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MagicStat is a*Cost-effective data analysis:***free**data analysis tool. Thatâ€™s why youâ€™re here, right?You do the stuff youâ€™re good at; let us do the stuff weâ€™re good at.*No deep statistics knowledge needed:*Chrome, FireFox, Safari, and Microsoft Edge.*Easy access via any web browser, anytime, anywhere:*Our interface is entirely pointy-clicky, so no need to code any commands like those other packages.*No coding needed:*Ooooh, pretty!*Rich visual analytics integration:*We let you import and export your data in well-known file formats on our system:*Data import/export support:*- Comma-separated (.csv)
- Microsoft Excel (.xls, .xlsx)
- SPSS (.sav, .zsav)
- More data types coming soon...

**Pearson correlation:**A widely-used parametric test that measures the strength and direction of the relationship between linearly related variables and is the appropriate correlation analysis when two measured variables are normally distributed.**Spearman's correlation:**A non-parametric test that is used to measure the degree of association between two variables. It is the appropriate correlation analysis when the variables are measured on a scale that is at least ordinal.**Kendall correlation:**A non-parametric test that measures the strength of dependence between two variables.**Chi-Square Goodness-of-Fit Test:**Used to determine whether sample data are consistent with a hypothesized distribution when you have one categorical variable from a single population.**Chi-Square Goodness Test for Independance:**Used to determine whether there is a significant association between two categorical variables from a single population.**Independent Samples**Parametric method that compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different.*t*-test:**Paired Samples**Used to determine whether there is statistical evidence that the mean difference between paired observations on a particular outcome is significantly different from zero.*t*-test:**One Sample**A parametric test that determines whether the sample mean is statistically different from a known or hypothesized population mean*t*-test:**Logistic Regression (Logit):**Predictive analysis used to describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables**Linear Regression:**Used to summarize and study relationships between two continuous (quantitative) variables**One-Way Between Subjects ANOVA (One-Way Non-repeated Measures ANOVA):**Used to determine whether there are any statistically significant differences between the means of two or more independent (unrelated) groups.**Two-Way Between Subjects ANOVA (Factorial Non-repeated Measures ANOVA):**Used to determine whether there are any statistically significant differences between the means of two or more independent (unrelated) groups of the given two factors.**One-Way Within Subjects ANOVA (One-Way Repeated Measures ANOVA):**Used to compare three or more group means where the participants are the same in each group and one factor is repeatedly tested.**Two-Way Within Subjects ANOVA (Factorial Repeated Measures ANOVA):**There are two within subjects factors which are repeatedly tested and used to compare three or more group means where the participants are the same in each group.**Two-Way Between Subjects and Within Subjects ANOVA (Mixed Factorial ANOVA):**There is a between subjects factor and a within subjects factor which is used to compare three or more group means of two factors where the participants are the same in each group.**More Models Coming Soon**