A category split means respondents below the observed median go into one category and respondents above the median go into another. When a data set is bimodal, a median split of the data will lead to error.
Unimodal distribution is when the data set has a single mode. Professor Greenfield's first class, the one that scored primarily B's on the math test, would be considered a unimodal distribution. Sometimes, a single mode doesn't describe the data properly. Take Professor Greenfield's second class for example.
Professor Greenfield can describe his data using unimodal and bimodal distribution. Unimodal distribution is when the data set has a single mode, like the professor's first class that scored mostly B's. Bimodal distribution is where the data set has two different modes, like the professor's second class that scored mostly B's and D's equally.
Because this set of data has two numbers that appear the most, it is considered to have bimodal distribution. Be careful when you are looking at bimodal distribution. You must have two distinct peaks of numbers. Look at this data set: 4, 6, 2, 10, 4, 7, 6, 4, 9, 7.
In a symmetrical distribution, the mean, median, and mode are all equal.
A unimodal distribution is a probability distribution with one clear peak. This is in contrast to a bimodal distribution, which has two clear peaks: This is also in contrast to a multimodal distribution, which has two or more peaks: Note: A bimodal distribution is just a specific type of multimodal distribution.
In a left skewed distribution, the mean is less than the median.
A simple tabulation of a variable's frequency distribution is sometimes called a marginal tabulation.
The row and column totals in a contingency table are called subtotals because they are less than the total.
Coding is the process of assigning a numerical score or other character symbol to previously edited data.
Combining the data from adjacent categories of a Likert-scale item is a common form of data transformation.
When a third variable inserted into the analysis changes the results when two other variables were studied previously, this third variable is called a moderator variable.