Calculate percentile of a raw score from normative data of a psychological test 2 Proper names for data - quantile and rank 0 How to compare equality of the distribution at different quantiles 5 Calculate mu and sigma of a log normal distribution from p50 and p99 in...
but I want the distribution with the box plot and data points graphed above it, with the additional information in the box plot, like the mean, median, and maximum 50% of the data -- you can't add these easily in graph builder, for example. ...
16S rRNA-gene sequencing is a valuable approach to characterize the taxonomic content of the whole bacterial population inhabiting a metabolic and spatial niche, providing an important opportunity to study bacteria and their role in many health and envir
# how to find outliers in r - calculate Interquartile Range iqr <- IQR(warpbreaks$breaks) Now that you know the IQR and the quantiles, you can find the cut-off ranges beyond which all data points are outliers. # how to find outliers in r - upper and lower range up <- Q[2]+1.5...
The IQR function also requires numerical vectors and therefore arguments are passed in the same way. # how to find outliers in r - calculate Interquartile Range iqr <- IQR(warpbreaks$breaks) Now that you know the IQR and the quantiles, you can find the cut-off ranges beyond which all da...
To calculate the mean and std deviation just take the mean and standard deviation of the columns. To plot histograms, calculate the difference between the ithith and the (i−1)th(i−1)th value. You can now just take histograms of these numbers to get what you want....
McCrory, cited in Jantsch (1967), assumes a Gaussian distribution and uses this to calculate the probability that a targeted level of progress be met at a given horizon. Here we assume and test a Gaussian distribution for the natural log. 2 To drive home the point that fossil fuels show...
The IQR function also requires numerical vectors and therefore arguments are passed in the same way. iqr <- IQR(warpbreaks$breaks) Now that you know the IQR and the quantiles, you can find the cut-off ranges beyond which all data points are outliers. up <- Q[2]+1.5*iqr # Upper ...
Here is how to reproduce the vegan procrustes analysis in Python using only SciPy and NumPy. Please refer to @Kat answers above for context on how to plot: # Get X and Y which are the first 2 embeddings # --- # X <- scores(X, display = scores, ...) mds_null = pd.read_csv...
Rank biserial correlation (Ord vs Bin) and its extension (Ord vs Cat): The rank biserial correlation replaces the continuous variable X in point biserial correlation with ranks. To calculate the correlation between an ordinal and a nominal variable (binary or multi-class), we transform the ordi...