comeiop.blogg.se - Ibm spss statistics 21.0

Ibm spss statistics 21.0 software#

The new simulation modeling feature within IBM SPSS Statistics Base uses Monte Carlo simulation techniques and is designed to account for uncertainty in inputs for predictive models. To ensure that the most advanced techniques are available to a broader group of analysts and business users, you get enhancements to the features and capabilities of IBM SPSS Statistics Base and its many specialized modules. The IBM SPSS Statistics family delivers the core capabilities needed for end-to-end analytics.

Build a predictive enterprise making the business more agile and maximizing return on investmentįor details, refer to the Technical information section.Īnalytics plays an increasingly important role in helping an organization achieve its objectives.

Process and deploy analytics faster with flexible deployment options.

Reveal deeper insights and provide better confidence intervals via visualizations and geographic spatial analysis.

Quickly understand large and complex datasets using advanced statistical procedures that can provide high accuracy to drive quality decision making.

Organizations use IBM SPSS Statistics to help:

Ibm spss statistics 21.0 software#

IBM SPSS Statistics is a leading statistical software product used to solve business and research problems by means of ad-hoc analysis, hypothesis testing, geospatial analysis and predictive analytics.

Integrating with other technologies and tools making it easy to access common data types, external programming languages, and file types.

Providing faster performance with more accurate results, increased productivity and effectiveness using a range of specialized techniques.

Building better models from uncertain inputs while assessing risk using Monte Carlo simulation techniques.

This means that mobile games may serve as an educational aid to these patients.ĭiabetes Education Mobile Game Mobile-Health. Conclusion: The mobile game (Amoo) could enhance the knowledge of patients with type 2 diabetes about food calories and glycemic index. However, there was no significant difference in fasting blood sugar (p=0.125). Results: The results indicated a statistically significant difference between the pre and post test scores in the intervention group (p<0.001). A P-value less than 0.05 was considered as a significant level. Data were analyzed using paired t test and suitable non-parametric testes including Mann-Whitney and Wilcoxon signed rank tests as well as Spearman and Pearson correlation coefficients via IBM SPSS statistics version 21 (SPSS, v 21.0, IBM, Armonk, NY, USA). A post-intervention test was run to show a possible improvement in dietary information.

The participants were randomly divided into one of two groups, including the intervention group: played the game for 15 minutes daily for 6 weeks, and the control group: did not involve in the game. The participants took part in a pre-intervention test to determine their dietary information.

Sixty patients with type 2 diabetes participated in the study. Methods: A mobile game (called Amoo), which was developed by researchers of this study, was applied to assess the self-education of patients with diabetes. The aim of the present study was to evaluate the effect of a mobile game (Amoo) implementation on enhancing dietary information in patients with type 2 diabetes. Application of digital games in patient's education can improve self-management of diabetes. Background: Nowadays, digital games are not just entertainment, but beside routine treatments, they are used in patient care, especially in patients with diabetes.