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Statistical package for the social sciences spss software version 22

Manufactured by IBM
Sourced in United States

The Statistical Package for the Social Sciences (SPSS) software version 22.0 is a data analysis and statistical software application. It provides tools for data management, data analysis, and reporting. SPSS 22.0 supports a variety of data types and offers a range of statistical analysis techniques.

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4 protocols using statistical package for the social sciences spss software version 22

1

Nutritional Evaluation of Wild Fruits and Vegetables

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Data were analyzed using IBM Statistical Package for the Social Sciences (SPSS) software version 22.0. Kolmogorov–Smirnov and Shapiro–Wilk tests were performed to check for normality of data for various aspects. Normality tests revealed that data on levels of antinutritional factors, levels of total iron, and levels of bioavailability of iron were normally distributed. However, data on percentage contribution of WFV to the pooled household annual RDA for the micronutrient were not normally distributed. On this basis, differences in the level of each antinutritional factor, total iron, and bioavailable iron among fruits or vegetables species studied were determined using one‐way analysis of variance (ANOVA). Means were separated using Tukey's honestly significant difference (HSD) test. Pooled antinutritional factor content, total iron, and bioavailable iron between fruits and vegetables were compared using independent sample t test. Finally, the contribution of WFV to the pooled annual RDA for iron among households in the study area was estimated by calculating the median of the percentage contribution attained for the sample size of 192 households that were involved in the study. For all statistical analysis, the level of significance was fixed at 5%.
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2

Comparing Public and Private Programs

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To investigate differences in patient characteristics and barriers between participants attending public versus private programs, Fisher's exact tests or independent-sample t tests were used (or the Mann-Whitney U test if the variables were not normally distributed, as per the Kolmogorov-Smirnov test), as appropriate. Statistical significance was set at 5%. The analyses were performed using the IBM Statistical Package for the Social Sciences (SPSS) software, version 22.0 (SPSS Inc., Chicago, Illinois, United States).
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3

Longitudinal Analysis of Social Support

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IBM Statistical Package for the Social Sciences (SPSS) software, version 22 (IBM, Chicago, Illinois) was used for data analysis. Mean value ± standard deviation (SD) was calculated to present quantitative data such as age and SSS score. Frequency (%) was measured for categorical data such as gender. Repeated measures analysis of variance (ANOVA) test was applied; further, multiple comparisons were also performed, for that Bonferroni test was used to compare SSS score at baseline score, at fourth, and at eighth week. P value ≤ 0.05 was considered as significant.
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4

Assessing eHealth Literacy and Influencing Factors

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It used descriptive and analytical statistics to analyze the data. To analyze the data, IBM Statistical Package for the Social Sciences (SPSS) software version 22 was used. To determine the level of eHealth literacy, we divided the obtained score into three parts, from 0 to 20, weak, from 20 to 30, intermediate, and above 30 at the optimal level. Independent sample t-tests to compare the average eHealth literacy score between two groups of gender (male and female) and smoking were used. Also, it uses the one-way ANOVA to investigate the relationship between demographic data (such as age and education level) and eHealth literacy. The Spearman correlation coefficient test, to summarize the strength and direction of a relationship between two variables, was used to find which variables can predict high eHealth literacy scores.
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