Refers to the normal distribution, the Gaussian continuous probability distribution.

learn more… | top users | synonyms

1
vote
0answers
57 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 ...
0
votes
0answers
33 views

Normality test with p-value equal to zero [duplicate]

I have an array dataset of about 650.000 points. I want to test if the dataset follow a normal distribution or any other distribution. The first thing I did was to split the data in groups, find the ...
23
votes
3answers
632 views

Interpreting QQplot - Is there any rule of thumb to decide for non-normality?

I have read enough threads on QQplots here to understand that a QQplot can be more informative than other normality tests. However, I am inexperienced with interpreting QQplots. I googled a lot; I ...
1
vote
1answer
34 views

How to test differences of means of 3 independent groups

I'm new to statistics and the only software i know how to use is SPSS. I need help.... I have 3 independent groups with sizes: 24, 27, 37. I wanted to test the difference between the means of their ...
0
votes
0answers
12 views

What are the benefits of normality assumption for AR(I)MA models?

I know normality assumption is not necessary for all of the ARIMA models. My question is that if we have a non-normal time series, is it better to transform it to normal state by transformations like ...
2
votes
1answer
35 views

Non normal residuals in multiple regression

I used height, weight, gender and age to regress on BMR (basal metabolic rate) and obtained the following qq plot of residuals I then regressed the above variables with log BMR and obtained the ...
0
votes
0answers
14 views

One sample Hoteling's T2

I used one sample Hotelling's T2 statistic to check if the nutrient intake of 75 men meet the recommended daily nutrient intake value. I got an F value close to 58000. Is such a large value ...
1
vote
1answer
11 views

Chi-square plot to check for multivariate normality: Should I use the sample covariance or “normal” covariance?

I'd like to check if my observations are normally distributed by using a chi-square plot. To calculate the generalized squared distances (squared Mahalanobis distances) I need the covariance matrix of ...
1
vote
1answer
15 views

Whether to transform non-normal pre-test when running linear regression on transformed post-test?

I'm running linear regression model on a post-intervention test score controlling for pre-intervention test score. I used Box-Cox transformation on the post-intervention test score to normalize it. ...
1
vote
1answer
33 views

Compare the “normality” of two scales

I have two scales measuring the same construct, and I would like to know which scale is distributed more closely to a normal distribution. There are various possibilities for comparing a distribution ...
0
votes
0answers
26 views

Usefulness of Z-normalization in Machine Learning

Z-normalization means rescaling the feature $X$ by subtracting the average $\mu$ and dividing by its standard deviation $\sigma$, i.e., $(X-\mu)/\sigma$. What is the usefulness of normalizing data ...
5
votes
2answers
225 views

Why is a Pearson correlation of ranks valid despite normality assumption?

I am currently reading up on assumptions for Pearson correlations. An important assumption for the ensuing t-test seems to be that both variables come from normal distributions; if they don't, then ...
4
votes
1answer
64 views

2x2 ANOVA - assess violations of homoscedasticity & normality

I have a 2x2 factorial unbalanced between-subject design, n = 355. My DV is a subjective probability estimate (i.e., a number between 0 and 100). My ANOVA model: ...
0
votes
1answer
42 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
49 views

Do you need justification to transform non-normal data

First, a bit of background: I'm currently working on a project at work that produces variable width data. During a operation qualification I collected a bunch of data at low, nominal, and high ...
1
vote
0answers
12 views

Normality Testing of Productivity Data

I have a series of measurements from a construction production study I've been carrying out. I essentially measured the output rate of workers in terms of output/hr. The measurements varied each day ...
0
votes
0answers
10 views

Can non-normal data be used for factor analysis? [duplicate]

I would like to do factor analysis to derive a nutrient intake pattern. Many of these variables are not normally distributed. Is it gonna be a problem? And there are just 7 variables available. Can ...
0
votes
1answer
37 views

When reporting a CFA, is it desirable to assess univariate normality in addition to multivariate normality?

