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  1. 3 days ago · Using IBM SPSS Regression with IBM SPSS Statistics Base gives you an even wider range of statistics so you can get the most accurate response for specific data types. IBM SPSS Regression includes: Multinomial logistic regression (MLR): Regress a categorical dependent variable with more than two categories on a set of independent variables.

  2. 1 day ago · For data management and statistical analyses, we used IBM SPSS Statistics versions 25.0 and 28.0 (SPSS Inc., Chicago, IL, USA), SAS Enterprise Guide 8.3, and the R Stats packages version 4.1.2 with the survival package for the Cox proportional hazards regression analysis.

  3. 3 days ago · The Descriptives procedure is used to find the measures of central tendency (mean, median, mode) and measures of dispersion (range, standard deviation, variance, minimum and maximum) and measures of kurtosis and skewness. This procedure is best suited to describe continuous variables.

  4. 2 days ago · By Diana Toma posted an hour ago. We are pleased to announce that IBM SPSS Statistics has been recognized as a leader in the Statistical Analysis Global Grid Report by G2, a leading software review platform. This recognition highlights our commitment to providing a high-quality product that meets the needs of our customers.

  5. 4 days ago · IBM Corp. IBM SPSS statistics for windows, version 28.0. Armonk; 2021. Bower ES, Wetherell JL, Mon T, Lenze EJ. Treating anxiety disorders in older adults: current treatments and future directions. Harv Rev Psychiatry. 2015;23(5):329–42. Article PubMed Google Scholar

  6. 5 days ago · Integrate, explore and model location and time data, and capitalize on new data sources to solve new business problems. The Spatio-Temporal Prediction (STP) technique can fit linear models for measurements taken over time at locations in 2D and 3D space.

  7. 4 days ago · SPSS (Statistical Package for the Social Sciences), also known as IBM SPSS Statistics, is a software package used for the analysis of statistical data. SPSS provides data analysis for descriptive and bivariate statistics, numeral outcome predictions and predictions for identifying groups.

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