing answers but what i would like to know is if there ...
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5k views

Any necessary EDA before logistic?

I wanted to know if we do EDA before logistic regression. Sure, I will look at the variables and their distributions, but is there anything specific to logistic?
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39 views

How to identify crucial features that lead to a strong sports performance

I have a dataset (500 samples) that contains information about sportsmen. It contains about 30 features that describe: age body composition like weight and size amount of daily training ...
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2answers
1k views

How to assess seasonality effect influence on time series

Suppose I collected a time-series data (e.g. drug prescription on every month for 12 years). I have no reason to believe that my data is influenced by a seasonal factor (e.g. drug consumption is not ...
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Is it better to do exploratory data analysis on the training dataset only?

I'm doing exploratory data analysis (EDA) on a dataset. Then I will select some features to predict a dependent variable. The question is: Should I do the EDA on my training dataset only? Or ...
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59 views

Which method can I use to pinpoint features that separates a sub-group from a group

Let's say I have a group (G) of 1000 individuals. I have complete knowledge of 200 demographic properties of each of them, from categorical (favorite drink) to numerical (age). Let's say I invite ...
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1k views

Choosing predictors in regression analysis and multicollinearity

I would like to run a linear regression analysis and I'm uncertain about including predictors. I have three predictor variables available. One is based on a lot of previous research. Therefore I am ...
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694 views

Texas sharpshooter fallacy in exploratory data analysis

I was reading this article in Nature in which some fallacies are explained in the context of data analysis. I noticed that the Texas sharpshooter fallacy was particularly difficult to avoid: A ...
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234 views

Suggestions for Exploratory Data Analysis for high-dimensional regression data?

I have a moderately high-dim dataset (around 20 predictors) that I plan to analyse using Bayesian variable selection techniques. This will be a logistic regression analysis since the output is a ...
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1answer
234 views

How to approach a regression problem? [closed]

I have to solve a regression problem involving 302 variables. How do we select appropriate models or ensemble of models to work well ? Does this decision of choosing models come from the ideas ...
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67 views

Rule of thumb for exploratory data

I frequently perform 2k factorial design of experiments and fit the data to a linear regression to control/optimize processes in a manufacturing environment. I have noticed recently that a large ...
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1k views

Python/R Exploratory Data Analysis for Classification [closed]

Are there preexisting functions in Python/R that create exploratory data analysis plots like the following:
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Conceptual question: how is a factor created in exploratory factor analysis?

As a conceptual question: in exploratory factor analysis, how is a factor created? I would like to know your simple answer to this simple question. Imagine, my academic field does not dependent on ...
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What is the “horseshoe effect” and/or the “arch effect” in PCA / correspondence analysis?

There are many techniques in ecological statistics for exploratory data analysis of multidimensional data. These are called 'ordination' techniques. Many are the same or closely related to common ...
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200 views

Introduction to Explorative Sequential Data Analysis

Short version I am looking for introductory material to explorative data analysis of complex sequential data like website activity, hospital visits etc. Long version Currently I am facing data ...
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1answer
391 views

Exploratory data analysis using box plots

How should you make a box plot when the data have an outlier? Must we use the data with the outlier, or use the data without the outlier? If we use the data without the outlier, we will change the ...
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10k views

How to interpret notched box plots

While doing some EDA I decided to use a box plot to illustrate the difference between two levels of a factor. The way ggplot rendered the box plot was satisfactory, but slightly simplistic (first ...
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3answers
2k views

Exploratory data analysis for a dataset with continuous and categorical variables

I have a data set which has DV and around 40 IVs. I want to select best variables out of the existing ones. I can use correlation, but it requires only numeric variables. I would like to see relation ...
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2k views

Is it appropriate to do an ANOVA on a feature selected via inspecting PCA results?

I've been given a dataset consisting of 8 dimensional feature vectors for 4 classes of objects. I was asked to find the features that best distinguish the classes, and write up a short report. My ...
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276 views

(LDA) Topic Modeling: eliminate Junktopics through normalization

Question: Is it reasonable to normalize topics to eliminate junk-topics and get a better distinction of document-relations? I used the MALLET-LDA Java-library to estimate a ParallelTopicModel with ...
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639 views

Statistical method to prove inverse relationship between class size and student achievement

A hypothesis states that there is an inverse relationship between class size and student achievement. With data records about class sizes and grades of its students at a certain school, we would like ...
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28 views

What is the discrete equivalent to the 4-plot?