I am using SPSS AMOS to do a factor analysis and it produces statistics related to both univariate and multivariate normality. p35 of the AMOS Users Guide states that "[T]he observed variables must ...
4
votes
3answers
276 views

Assumptions of linear models and what to do if the residuals are not normally distributed

I am a little bit confused on what the assumptions of linear regression are. So far I checked whether: all of the explanatory variables correlated linearly with the response variable. (This was the ...
4
votes
1answer
100 views

Why not always use bootstrap CIs?

I was wondering how bootstrap CIs (and BCa in barticular) perform on normally-distributed data. There seems to be lots of work examining their performance on various types of distributions, but could ...
3
votes
2answers
87 views

Regression, Independence & Normality of x and y variables (not residuals)

I am trying to predict productivity of inbound process of a warehouse using y-value = productivity in terms of pcs/hr x-value = # pcs and ratio pcs/SKU. (where SKU = stock keeping unit) Basic ...
1
vote
2answers
142 views

Normality tests for histograms

I understand that one quick way to test for normality is to create a histogram from my data and see if it "looks bell-curved". Alternatively, I can use some normality test like Pearson's chi-squared. ...
1
vote
0answers
89 views

Appropriate test for detecting a signal in normally distributed noise

I am doing some signal processing and I have a histogram which has a bell shape when there is only noise in the signal. (I have been advised that this is to be expected due to the central limit ...
0
votes
1answer
59 views

Transformation for negative skewness data

My analysis involved some behavioral data on swine. One measure we had was standing time (min) for pigs using accelerometers. Using SAS, I checked for normality, and results showed data to be ...
1
vote
0answers
49 views

Variable transformation in a ANOVA and multivariate analyses

I want to run an ANOVA, and the multiple correlation and regression analyses. Some of my variables to be included in these analyses are normally distributed and some are not. I log transformed the not ...
5
votes
3answers
537 views

Regression - How do I know if my residuals are normally distributed?

Performing a regression and need to find out if my residuals are normally distributed.
-2
votes
1answer
94 views

how to interpret KS test or Shapiro wilk test for ordinal criterion variable?

Here Rank is my dependent variable from level (Strongly disagree to strongly agree) and Pre_Sales_support is one of the independent variable. Due to smaller sample size of 15, I am taking ...
1
vote
1answer
36 views

how to transform data of two experimental groups? one is positively skewed and one is negatively..

I have two experimental groups. Then I test their normality respectively. Result shows that one is positively skewed and the other is negatively skewed. In this case, how should I do the data ...
10
votes
1answer
122 views

Why does non-normally distributed errors compromise the validity of our significance statements?

There is a normality assumption when it comes to consider OLS models and that is that the errors be normally distributed. I have been browsing through Cross Validated and it sounds like Y and X don't ...
3
votes
1answer
189 views

Meaning of Qqnorm plot in R

I am testing the normality of a sample with R using qqnorm. I obtain this: I understand that the meaning of this plot is that the sample has fat tails. But what is the meaning of the values on the ...
0
votes
1answer
57 views

Kalman filter and Box-Cox

I'm interested in wind forecasting, which I have analyzed over some time by means of ARMA methods. Now I've being reading about Kalman filtering. Kalman filter is optimal when Gaussian assumption can ...
0
votes
1answer
30 views

Finding the probability of normality via Anderson-Darling, Shapiro-Wilk , and Kolomogrov-Smirov

I have quite a few distributions that were generated by some system, and I am trying to find the probability of accordance to normality for these distributions. So, the probability of accordance to ...
1
vote
1answer
56 views

how do normality check in ks test assess for equivalence or difference in data sets?

I have a series of data of photon counts versus time. These data are periodic, then I can fold them and obtain an average profile of the data. Nonetheless, some variations appear sometime in the ...
0
votes
0answers
30 views

SEM for Non-Normal Ordinal Data

In short, I conducted a satisfaction survey in which surveyees are required to answer on a satisfaction scale from 1 to 7: 285 observations, 37 satisfaction variables. Here is an example of what the ...
1
vote
1answer
28 views

Similarity Coefficient and Geochemical Correlation

I have a set of around 160 samples from different sediment bodies, or stratigraphic units, which I am attempting to correlate using geochemical analysis of 25 elements for each sample, and a ...
4
votes
1answer
301 views

Testing large dataset for normality - how and is it reliable?

