PDF Statistics Quick Review: Concepts and Terminologies (Quick Review Notes)

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Our Over and Under Sampling can combat that. In both the left and right side of the image above, our blue class has far more samples than the orange class. In this case, we have 2 pre-processing options which can help in the training of our Machine Learning models. Undersampling means we will select only some of the data from the majority class, only using as many examples as the minority class has.

This selection should be done to maintain the probability distribution of the class. That was easy!

Introduction

We just evened out our dataset by just taking less samples! Oversampling means that we will create copies of our minority class in order to have the same number of examples as the majority class has. The copies will be made such that the distribution of the minority class is maintained. We just evened out our dataset without getting any more data! Fully understanding why we use Bayesian Statistics requires us to first understand where Frequency Statistics fails. It involves applying math to analyze the probability of some event occurring, where specifically the only data we compute on is prior data.

Suppose I gave you a die and asked you what were the chances of you rolling a 6. Indeed if we were to do a frequency analysis we would look at some data where someone rolled a die 10, times and compute the frequency of each number rolled; it would roughly come out to 1 in 6! But what if someone were to tell you that the specific die that was given to you was loaded to always land on 6? Since frequency analysis only takes into account prior data , that evidence that was given to you about the die being loaded is not being taken into account.

Bayesian Statistics does take into account this evidence.

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The probability P H in our equation is basically our frequency analysis; given our prior data what is the probability of our event occurring. The P E H in our equation is called the likelihood and is essentially the probability that our evidence is correct, given the information from our frequency analysis. The P E is the probability that the actual evidence is true. As you can see from the layout of the equation Bayesian statistics takes everything into account.

Use it whenever you feel that your prior data will not be a good representation of your future data and results. Connect with me on LinkedIn too! Want to learn more about Data Science?


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And just a heads up, I support this blog with Amazon affiliate links to great books, because sharing great books helps everyone! As an Amazon Associate I earn from qualifying purchases. Sign in. Get started. George Seif Follow. Chemical structures should be produced using ChemDraw or a similar program. All chemical compounds must be assigned a bold, Arabic numeral in the order in which the compounds are presented in the manuscript text.

Structures should then be exported into a dpi RGB tiff file before being submitted. Stereo diagrams should be presented for divergent 'wall-eyed' viewing, with the two panels separated by 5. In the final accepted version of the manuscript, the stereo images should be submitted at their final page size. It should be clear what statistical test was used to generate every P value.

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Use of the word "significant" should always be accompanied by a P value; otherwise, use "substantial," "considerable," etc. Data sets should be summarized with descriptive statistics, which should include the n value for each data set, a clearly labelled measure of centre such as the mean or the median , and a clearly labelled measure of variability such as standard deviation or range. Ranges are more appropriate than standard deviations or standard errors for small data sets. Graphs should include clearly labelled error bars.

Authors must justify the use of a particular test and explain whether their data conform to the assumptions of the tests. Three errors are particularly common:. Molecular structures are identified by bold, Arabic numerals assigned in order of presentation in the text. Once identified in the main text or a figure, compounds may be referred to by their name, by a defined abbreviation, or by the bold Arabic numeral as long as the compound is referred to consistently as one of these three.

When possible, authors should refer to chemical compounds and biomolecules using systematic nomenclature, preferably using IUPAC. Standard chemical and biological abbreviations should be used. Unconventional or specialist abbreviations should be defined at their first occurrence in the text. Authors should use approved nomenclature for gene symbols, and use symbols rather than italicized full names for example Ttn, not titin.

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Please consult the appropriate nomenclature databases for correct gene names and symbols. A useful resource is LocusLink. Approved mouse symbols are provided by The Jackson Laboratory, e-mail: nomen informatics.


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For proposed gene names that are not already approved, please submit the gene symbols to the appropriate nomenclature committees as soon as possible, as these must be deposited and approved before publication of an article. Use one name throughout and include the other at first mention: 'Oct4 also known as Pou5f1 '.

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Authors should provide a statement confirming the source, identity and purity of known compounds that are central to the scientific study, even if they are purchased or resynthesized using published methods.

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Chemical identity for organic and organometallic compounds should be established through spectroscopic analysis. For new materials, authors should also provide mass spectral data to support molecular weight identity. High-resolution mass spectral HRMS data are preferred. UV or IR spectral data may be reported for the identification of characteristic functional groups, when appropriate. Melting-point ranges should be provided for crystalline materials.

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Specific rotations may be reported for chiral compounds. Authors should provide references, rather than detailed procedures, for known compounds, unless their protocols represent a departure from or improvement on published methods. Authors describing the preparation of combinatorial libraries should include standard characterization data for a diverse panel of library components. For new biopolymeric materials oligosaccharides, peptides, nucleic acids, etc. In these cases, authors must provide evidence of identity based on sequence when appropriate and mass spectral characterization.

Authors should provide sequencing or functional data that validates the identity of their biological constructs plasmids, fusion proteins, site-directed mutants, etc. Evidence of sample purity is requested for each new compound. Methods for purity analysis depend on the compound class. Detailed spectral data for new compounds should be provided in list form see below in the Methods section. Figures containing spectra generally will not be published as a manuscript figure unless the data are directly relevant to the central conclusions of the paper. Authors are encouraged to include high-quality images of spectral data for key compounds in the Supplementary Information.

Specific NMR assignments should be listed after integration values only if they were unambiguously determined by multidimensional NMR or decoupling experiments. Authors should provide information about how assignments were made in a general Methods section. Example format for compound characterization data. Manuscripts reporting new three-dimensional structures of small molecules from crystallographic analysis should include a.

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Crystallographic data for small molecules should be submitted to the Cambridge Structural Database and the deposition number referenced appropriately in the manuscript. Full access must be provided on publication. Manuscripts reporting new structures should contain a table summarizing structural and refinement statistics. Templates are available for such tables describing NMR and X-ray crystallography data.

If the reported structure represents a novel overall fold, a stereo image of the entire structure as a backbone trace should also be provided. Advanced search. Skip to main content. Author instructions Author instructions Before you submit Submission guidelines Ready to submit Post-publication. Submission guidelines. Cover letter Format of manuscripts Methods References Acknowledgements Author contributions Competing interests Data availability Supplementary information Figure legends Tables Equations General figure guidelines Figures for peer review Figures for publication Statistical guidelines Chemical and biological nomenclature and abbreviations Gene nomenclature Characterisation of chemical and biomolecular materials Format of articles Scientific Reports publishes original research in one format, Article.


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As a guideline and in the majority of cases, however, we recommend that you structure your manuscript as follows: Introduction Results with subheadings Discussion without subheadings Methods A specific order for the main body of the text is not compulsory and, in some cases, it may be appropriate to combine sections. Authors must provide a competing interests statement within the manuscript file. The format requirements of Scientific Reports are described below. Scientific Reports uses UK English spelling. Cover letter Authors should provide a cover letter that includes the affiliation and contact information for the corresponding author.

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