Do I need to transform my data?
If you visualize two or more variables that are not evenly distributed across the parameters, you end up with data points close by. For a better visualization it might be a good idea to transform the data so it is more evenly distributed across the graph.
Does it matter if data is not normally distributed?
Many practitioners suggest that if your data are not normal, you should do a nonparametric version of the test, which does not assume normality. But more important, if the test you are running is not sensitive to normality, you may still run it even if the data are not normal.
Does the dependent variable have to be normally distributed?
So is the normality assumption necessary to be held for independent and dependent variables? The answer is no! The variable that is supposed to be normally distributed is just the prediction error.
How do you turn data into information?
Use tools that help you analyze the information and data you have. Export the data from your system if necessary and load it into Excel. Use Excel’s pivot table tool to analyze data and convert it into information. You can use other software or enterprise systems that are designed for data analysis as well.
How to transform data to a normal distribution?
If you have run a histogram to check your data and it looks like any of the pictures below, you can simply apply the given transformation to each participant’s value and attempt to push the data closer to a normal distribution. Figure from Stevens (2002) Applied Multivariate Statistics for the Social Sciences 5th ed.
How can you tell if data is normally distributed?
There are two ways to determine if the data are normally distributed. First, if the points fall along a straight line, then the data probably came from a normal distribution. You can also calculate the Anderson-Darling statistic and determine the p-value associated with that statistic.
How are errors assumed to follow a normal distribution?
In linear regression, errors are assumed to follow a normal distribution with a mean of zero. Let’s do some simulations and see how normality influences analysis results and see what could be consequences of normality violation.
Is there a way to change the distribution of data?
Sometimes, though, this is not what the data look like. A possible way to fix this is to apply a transformation. Transforming data is a method of changing the distribution by applying a mathematical function to each participant’s data value.