SPSS software Ver. 25 was used for data entry and analysis. Descriptive statistics such as mean score and standard deviation, as well as frequency and percentages of all independent variables (age, gender, educational grade, etc. …), were used. Responses were scored by frequency and percentage then converted to percentage mean scores, then transformed to qualitative data as mentioned previously. To predict the significant predictors of student’s practice, multiple regression analysis was applied. Significance was considered at p-value < 0.05.
Spss software ver 25
Manufactured by IBM
Sourced in United States
SPSS software version 25 is a statistical analysis tool developed by IBM. It provides advanced analytical capabilities to help users interpret data, identify patterns, and make informed decisions. The software offers a range of statistical techniques, including regression analysis, hypothesis testing, and data mining, among others. SPSS software version 25 is designed to work with a variety of data formats and can be used across different industries and research fields.
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Lab products found in correlation
41 protocols using spss software ver 25
1
Predicting Student's Practical Skills
2
Investigating Factors Influencing Research
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All the experiments were conducted as triplicates. Chi-Square test was used to investigate the relationship between the tested factors. SPSS software ver. 25 (Chicago, IL, USA) was used for data analysis and P-value of less than 0.05 was considered as statistically significant.
3
Triplicate Statistical Analysis of Sensory Data
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All tests were performed in triplicate. Statistical data analysis was carried out using SPSS software ver. 25 (SPSS, Inc.). Data were expressed as mean ± standard deviation. Tukey's test was used to determine the significant difference among samples. Sensory data were analyzed using the Friedman nonparametric test. Statistical significance was stated at p < .05.
4
Factors Influencing COVID-19 Infection Rates
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We conducted a t test for continuous variables between the two types of areas considered (areas covered by the state of emergency and those not covered by the emergency), and we conducted a chi-squared test to evaluate the differences in pro-portions between the covered and non-covered areas. To clarify the association between the number of active users per 1,000 households and the cumulative infection rate or geographical distance from Tokyo (Japan’s capital city, which exhibited the highest cumulative infection rate) or the prefectures wherein a state of emergency was declared for COVID-19, we generated scatterplots and asymptotic lines. The associations were evaluated by means of Pearson’s correlation coefficient. A p value of ≤0.05 was considered statistically significant. We analyzed all data using SPSS software (ver. 25; SPSS Inc., Chicago, IL). In the study, the continuous variables are presented as means with SD.
5
Neoadjuvant Therapy for Operable NSCLC
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All analyses were performed using SPSS software ver. 25. The MPR in the SOX group was estimated to be 15%, and a calculated sample size of 70 patients per group was needed assuming an improvement in MPR by DOS of 35%, with αlevel of 0.05 (two-sided) and test power of 0.8. Considering a drop-out rate of 5%, 74 patients per group were required. Patients who withdrew their consent before undergoing preoperative chemotherapy were excluded from the analysis. The remaining patients, who were randomized and received any form of study treatment, were included in the mITT population. The MPR, survival, chemotherapy safety, and resection analyses were conducted in the mITT population, while the pathological stage and postoperative complication analyses were performed on patients who underwent surgery (surgery population). PFS and OS were analyzed by the Kaplan–Meier method. Categorical data between these two groups were compared using the chi-squared test. All P-values were 2-sided.
6
Factors Influencing Hearing Recovery Post-Treatment
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Finally, the collected information was entered into Statistical Package for the Social Sciences (SPSS) software (ver. 25) and the data were reported as mean ± standard deviation (SD) or frequency (percentage).
Fisher’s exact and Chi-square tests were used to compare the frequency distribution of qualitative data between the two groups, and independent-samples t-test was used to compare the mean of quantitative data. Logistic regression analysis was also used to assess the factors associated with the percentage of hearing recovery immediately after completion of treatment (grades I and II compared with grades III and IV) in patients. In this regard, odd ratio (OR) and confidence interval (CI) were reported. In all analyses, a significance level of less than 0.05 was considered.
Fisher’s exact and Chi-square tests were used to compare the frequency distribution of qualitative data between the two groups, and independent-samples t-test was used to compare the mean of quantitative data. Logistic regression analysis was also used to assess the factors associated with the percentage of hearing recovery immediately after completion of treatment (grades I and II compared with grades III and IV) in patients. In this regard, odd ratio (OR) and confidence interval (CI) were reported. In all analyses, a significance level of less than 0.05 was considered.
7
Evaluating Caring Behavior in Cancer Treatment
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SPSS software (ver. 25) was utilised for data analysis. The normal distribution of quantitative data was examined using the Kolmogorov-Smirnov test, indicating the normal distribution of all data. Descriptive statistics were reported as mean ± SD for quantitative variables and as frequency (%) for categorical variables. Repeated Measures ANOVA and post hoc with Bonferroni adjustment were used. A linear mixed model was performed to assess the effect of time and self-efficacy on the caring behaviour adjusting for family size, mother's age, mother's job, mother's education, and frequency of chemotherapy sessions. The significance level was set at P < 0.05.
8
Evaluating Caring Behavior in Cancer Treatment
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SPSS software (ver. 25) was utilised for data analysis. The normal distribution of quantitative data was examined using the Kolmogorov-Smirnov test, indicating the normal distribution of all data. Descriptive statistics were reported as mean ± SD for quantitative variables and as frequency (%) for categorical variables. Repeated Measures ANOVA and post hoc with Bonferroni adjustment were used. A linear mixed model was performed to assess the effect of time and self-efficacy on the caring behaviour adjusting for family size, mother's age, mother's job, mother's education, and frequency of chemotherapy sessions. The significance level was set at P < 0.05.
9
Statistical Analysis of Experimental Data
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Data management and statistical analyses were performed using SPSS software ver. 25. Numerical data are summarized as means and standard deviations. Categorical data are summarized as numbers and percentages. Comparisons among the three groups with regard for normally distributed numeric variables were performed using ANOVA. Categorical variables were compared using the Chi-square test. Pearson correlations were performed. “r” is the correlation coefficient and it ranged from −1 to +1, with −1 indicating a strong negative correlation, +1 indicating a strong positive correlation, and 0 indicating no correlation. All p-values were two-sided. p-values less than 0.05 were considered significant. The p-values were adjusted for multiple comparisons.
10
Thermal Stimulation Effects on Pain
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