Quoting NIST, when analyzing a continuous variable, one needs to validate four assumptions that typically underlie all measurement processes; namely, that the data at hand "behave like": random ...
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54 views

Reduction of species variables in vegetative analysis

Edited following helpful feedback. I have vegetation species data for a number of grassland habitat sites, and am preparing to begin Exploratory Data Analysis. Data was collected in 100 quadrats over ...
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212 views

What statistical technique could I use to see if gender effect exists in this scenario?

Suppose I give 6 short stories (of word length varying from 200 to 400),and ask N=100 students about which one (e.g., story #1, #2,..., #6) is their favorite story (see below table). Some data are ...
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18k views

If my histogram shows a bell-shaped curve, can I say my data is normally distributed?

I created a histogram for Respondent Age and managed to get a very nice bell-shaped curve, from which I concluded that the distribution is normal. Then I ran the normality test in SPSS, with n = 169. ...
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1answer
109 views

Quantitative Location Shifting Detection for Run-Sequence Plot

I am trying to complement a Run-Sequence Plot by some quantitative metric to validate that a dataset has a fixed location. Since the Run-Sequence Plot will be used in the early phases of Exploratory ...
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1answer
2k views

Minimum cumulative variance to extract in exploratory factor analysis to ensure a good fit

As a part of my exploratory factor analysis, I would like to report the cumulative variance % (eigenvalues). I wonder if there are guidelines on the minimum percentage in order to have a good model ...
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507 views

Is there any rule of thumb to delete a variable in a large data set?

I'm working with a large set as a project for the business analytic course with $10^5$ observations and 170+ variables, some of which come with a missing value proportion of larger than 20%, even more ...
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3k views

Quick Exploratory Analysis of Categorical Data [closed]

Does anyone know of a tool (preferably free) that does quick analysis of exploratory data mainly categorical with date. Using R and Python I can create time series and histograms, perform tests such ...
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Is there any good reason to use PCA instead of EFA? Also, can PCA be a substitute for factor analysis?

In some disciplines, PCA (principal component analysis) is systematically used without any justification, and PCA and EFA (exploratory factor analysis) are considered as synonyms. I therefore ...
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3answers
471 views

Which is correct way for regression line?

I have a set of data (some Frequencies per month, Var1 is the month): ...
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2answers
6k views

How to do exploratory data analysis to choose appropriate machine learning algorithm

We are studying machine learning via Machine Learning: A Probabilistic Perspective (Kevin Murphy). While the text explains the theoretical foundation of each algorithm, it rarely says in which case ...
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3answers
6k views

How to determine moving window size?

I am using moving window technique for data analysis... For example I compute the mean, the standard deviation and etc. for a given window. And I wonder if there's any good criterion to determine ...
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2answers
19k views

What are some good examples of exploratory data analysis today?

Are there some papers published which illustrate EDA used to tackle substantial data problems? I am particularly looking for actual (current) data examples, where plots have been made and statistics ...
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410 views

Can factor analysis improve the fit of a predictive regression model?

My company is working with a client who have built a logistic regression model to predict whether kids with psychiatric disorders will successfully complete a State intervention program (Yes or No). ...
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1answer
262 views

Is there a way to explain and generalise the decision made by random forest?

I saw a similar question was asked a few years ago, maybe there are updates on that. I would like to have a way to explain the decisions generated by random forest, possibly in a single tree. I ...
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3answers
120 views

I do not have hypotheses for my research and I have got only categorical data. what kind of data analysis can i conduct? also

I do not have hypotheses for my research and I have got only categorical data. what kind of data analysis can i conduct for correlation between variables? also is chi-square used only for hypotheses ...
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42 views

Choosing a test based on by data and how to test when I have several groups?

I'm trying to analyze the effect of the laying order on a certain concentration of immune factor. I have a large set of data (1000+ eggs). I want to know if egg 1 (first-laid egg) will have higher ...
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1answer
2k views

Determining probability distribution for datasets with missing values

As a part of my exploratory data analysis (EDA) prior to further analysis, I'm trying to determine a probability distribution of my pilot dataset's variables. A particular feature of this dataset is a ...
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2answers
85 views

Cross Vaidation in Factor Analysis

I am trying to conduct an EFA with a sample size of 150 respondents. I would also like to use cross-validation but my professor says that the sample is not big enough for that. Is that true?
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2answers
749 views

Is PCA appropriate for comparing subsets of panel data?

I have a large panel (5000+ subjects, 4 variables over 182 periods), and I've identified particular Granger-causal relationship in a large subset of those subjects (30% or so). I would like to somehow ...
3
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1answer
3k views

R scatterplot matrix with nonparametric density

I normally use MATLAB, or JMP but right now am working with R. I have ~150 dimensional data with a few hundred thousand rows. Some of the columns are non-informative, they only have one value. This ...