Normally Distributed Data
Visually (with QQ-plots and histograms) or statistically (with tests like D'Agostino-Pearson and Kolmogorov-Smirnov), you may see if your data are normally distributed. It's unusual, nevertheless, that you'll need to check if your data is normal.
Statistical models such as ANOVA, linear regression, and nonlinear regression are most likely being used to fit your data. The residuals, or the differences between the model predictions and the observed data, must be NORMALLY distributed in these circumstances.
To obtain meaningful statistical inference such as confidence intervals, coefficient estimates, and p values, the residuals must be approximately normally distributed.
Height, blood pressure, measurement error, and IQ scores, for example, all follow the normal distribution. It's also known as the bell curve or the Gaussian distribution.
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