EDA stands for "Exploratory data analysis". Developed by Tukey to contrast w/ *confirmatory* DA (the formal testing of hypotheses), EDA is typically concerned w/ describing data numerically & graphically to make the data easier to understand & to yield new insights.

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64 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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7 views

Finding feature values most specific for a subset

I have a set of items with lots of categorical features. I also have a small subset of this set. I want to find out what's different about this subset compared to general population (i.e. what feature ...
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2answers
81 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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1answer
45 views

Is it better to do exploratory data analysis on the train 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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1answer
22 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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2answers
81 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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0answers
9 views

Setting a Target or Benchmark based on Historic Process data

We have 15 Work processes for a departments. There is the historic data for the dept with all the information. Data defines the which process is done by whom, minutes of work, start date and finish ...
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1answer
19 views

Exploratory Data Analysis for financial data and validating the IID assumption

I am trying to model financial data and I need a little help. As I understand it, EDA is the first step, basically looking at the data. What tools (plots or tests) can be of help to me? Second, the ...
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0answers
15 views

Determining “n” in moving averages

I'm monitoring seven variables (flow into tank, flow out of tank, volume in tank, concentration of the flow in, concentration of the flow out, concentration in tank and weight inside tank). The weight ...
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5answers
210 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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23 views

Analysis of charts

Let $X$ a variable that represents the performance of a student in high school and a variable $Y$ representing the performance of this same student at the university. Consider the regression ...
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0answers
16 views

Best Method for Finding Cause of Change Between two Datasets

There are two data sets with exactly the same fields, taken from two different years. Two of the fields are numerical, thought of as numerator and denominator. All the remaining fields are ...
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52 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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16 views

Can factor analysis identify factor structure if only 5-15% of my sample give positive responses?

Looking to do EFA and CFA with different versions of the same data; 3 to 4 thousand participants, 50 symptoms with a 4-point Likert scale. I would expect most of the participants to endorse 5-10 out ...
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1answer
59 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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0answers
39 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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1answer
134 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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47 views

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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1answer
729 views

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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1answer
50 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
73 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 ...
3
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1answer
781 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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0answers
24 views

How can we observe interaction?

Are there graphical methods to determine whether there are some sort of interaction between two variables towards the response variable? Thanks!
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3answers
403 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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2answers
230 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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53 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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23 views

Topic Model inference for subselection

Question: Does the inference of a trained topic model (LDA) used on a subselection of a text corpus result in more accurate document-document-relations? I used the MALLET-LDA Java-library to estimate ...
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0answers
9 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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0answers
36 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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76 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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2answers
2k 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
61 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 ...
2
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1answer
255 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 ...
3
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1answer
57 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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1answer
347 views

Quick Exploratory Analysis of Categorical Data

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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6answers
5k views

Is there any good reason to use PCA instead of EFA?

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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2answers
159 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
948 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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1answer
106 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
2k 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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0answers
112 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
92 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
107 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 ...
4
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1answer
523 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
42 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?
2
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2answers
212 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 ...
2
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1answer
1k 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 ...
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61 views

Exploring properties of groups in R

I have a data frame with the following structure: ...
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1answer
56 views

factor analysis: can irrelevant factors be identified by tweaking FA options?

So I ran a factor analysis (principal components method) on a dataset, first using the correlation matrix and then using the covariance matrix, both with varimax rotations. The results of both factor ...
2
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0answers
53 views

What to do when exploratory factor analysis results are different for complete-cases and imputed data?

I have a hundred items that I'm performing EFA on, with around 370 complete cases. Using parallel analysis to determine the number of factors to extract, EFA gave 9 factors, all of which make ...