Skip to main content

Questions tagged [qq-plot]

A Q–Q plot (or quantile quantile plot) is a scatterplot of the quantiles of two distributions. Q–Q plots are useful for comparing distributions.

Filter by
Sorted by
Tagged with
0 votes
0 answers
28 views

Assessing whether a dataset follows a distribution using Q-Q Plot

I recently found myself answering a question on Stack Overflow about adjusting a dataset to a unknown distribution. Adding my two cents to the community, I have provided a script to draw a Q-Q Plot in ...
jlandercy's user avatar
  • 131
1 vote
0 answers
28 views

Distribution of the model vs. Distribution of the Residuals

Let's say I'm going to do an analysis where my response variable has a gamma distribution. I perform the analysis pointing to the distribution in my model (eg. using the lme4 package, m1<-glmer(Y~...
Graciliano Santos's user avatar
1 vote
1 answer
87 views

Ambiguity between Statistic Normality Test vs Visual Normality Check

I'm learning some basic EDA using the Boston housing price dataset and I want to filter out outliers in the feature columns. To do that I first wanted to understand what distribution each of my ...
joesan's user avatar
  • 163
0 votes
0 answers
18 views

3 way interaction, residual plot showing clustering across fitted values, do I need to account for grouping in a different way?

I have created a model with a three way interaction, analyzing how taste of bread (fr2) decreases over time (time2), and how skill of the baker (skill2) impacts longevity of taste, across different ...
Jackson's user avatar
  • 11
0 votes
0 answers
45 views

Are GLM response residuals supposed to be centered on 0?

I'm struggling with the idea of residuals and error terms in GLMs. I've gathered that there are no explicit error terms in GLMs because the distributions modelled don't allow the decomposition between ...
Boussens-Dumon Grégoire's user avatar
10 votes
5 answers
1k views

Why GLM don't have an error term and why shouldn't residuals be i.i.d?

I've read dozens on post on the subject but I cannot figure this out. From what I've gathered, GLMS don't include an error term in their formulation unlike linear models (LM). I was wondering why (or ...
Boussens-Dumon Grégoire's user avatar
0 votes
0 answers
12 views

Negative values Box-Cox [duplicate]

I have a dataset and have developed a regression model. The linear assumption is not fulfilled and I have therefore made a BoxCox transformation. Some of the dependent variables were negative and in ...
user412104's user avatar
0 votes
0 answers
19 views

Is this normal QQ plot light or heavy tailed? First QQ plot I'm trying to analyse on my own

I think if it wasn't for the outliers on the tails, I'd be sure this normal QQ plot is light tailed but I'm not sure. I'm aware I can use formal tests to find out, but I was told statisticians like to ...
user409634's user avatar
1 vote
1 answer
50 views

How do I interpret this QQ plot and residual vs fitted plot?

I have a model in R looking at infectious disease spread on social networks, and I am running into a problem where my data are clearly not normally-distributed when I try to run a linear regression ...
mxseabat's user avatar
1 vote
0 answers
71 views

How does plotting QQ plot on ggplot work?

I am new to r programming and have ran into an odd situation while plotting a QQ plot for studentised residuals with ggplot2. See code and plot below: ...
Yat-Hon's user avatar
  • 13
1 vote
1 answer
39 views

Are there any heavy tailed distributions available for GAMM?

I have a gamm that looks to be heavy tailed according to the qqplot so I'd like to account for this. According to this page things like scaled t distributions for heavy tailed data are only available ...
adkane's user avatar
  • 1,021
10 votes
3 answers
1k views

Why does creation of a Q–Q plot in Excel need an adjustment by 0.5?

I am aware that different statistical packages provide Q–Q plots using code or via a black box. For example, minitab with R integration for Q–Q plot from here. I am trying to do this manually via ...
Tryer's user avatar
  • 275
3 votes
2 answers
353 views

Normality test using normal Q-Q plot and histogram

I have plotted a normal Q-Q Plot and a histogram to check the normality of this set of discrete data. My interpretation is the data are not normally distributed since they do not fall on the linear ...
user281667's user avatar
9 votes
4 answers
912 views

An interesting observation regarding the log transformation of data

I stumbled upon something interesting while attempting to do a log transformation for some data (with zeros) today. It seems that there must be a good reason for this that I'm just not seeing. I'm ...
knrumsey's user avatar
  • 8,382
0 votes
1 answer
158 views

Impact of outliers to QQ plot

I'm trying to build an GLM regression (10k samples and 50 dimensions). I ran an analysis of the dependent variable since the regression has a normality assumption for the dependent variable. The QQ ...
cat's user avatar
  • 53
1 vote
0 answers
39 views

Why my GWAS p-value QQ-plot falls far above diagonal? [duplicate]

I'm trying to run GWAS pipeline using plink, but the results I got look really off. The QQ-plot of the p-values is far above the diagonal. I'm pretty sure I followed the correct QC process, and the ...
Celia L.'s user avatar
3 votes
1 answer
694 views

