Simply select the columns you want to analyze-and away you go! I can run any statistical analysis in less than 5 minutes and return to my same dataset-with a new perspective. This makes it easy to work from existing Excel workbooks, without having to re-format and re-code data tables. XLSTAT provides all the common statistics analyses I need for my research and it works seamlessly-integrated into Excel-which is a huge plus. The cost is reasonable if you compare it with the time saved. I highly recommend it for students as well as more senior researchers. I have been able to run every common statistical analysis with this program. The results simply appear as a new worksheet, to which I can return at a later time, if need be. In less than 5 minutes I can run all kinds of statistical analyses (and try out different approaches) to resolve a specific question, and then return to my raw data Excel spreadsheet without having to hop around between different applications. XLSTAT has been a "one-stop" statistical analysis tool for me, a real time-saver, improving my ability to explore complex datasets without hopping around different programs. Versatile, easy-to-use, all-you-need statistics package Not suitable for processing a big dataset with 10 million rows such as high-resolution remote sensing images
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XLSTAT has all standard features and algorithms of machine learning software which can be operated by editing simple spreadsheets. Data preparation is the single tedious task which consumes most of the time in a data science project. XLSTAT can process even spatial data as raster to CSV converted files and enables to prepare the data just like in Excel. In short, XLSTAT is a workhorse for data scientists with a few simple mouse clicks and visualizing the response in every step as stunning graphics. This is where XLSTAT becomes the default platform for data science projects. In this situation, undergraduates who only have some basic operational knowledge about Excel spreadsheets are easily drawn into using a data science platform which runs on the already familiar Excel and transforms their data in spreadsheets into powerful and efficient models. This tutoring approach goes a long way in encouraging students towards a dissertation project involving data-driven modelling. This includes even spatial and time-series data. In the academic milieu, we regularly face the task of explaining students of how statistical models are built from a set of data and their specific applications accompanied by demonstrations in the classroom. With XLSTAT, the first one in the list alone is sufficient enough to successfully accomplish the goal the rest is taken care of by XLSTAT. Sampling, data preparation, exploratory data analysis to building prediction models with state-of-the-art machine learning algorithms generally encompasses a set of requirements: a clear objective, a software with all standard features and algorithms, intuition, technical guidance, and probably, also experience.
Use this information to assess whether the data are approximately normal.XLSTAT can be best described as the software for data science from beginner to advanced levels that can be operated without the need of technical guidance. An XLSTAT normal probability plot follows. Use this information to assess whether the data are approximately normal.ī. Descriptive statistics for the drug concentrations are shown at the top of the XLSTAT printout on the next page. Drug concentrations (measured as a percentage) for 50 randomly selected tablets are listed in the table below and saved in the accompanying file.Ī. Scientists at GlaxoSmithKline Medicines Research Center used high-performance liquid chromatography (HPLC) to determine the amount of drug in a tablet produced by the company (Analytical Chemistry, Dec. Use the Minitab printout (next page) to help the scientists draw a conclusion.ĭrug content assessment. The scientists want to know whether there is any difference between the mean drug concentration in tablets produced at Site 1 and the corresponding mean at Site 2. Drug concentrations (measured as a percentage) for the tablets produced at the two sites are listed in the table below. Twenty-five tablets were produced at each of two different, independent sites. 15, 2009) study in which scientists used high-performance liquid chromatography to determine the amount of drug in a tablet. 05 to conduct the appropriate test for the researchers.ĭrug content assessment. Locate the test statistic and p-value on the printout. A Minitab printout of the analysis follows. The researchers want to determine if the two sites produced drug concentrations with different variances. Recall that 25 tablets were produced at each of two different, independent sites.
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