I'm examining a part of my dataset containing 46840 double values ranging from 1 to 1690 grouped in two groups. In order to analyze the differences between these groups I started by examining the ...
4
votes
1answer
205 views

Using Univariate ANOVA with non-normally distributed data

If my data are non-normally distributed and I'm conducting a 2x2 ANOVA, what can I do to correct for this problem so I can report the main effect and interaction output appropriately? Only one ...
1
vote
1answer
38 views

Use pc scores to check mulitvariate normality

How can you check multivariate normality, using the scores from the PCA? Or what can we expect about the scores if the data is multivariate normal distributed?
3
votes
2answers
73 views

How much is moderate violation to normality for one sample t-test?

I want to test if my data have a mean equal to zero (Ho: mu=0). The sample size in not large (n=21). My variable is numerical with average -0.10 and sample_sd 0.05. I don't know the population ...
1
vote
1answer
100 views

Why is Shapiro–Wilk test considered to be the best normality test?

I have read somewhere in the literature that the Shapiro–Wilk test is considered to be the best normality test because for a given significance level, $\alpha$, the probability of rejecting the null ...
0
votes
1answer
32 views

ANOVA normality assumption for which variables?

When I want to conduct a repeated measures ANOVA pre and post test scores, which variables need to be tested for normality? Each the pre and post scores or the difference between them? I suppose ...
0
votes
0answers
91 views

Can I normalize a data proportion?

Is there any way to normalize this variable (attached)? In fact, this is a proportional data (a percentage). But I need transform it in order to do some contrasts. I try with arcsine transformation: 2 ...
2
votes
2answers
141 views

Standard error of regression coefficients without an assumption of homoscedastic normal noise

I have a time series that is affected by two (or more) kinds of events. When event $A$ happens, some signal is linearly added to the time series (the signal lasts, for example, for 100 time points). ...
0
votes
0answers
38 views

Determining the number of levels in a Repeated Measures ANOVA for multivariate or univariate within subjects effects

Maxwell and Delaney (1990) wrote that the multivariate approach should not be used for a repeated measures ANOVA for within subjects effects if n is less than "a + 10" (a is the number of levels for ...
1
vote
1answer
59 views

Total scores are normally distributed, but subtest scores are not; what to do?

I have two sets of data for males and females: $n=33$. I'd like to compare test results for both groups. I want to do a $t$ test, and I know my data should be normally distributed if I want to use a ...
2
votes
1answer
135 views

transformation to normality of the dependent variable in multiple regression

Is it really important to normalize dependent variables in multiple regression or are there any exceptions? My model is providing better results with more significant hypothesis when the DVs are not ...
0
votes
0answers
44 views

How to interpret probability plot?

I was reading about how to find the distribution of data from this question I generated the following probability plot from the scipy package.scipy prob plot Can someone please help me figure out ...
0
votes
0answers
21 views

Regarding transformation of a variable to follow normality [duplicate]

When I plotted histogram of a variable to see whether it follows normality, I got a highly positive skewed graph, more like that of a Poisson/exponential distribution. Now, what kind of ...
1
vote
1answer
99 views

Do all these estimates of kurtosis and skewness have the same (asymptotic) distribution under normal sample distribution?

I have seen five types of estimates of kurtosis and skewness: three from http://stats.stackexchange.com/a/84057/1005 one from page 9 of Analysis of Financial Time Series by Ruey S. Tsay one from ...
4
votes
1answer
83 views

Non-normal residuals - P-values higher or lower?

Background: I have estimated a model using panel data with the Arellano Bond estimator (see e.g., http://www.fordham.edu/economics/mcleod/Elitz-usingArellano%E2%80%93BondGMMEstimators.pdf) and n=300. ...