I have applied many statistical tests to my data, but still cannot determine normality

I have run multiple tests to determine normality on my dataset, but I am unsure which one to adhere to, especially since my histograms, density plots, and QQ plots leave much to be desired in terms of ...
Kimber's user avatar
  • 53
0 votes
0 answers
85 views

How to interpret a qq plot of uniform distribution whose slope is greater than 1

I am trying to interpret a qq plot of a uniform distribution in R where the plot is as shown in the image. The qq lines are a kind of straight but the slope of these lines way greater than the 45 ...
user395733's user avatar
0 votes
0 answers
28 views

Distribution looks roughly normal on a q-q plot, but has a p-value of 0.0 for the Shapiro-Wilk normality test. How to interpret? [duplicate]

The distribution is as follows: However the Shapiro-Wilk test yields a p-value of 0.0 and a W statistic of 0.9. There are over 7,000 values in the sample. Note, the quantile values have been ...
NominalSystems's user avatar
2 votes
1 answer
245 views

Trouble selecting q-q plot settings with statsmodels. Do any of these plots properly compare the sample quantiles to theoretical normal quantiles?

I have an array of over 6,000 data points and am trying to show whether they follow a normal distribution. Statsmodels (the library I'm using to generate plots) gives the option of using a 45-degree ...
user395052's user avatar
0 votes
0 answers
20 views

Does the maximum likelihood estimate give the optimal line of fit in a QQ plot?

Many analysts attempt to fit a distribution for a random variable by a. estimating the parameters with maximum likelihood then b. assessing the quality of the fit to the distribution by inspecting a ...
AdamO's user avatar
  • 63.7k
2 votes
2 answers
115 views

Distribution and variable analysis

I am doing a statistical test (program used is SPSS). On the basis of distribution and sample size, I have to chose the correct variable analysis. I also have to justify every decision. I have two ...
Chester's user avatar
  • 21
0 votes
0 answers
54 views

Does this need to be transformed? If, yes, how?

My data is collecting deposition of particles from the atmosphere once a month for 11 months at two sites. I am testing to see if my two sites' data are normally distributed so I can determine what T-...
NickW's user avatar
  • 1
3 votes
1 answer
292 views

Help me understand this qqplot

I have plotted the qqplot of the residuals that my model generates with the python module statsmodel sm.qqplot(data, line ='r') and it looks like this The points are placed on a straight line but ...
Alucard's user avatar
  • 325
0 votes
0 answers
48 views

How do I interpret this QQ plot?

I am calculating a multiple regression with a sample of 128 and I was wondering, what distribution would best describe this residuals qq plot? It seems like a a Poisson-distribution to me, is it ...
Migle's user avatar
  • 1
2 votes
1 answer
116 views

Q-Q plots and normality: Can I use ANOVA?

I want to use an ANOVA for my analysis (2x3 design). I can decide if I can safely use parametric tests. The two samples results: Shapiro-Wilk p<.001) and Q-Q plots don't seem to be normally ...
Audere Semper's user avatar
3 votes
1 answer
326 views

Evaluating goodness-of-fit for GARCH models in R with QQ-plots (rugarch package)

I'm currently working with multivariate GARCH representations of time-series for financial data using the rmgarch R package. This package in turn uses the well-...
OJK's user avatar
  • 31
5 votes
1 answer
3k views

How to define the line to fit in Q-Q plot?

I'm trying to figure out if my data follows a normal distribution and if it contains outliers. I have plotted the histogram and now I would like to plot the quantile-quantile (Q-Q) plot. My point is, ...
JCV's user avatar
  • 153
0 votes
1 answer
71 views

Goodness-of-fit Tests

Continuing from my previous question here. Furthermore, I intend to perform the chi-squared test and plot QQ-plots to test the hypothesis $H_0:\lambda=1$. I do not get to see the actual data though; I ...
pecer10012's user avatar
4 votes
1 answer
213 views

Goodness-of-fit Tests

I wish to test whether a large number of observations $X_i$ follows an exponential distribution with parameter $\lambda=1$. I also wish to test this hypothesis exactly, and intend that if the ...
pecer10012's user avatar
0 votes
0 answers
1k views

Different Calculation Methods for Theoretical Quantiles of Q-Q Plot

There seem to be at least two different methods to calculate the theoretical quantiles in a Q-Q plot. In the following, the normal distribution is assumed to be the theoretical distribution. Split ...
keezar's user avatar
  • 35
0 votes
1 answer
63 views

How can the author get the following conclusion from the QQ plot?

