Start Date: 08/09/2020
Course Type: Common Course |
Course Link: https://www.coursera.org/learn/data-analysis-tools
Explore 1600+ online courses from top universities. Join Coursera today to learn data science, programming, business strategy, and more.In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.
This session starts where the Data Management and Visualization course left off. Now that you have selected a data set and research question, managed your variables of interest and visualized their relationship graphically, we are ready to test those relationships statistically. The first group of videos describe the process of hypothesis testing which you will use throughout this course to test relationships between different kinds of variables (quantitative and categorical). Next, we show you how to test hypotheses in the context of Analysis of Variance (when you have one quantitative variable and one categorical variable). Your task will be to write a program that manages any additional variables you may need and runs and interprets an Analysis of Variance test. Note that if your research question does not include one quantitative variable, you can use one from your data set just to get some practice with the tool. If your research question does not include a categorical variable, you can categorize one that is quantitative.
Data Analysis Tools In this course, we’ll focus on the use of data to inform decision making. We’ll cover statistical techniques for independence testing (I&D), univariate logistic regression, and multivariate Poisson regression. You’ll learn about the different types of I&D, namely clustered, univariate, and mixed effects. We’ll also cover basic multivariate Poisson regression, which is the technique used to fit the Poisson distribution. We’ll use an example case to demonstrate the concepts. We’ll also cover some advanced techniques for independence testing. You’ll learn about noise in regression, the use of different regression models, and independence testing. An important component of independence testing is the use of a series of t-tests for equality. You’ll learn about these statistical tests and the appropriate strategy for using them. You’ll also learn about Poisson regression, which is the technique we use to fit the Poisson distribution. We’ll use an example case to demonstrate the concepts. We’ll also cover some advanced techniques for independence testing. You’ll learn about noise in regression, the use of different regression models, and independence testing. An important component of independence testing is the use of a series of t-tests for equality. You’ll learn about these statistical tests and the appropriate strategy for using them. You’ll also learn about Poisson regression, which is
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GemIdent | GemIdent also packages data analysis tools to investigate spatial relationships among the objects identified. |
Harlequin (software company) | Other products included data analysis tools created using LispWorks, the Lisp IDE. |
Buzz monitoring | The collected information can then be restrained using data analysis tools, built on Structured Query Language (SQL) for later use. |
GNU Data Language | GDL is licensed under the GPL. Other open-source numerical data analysis tools similar to GDL include GNU Octave, NCAR Command Language (NCL), Perl Data Language (PDL), R, Scilab, SciPy, and Yorick. |
Visiscience | VisiScience Corporation has a targeted product offering specializing in presentation software, data analysis tools and internet based software systems for scientists and educators in the following fields: |
Bird Technologies | Its products include real-time RF capture and storage solutions, digital wideband waveform generators, Radio Frequency data analysis tools, and a line of Naval Tactical Data System (NTDS) devices. |
NK News | As well as functioning as a news outlet, NK News also provides subscription-based data analysis tools designed for use by experts. These include the North Korea Leadership Tracker, the Ship Tracker, Leading Indicators and KCNA Watch. |
MAXQDA | The standard version of MAXQDA for macOS and Windows offers tools for the organisation and analysis of qualitative data. This includes text, audio, image, video and bibliographical files as well as survey data, Twitter tweets or focus group transcripts. The data can be analysed in a four-screen window with the help of codes and memos. MAXQDA’s visualisation functions and export options facilitate presentations. MAXQDA includes some quantitative data analysis tools (e.g. Mixed Methods tools). |
Whitebox Geospatial Analysis Tools | Whitebox GAT contains more than 385 tools to perform spatial analysis on raster data sets. The following is an incomplete list of some of the more commonly used tools: |
Sorin Draghici | His research area is computational biology and bioinformatics. His research has been supported by the National Science Foundation, National Health Institutes and others. He has published over 190 scholarly papers and two technical books: Statistics and Data Analysis for Microarrays Using R and Bioconductor and Data Analysis Tools for DNA Microarrays. |
Data analysis | Data integration is a precursor to data analysis, and data analysis is closely linked to data visualization and data dissemination. The term "data analysis" is sometimes used as a synonym for data modeling. |
Minimum Information Standards | The minimum information standard is a set of guidelines for reporting data derived by relevant methods in biosciences. If followed, it ensures that the data can be easily verified, analysed and clearly interpreted by the wider scientific community. Keeping with these recommendations also facilitates the foundation of structuralized databases, public repositories and development of data analysis tools. |
Reactome | The website can be used to browse pathways and submit data to a suite of data analysis tools. The underlying data is fully downloadable in a number of standard formats including pdf, SBML and Biopax. Pathway diagrams use a Systems Biology Graphical Notation (SBGN)-based style. |
Memory forensics | Prior to 2004, memory forensics was done on an "ad hoc" basis, using generic data analysis tools like strings and grep. These tools are not specifically created for memory forensics, and therefore are difficult to use. They also provide limited information. In general, their primary usage is to extract text from the memory dump. |
Cellebrite | Cellebrite Wireless Carriers & Retailers produces hardware and software for phone-to-phone data transfer, backup, mobile applications electronic software distribution, and data analysis tools. Cellebrite Wireless Carriers & Retailers products are used by various mobile operators, and are deployed in wireless retail points of sale. Cellebrite works with handset manufacturers to ensure compatibility before devices are released to the public. |
Qunb | Qunb additionally provides a standard data visualization service for Google Analytics. The Google Analytics GAPI is used to extract key performance indicators from Google Analytics dashboard metrics without the use of third-party data analysis tools. The dimensions and nodes are processed on Qunb servers. |
Business intelligence | Critics see BI as evolved from mere business reporting together with the advent of increasingly powerful and easy-to-use data analysis tools. In this respect it has also been criticized as a marketing buzzword in the context of the "big data" surge. |
Data analysis | The most important distinction between the initial data analysis phase and the main analysis phase, is that during initial data analysis one refrains from any analysis that is aimed at answering the original research question. The initial data analysis phase is guided by the following four questions: |
Whitebox Geospatial Analysis Tools | Whitebox Geospatial Analysis Tools (GAT) is an open-source and cross-platform Geographic information system (GIS) and remote sensing software package that is distributed under the GNU General Public License. It has been developed by the members of the University of Guelph Centre for Hydrogeomatics and is intended for advanced geospatial analysis and data visualization in research and education settings. The package features a friendly graphical user interface (GUI) with help and documentation built into the dialog boxes for each of the more than 410 analysis tools. Users are also able to access extensive off-line and online help resources. The Whitebox GAT project started as a replacement for the Terrain Analysis System (TAS), a geospatial analysis software package written by John Lindsay. The current release support raster and vector (shapefile) data structures. There are also extensive functionality for processing laser scanner (LiDAR) data contained with LAS files. |
Data analysis | In the main analysis phase either an exploratory or confirmatory approach can be adopted. Usually the approach is decided before data is collected. In an exploratory analysis no clear hypothesis is stated before analysing the data, and the data is searched for models that describe the data well. In a confirmatory analysis clear hypotheses about the data are tested. |