Statistical package for the social sciences

Data analysis is one of the most flourishing fields right now as businesses around the world are trying to make sense of their data. However, there are a number of data analysis tools available in the market. In this article, we are going to discuss the Statistical Package for the Social Sciences (SPSS): one of the most-used statistical analysis tools.In this article, we’re going to explore:What is SPSS software?What are the core features of SPSS?Types of SPSSSPSS by industry: Use casesBenefits of SPSS predictive analytics (for all industries)Advantages of SPSSLimitations of SPSSWhat is SPSS Software?It is a suite of software programs that analyzes scientific data related to the social sciences. SPSS offers a fast-visual modeling environment that ranges from the smallest to the most complex models. The data obtained from SPSS is used for surveys, data mining, market research, etc.SPSS was originally launched in 1968 by SPSS Inc., and IBM acquired it in 2009.SPSS is popular because of its simplicity, easy-to-follow command language, and well-documented user manual. Government entities, educational institutions, survey companies, market researchers, marketing organizations, health researchers, data miners, and many others use it for analyzing survey data.What are the Core Features of SPSS?The core functionalities offered in SPSS are:Statistical program for quantitative data analysis – It includes frequencies, cross-tabulation, and bivariate statistics.Modeler program that allows for predictive modeling. It enables researchers to build and validate predictive models using advanced statistical procedures.Text analysis helps you derive insights from qualitative inputs through open-ended questionnaires.Visualization Designer allows researchers to use

Modern statistical software provides the ability to compute statistics in a timely, orderly fashion. This introductory statistics textbook presents clear explanations of basic statistical concepts and introduces students to the IBM SPSS program to demonstrate how to conduct statistical analyses via the popular point-and-click and the "syntax file" methods. The focal point is to show students how easy it is to analyse data using SPSS once they have learned the basics.Provides clear explanation of basic statistical concepts that provides the foundation for the beginner students’ statistical journey.Introduces the SPSS software program.Gives clear explanation of the purpose of specific statistical procedures (e.g., frequency distributions, measures of central tendencies, measures of variability, etc.).Avoids the conventional cookbook approach that contributes very little to students’ understanding of the rationale of how the correct results were obtained.The advantage of learning the IBM SPSS software package at the introductory class level is that most social sciences students will employ this program in their later years of study. This is because SPSS is one of the most popular of the many statistical packages currently available. Learning how to use this program at the very start not only familiarizes students with the utility of this program but also provides them with the experience to employ the program to conduct more complex analyses in their later years.

Items and research and related to programs including physical education, athletics, movement, and sport sciences. 3 EXSS 6352 Research Methods in Sport Administration This course will explore qualitative research design and analysis. This course will serve as an introduction to statistics, experimental design, and proposal writing. Developmental theory, investigation and gathering of data, statistical analysis and evaluation, and research reporting as these relate to research in exercise science. 3 EXSS 6353 Research Methods This class will introduce students to the research process in public health and health sciences. An emphasis will be placed on the application of research design, data collection methods, and data analysis procedures used in quantitative and qualitative research. 3 EXSS 6355 Clinical Exercise Physiology Advanced theory and practical application to clinical aspects of exercise physiology, exercise testing and prescription, ECG analysis and interpretation, and pharmacotherapy. Concentration is focused on diseased and disabled populations that are observed in clinical settings. Prerequisite: EXSS 3395 3 EXSS 6360 Biostatistics This course will introduce biostatistics used in the fields of public health and health sciences. Students will develop an understanding of hypothesis testing, descriptive statistics, and methods for comparing discrete and continuous data including analysis of variance (ANOVA), t-test, correlation, and regression. Students will learn basic steps to analyze quantitative data using the Statistical Package for the Social Sciences (SPSS) and the interpretation of analysis results. 3 EXSS 6365 Exercise Endocrinology An in-depth examination of the role of the endocrine system on metabolism and how nutrition affects hormonal control, regulation, substrate availability, catabolism and anabolism. The scope will focus on the role of the endocrine system in response to exercise in the human body. Prerequisite: EXSS 6380 or equivalent. 3 EXSS 6370 Sport Psychology An in-depth study an application of the psychological principles relating to the coaching profession. Emphasis will be placed on principles which influence behavior, enhance skill acquisition and maximize sport performance of athletes and coaches involved in sport. 3 EXSS 6375 Exercise & Nutritional Biochemistry A study of the biochemistry of humans in relation to nutrition and exercise with an emphasis on the basic elements of carbohydrate,

ATSA/rTSA, categorized by chronic preoperative steroid useFull size tableStatistical analysisAll data were analyzed using descriptive and comparative statistics. An independent samples t-test was used for continuous variables. Pearson’s chi-square or Fischer’s exact test was employed, whenever appropriate, for categorical variables. Propensity score matching utilizing a nearest neighbor within-caliper strategy was used to control for baseline preoperative differences between the two cohorts, including both modifiable and non-modifiable risk factors. Matching was performed based on the following variables: gender, age, race, ethnicity, BMI, functional status, ASA, smoking status, alcohol use, year of operation, and comorbidities (diabetes, dyspnea, COPD, ascites, history of congestive heart failure, coronary artery disease, peripheral vascular disease, renal failure, weight loss, bleeding disorders, history of blood transfusion, and hypertensive medication use). Matching involved two controls (no steroid use) for each case (steroid use) using a caliper width of 0.01 on the propensity score. Of the 1,157 cases, virtually all (1,131, 97.8%) were successfully matched with two controls, with the remaining 26 matched to one control. Balance on baseline demographic and clinical features between groups was assessed with standardized difference, where a difference of less than 0.20 is considered comparable. The conditional logistic regression model used the matched groupings as strata and steroid use as the predictor variables to calculate odds ratios for each outcome. All statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) 29 and statistical significance was set at an alpha level of 0.05.ResultsThis review of the NSQIP database for aTSA/rTSA yielded 23,581 operations

Last Updated: March 3rd, 2025 Our analysts compared Hadoop vs SPSS Statistics based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform. Apache Hadoop is an open source framework for dealing with large quantities of data. It’s considered a landmark group of products in the business intelligence and data analytics space, and is comprised of several different components. It functions on basic analytics principles like distributed computing, large data processing, machine learning and more.Hadoop is part of a growing family of free, open source software (FOSS) projects from the Apache Foundation, and works well in conjunction with other third-party products. read more... IBM SPSS, or Statistical Product and Service Solutions, is a data analysis platform that provides advanced statistical insights to propel business decision-making and research by crunching large datasets. With a user-friendly interface, it empowers everyone from basic users to experienced data scientists to perform statistical analysis. Scalable and agile, it is suitable for companies of all sizes. Users can purchase it through an on-premises license or a subscription plan to a hybrid SaaS. Users who choose either monthly or annual subscription receive access to the base version and can choose which of three optional add-ons to include, if any, between Custom Tables and Advanced Statistics, Complex Sampling and Testing, and Forecasting and Decision Trees.Perpetual and term licensees can choose between four editions that offer different levels of functionality: Base, standard, professional and premium. It was first launched as Statistical Package for the Social Sciences by three Stanford students in 1968 and later acquired by IBM in 2009. read more... Undisclosed Free Trial is unavailable → $99 Monthly SmallMediumLarge SmallMediumLarge WindowsMacLinuxAndroidChromebook WindowsMacLinuxAndroidChromebook CloudOn-PremiseMobile CloudOn-PremiseMobile DocumentationIn PersonLive OnlineVideosWebinars DocumentationIn PersonLive OnlineVideosWebinars EmailPhoneChatFAQForumKnowledge Base24/7 Live