In this paper: https://www.tandfonline.com/doi/pdf/10.1080/02664763.2021.1940109, the authors have two actual datasets (e.g., 59 observations showing continuous annual flood data) and the authors want ...
Hermi's user avatar
  • 747
0 votes
0 answers
73 views

Frequentists tests to check for normality

Let $X_1,...,X_n\sim X$ be $n$ i.i.d. random variables. I want to to test if they follow a normal distribution, in other words, check if their distribution belongs to the Gaussian family. These are ...
pecer10012's user avatar
1 vote
1 answer
636 views

Interpreting QQ plot

Can we say that the assumption for linearity is met? I'm confused because the tails are heavy, and deviations have a bow-shaped pattern. Still, I think that the linearity has met because the majority ...
Dan's user avatar
  • 11
1 vote
1 answer
498 views

Interpreting 2 residuals plots [closed]

Hello. Can anyone help me with interpreting these plots? I would like to know what assumptions of the linear model are not being met and what method should be used to fix the problems. I think there ...
Mdddl's user avatar
  • 11
1 vote
0 answers
2k views

How to choose between ordered logit and ordered probit regression?

If the dependent variable is discrete ordinal, like 0-10 then an ordered logit or ordered probit is appropriate to use. They are both similar but their interpretation are different and their error is ...
rr19's user avatar
  • 65
0 votes
1 answer
72 views

Can we compare a standardized version of a variable with a standard normal distribution to check a variable's normality?

I am currently exploring ways to check the normality of a given variable in the dataset. Since most algorithms assume a variable's gaussian distribution, it is important to check it. A Q-Q Plot Came ...
badc0ffee's user avatar
  • 134
2 votes
1 answer
89 views

Is there normality in my data? Which statistical test should I use?

I runned two GLMs using the same dependent and independent variables, but modelling each analysis according a different type of distribution. Then, I compared its AIC values to find what distribution ...
user avatar
0 votes
1 answer
110 views

Does this plot indicate the data is normal distributed?

I use qqnorm to plot my data as the photo attached. Does this plot indicate the data is normal distributed?
lily zhu's user avatar
0 votes
1 answer
26 views

Checking interaction between one dependent continuous variable and two independent continuous variable

I am trying to figure out if there is a way that we can perform some statistical test to check the interaction between two independent continuous variables and a dependent variable in R. I have three ...
Ranji Raj Nair's user avatar
0 votes
0 answers
52 views

How do I interpret this plot?

I'm finding it hard to interpret this plot. Is it skewed, bimodal, or what is it? What do the points lying in the same line and rising suddenly mean? Is it exponential?
Amreesh Karthikeyan's user avatar
0 votes
0 answers
81 views

Theoretical q-q plot: What does the f-value mean in this example?

I am looking at this article on theoretical q-q plots and am trying to understand it in its entirety. The part where I get lost is when the author writes: We first find the f-values for alto What do ...
willpkay's user avatar
0 votes
1 answer
3k views

What are the main difference between a QQ plot and a probability plot for measuring nomality? [duplicate]

I am trying to evaluate the normality of the distribution of my model's residuals. I have been using statsmodels.api.qqplot and ...
Archie's user avatar
  • 205
2 votes
1 answer
457 views

Is my data normally distributed? (QQ plot and histogram analysis) [duplicate]

I am trying to create a regression model for prediction. I need to generate prediction/confidence intervals for my model. I am trying to decide whether to use a quantile regression or linear ...
Archie's user avatar
  • 205
4 votes
1 answer
552 views

Calculation of quantiles with fitted parameters in Python

I am trying to make two-sample Q-Q plots in Python. A Python function that is used for calculating quantiles has the option of fitting parameters for the calculation of quantiles. These parameters are ...
weakboneman's user avatar
4 votes
1 answer
290 views

Is it possible to make a confidence envelope for a two sample Q-Q plot in R (or Python)? If so, what is the simplest method?

I want to show the confidence envelope for a two sample Q-Q plot in R (or Python). The aim is to use the Q-Q plot to give an indication of whether my two samples are drawn from the same population The ...
weakboneman's user avatar
1 vote
2 answers
1k views

Quantile-Quantile Plot for Negative Binomial Distribution

I am performing regression analysis in R on count data which are negative binomial distributed. I would like to use a quantile-quantile plot as a tool to diagnose the fit of my models, but I am ...
jmf's user avatar
  • 11
5 votes
2 answers
332 views

GAM: Find a good distribution for the monthly data sums?

I am new in the GAM modelling. I would like to find a family, that will fit my response variables. I am using the sums of monthly counts of beetles, collected from the beetle traps in ~ two weeks ...
maycca's user avatar
  • 325
0 votes
1 answer
366 views

Which statistical test do I use with 2 independent groups and 1 dependent variable

I want to test if there is a difference in the mean distance travelled (Afstand) by sex (Geslacht) and age class (...
Pepijn95's user avatar
  • 103
0 votes
1 answer
97 views

QQ Plot interpretation

I wanted to investigate if my data is normally distributed with a QQ Plot. I'm not quite sure if the deviations from the theoretical plot are too big to crate a bland-altman plot?
C K's user avatar
  • 51

1
2 3 4 5
7