An introduction to the independent t-test. Learn when you should run this test, what variables are needed and what the assumptions you need to test for first.
Independent variables are quantities that in a study context are seen as not depending on any other quantity. Dependent variables, in turn, are seen as functions of independent variables. For example, in one study, the researcher might try to find a rule that explains the height of children a...
Inspecting how values have been coded is one of my routine checks for categorical variables. I usually just run a quick FREQUENCIES command which tells me basically all I need to know.*Show values and value labels / variable names and labels in tables.set tnumbers both tvars both.*Create ...
There are other ways of classifying variables that are common in statistics. One is qualitative vs. quantitative. Qualitative variables are descriptive/categorical. Many statistics, such as mean and standard deviation, do not make sense to compute with qualitative variables. Quantitative variables have ...
variance of the population (year 2000). They would like to use the line in 2000 as the standard to compare the current line to see if their mpg is improving and they are making progress to meeting government regulations. What are the independent and dependent variables and how a...
Variables:Variables are anything that has an amount or characteristic that varies. In research, these variables can be independent, dependent, confounding, extraneous, and moderated.Answer and Explanation: Confounding variables are outside interference that affect both the independent and dependent variable...
In statistics, most of the data you analyze are random variables, which are functions describing all values that occur during a series of random events or experiments. They can represent categorical, discrete, and continuous data. Examples include the following: ...
Dichotomous Variables are both Categorical and MetricChoosing the right data analysis techniques becomes much easier if we're aware of the measurement levels of the variables involved. The usual classification involves categorical (nominal, ordinal) and metric (interval, ratio) variables. Dichotomous ...
In this article, two new approaches to the analysis of mediation are proposed. Both of these approaches focus on the analysis of categorical variables. The first involves mediation analysis at the level of configurations instead of variables. Thus, mediation can be incorporated into the arsenal of...
Recurrent neural networks are the mathematical engines to parse language patterns and sequenced data. Deep learning (DL) recommender models build upon existing techniques such as factorization to model the interactions between variables and embeddings to handle categorical variables. An embedding is a lear...