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BellCurve is a laboratory instrument designed to analyze and visualize data distributions. It provides a graphical representation of the frequency distribution of a set of data, allowing users to understand the underlying patterns and characteristics of the collected information.

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18 protocols using bellcurve

1

Recidivism Predictors for Incarcerated Individuals

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First, diagnostic classifications were examined to identify inmates’ diagnoses. The recidivism rate of each clinical diagnoses was calculated using the F-codes of the International Classification of Diseases, Tenth Revision. To examine the hypothesis that each diagnostic category is an independent predictor of recidivism, Kaplan–Meier survival analyses were conducted on the diagnostic categories for which there were a sufficient number of participants.
Second, we tested the hypothesis that each recidivism risk factor is associated with recidivism using recidivism 3 years after release as the dependent variable and the sociodemographic factors and risk factors associated with the C8 as the independent variables. A chi-square or Fisher's exact test was conducted [30 (link)]. The difference between the population mean test was performed for age. To calculate the effect size, Cohen's d was used for age and the φ coefficient was used for other variables.
Diagnostic categories that were found to be meaningful in the Kaplan–Meier survival analyses and risk factors were examined with Cox proportional hazards models to consider their value for recidivism. Age was included in the analysis after classification with reference to descriptive statistics.
BellCurve (Social Survey Research Information Co., Ltd., Japan) for Excel (Version 4.04) was used for all statistical analyses.
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2

Regional Differences in Student Responses

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The differences in student responses by region were compared between the Kanto region, where Tokyo is located, and other regions. Fisher’s test was conducted using the Bell Curve for Excel statistics (Social Survey Research Information Co., Ltd., Tokyo, Japan). All other comparison tests were analysed using EZR version 1.55 (Saitama Medical Centre, Jichi Medical University, Saitama, Japan), and the Bonferroni multiple comparison tests were applied. Statistical significance was set at P < 0.05.
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3

Statistical Analysis of Experimental Data

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Statistical significance was determined using a Student’s t-test with Excel 2019 (Microsoft Japan, Tokyo, Japan) or Tukey method with BellCurve (Social Survey Research Information, Tokyo, Japan).
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4

Polymer Effects on Mesenchymal Stem Cells

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Mouse mesenchymal stem cell line (D1 cell, ATCC® Number: CRL-12424™, cell passage 4) was seeded at a cell density of 9000 cells/cm2 with the control medium (Dulbecco’s modified eagle’s medium with 10% fetal bovine serum and 1% antibiotics) and cultured overnight to attach the cells. The cells were treated with the control medium (negative control group) or the media with poly(MalVE-co-EtMI) and poly(MalMI-co-LacVE) separately for an additional four days. The concentrations of each polymer varied from 0 to 100 μg·mL−1. WST-8 (Cell Counting Kit, Donjindo, Kumamoto, Japan) was used to assess the cell cytotoxicity in accordance with the manufacturer’s instruction. The absorbance was measured with microplate reader (SpectraMax M5; Molecular Devices, San Jose, CA, USA) at a wavelength of 450 nm. BellCurve (Social Survey Research Information Co., Ltd., Tokyo, Japan) was used for the statistical analysis. Statistical significance was evaluated using a one-way analysis of variance (ANOVA), followed by a Tukey–Kramer test. All results are presented as the mean ± standard deviation (SD) (n = 5).
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5

Growth and Physiological Parameters

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Data are presented as means of eight replicates (growth) or individual birds (all other
parameters) and were analyzed using two-way analysis of variance (ANOVA) using a bell
curve (Social Survey Research Information Co., Ltd., Tokyo, Japan). Differences were
considered significant at P < 0.05.
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6

Statistical Analysis of Multidimensional Data

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Statistical significance was determined using Student’s t-test with Excel 2019 (Microsoft Japan, Tokyo, Japan) or Tukey’s method with Bellcurve (Social Survey Research Information, Tokyo, Japan). Statistical processing, such as log transformation and scaling, and multivariate analysis (OPLS-DA and PCA) were performed using SIMCA 14.1 software (Infocom, Tokyo, Japan) [8 (link),34 (link)].
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7

Quantitative Western Blot Analysis

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The density of protein bands detected by Western blotting was measured using ImageJ (National Institutes of Health, Bethesda, MD, USA). For overexpression, siRNA, or cell viability assays, biological replicates were performed using three different samples. Three technical replicates were performed for the pull-down assay of HPSB5 and PLK2. Statistical significance was determined at p < 0.05 on Student’s t-test using Excel 2019 (Microsoft Japan, Tokyo, Japan). Multiple comparisons were performed using the Tukey method with BellCurve (Social Survey Research Information, Tokyo, Japan) [52 (link)].
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8

Evaluating Orthodontic Bracket Performance

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The Excel software BellCurve (version 3.21; Social Survey Research Information, Tomihisa, Japan) was used for statistical analyses. The means and standard deviations of the total viable counts and the ATP and OD values were calculated in each bracket from each of the three groups. One-way ANOVA and Tukey's test were used to analyze the effects of SRW on the total viable counts and ATP values in each bracket type. The Kruskal-Wallis and Steel-Dwass tests were used to determine significant differences in the action times of SRW on each bracket. Two-way ANOVA followed by the Tukey test was used to analyze the main effects of SRW on the different bracket types after the crystal violet assay. The parametric and nonparametric tests were performed after testing the normality of the distribution (Kolmogorov-Smirnov test) and the homogeneity of variance (Leven test). The level of significance was set at P < 0.05.
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9

Elemental Concentration Analysis Across Disciplines

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Data are presented as mean ± standard error of the mean. Analyses were performed using the Japanese language version of Lotus 2001 software (Microsoft Japan Co., Ltd., Tokyo, Japan) and Excel 2016 (Microsoft Japan Co., Ltd., Tokyo, Japan). The normality of data has been checked by the Kolmogorov–Smirnov test and the Shapiro–Wilk test. Because the data in the present study has shown a mixture of non-normal and normal and distribution, significant differences in elemental concentrations were tested for using the Kruskal–Wallis test. In addition, the Dunn test was used as a post hoc test. The differences in 2 variates were tested for using the Mann–Whitney U-test. Those statistical tests were performed using the Japanese language version of IBM statistics 19 (IBM Japan Ltd., Tokyo, Japan) and Bell curve (Social Survey Research Information Co., Ltd., Tokyo, Japan).
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10

Growth Performance and Blood Metrics

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All data were analyzed using BellCurve (Social Survey Research Information Co., Ltd., Tokyo, Japan). Data are presented as the mean of 6 replicates (growth performance) or 6 individual birds (blood parameters and mRNA levels). Statistically significant differences between the groups were identified using Student t test or two-way ANOVA, followed by Tukey's multiple comparison test. Differences were considered significant for values of P < 0.05.
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