When writing about the dummy variables, you will want to make clear what type of coding system was used e. The simplest form of interaction to interpret is the interaction of two dichotomous variables.

What can we say about this? The important point here is that how you code your variables affects how you interpret their coefficients in the output. In the analysis part of the results section, you will want to describe your specific hypothesis, the statistical technique that you will be using, and the model e.

Frequency distributions can be depicted in two ways, as a table or as a graph. One of the most common ways to describe a single variable is with a frequency distribution. To compute the mean all you do is add up all the values and divide by the number of values.

What could be difficult about interpreting this? The single number describes a large number of discrete events. Also, some statistical software packages are better than others for creating the graphs of interactions, so you may need to switch packages to make the graph.

Range, quartilesabsolute deviation, and variance are all examples of writing about descriptive statistics calculator of variability. Or we may measure a large number of people on any measure. This means that positive effects are greater than one and negative effects are between zero and one.

If you are running a logistic regression model, an ordered logit model, a multinomial logit model, a poisson model or a negative binomial model, I strongly suggest that you borrow or buy a copy of this book and read up on the particular type of model that you are running. Dispersion refers to the spread of the values around the central tendency.

For instance, in a bimodal distribution there are two values that occur most frequently. The best way to write a clear, concise results section is to thoroughly understand the statistical techniques that you used to analyze your data. There are two common measures of dispersion, the range and the standard deviation.

In this case, we group the raw scores into categories according to ranges of values. After that, we will look at some examples of some common pitfalls encountered when writing up the results of seemingly simple analyses.

In a research study we may have lots of measures. Another good strategy is to look at articles in your field that report similar analyses for ideas about the exact terminology to use.

We know from above that the mean is Logistic regression If you have conducted a logistic regression, you can describe your results in several different ways. The situation becomes even more complex if you have more than one interaction in the model or three-way or higher interactions.

Which metric you choose is a matter of personal preference and convention in your field. Measures of variability, or the measures of spread, aid in analyzing how spread-out the distribution is for a set of data. When you have a continuous by continuous interaction, the graph is three dimensional, and you are looking at the warping of a plane.

The simplest distribution would list every value of a variable and the number of persons who had each value. You will want to indicate how the missing data were handled e. For example, consider the test score values: This nonlinearity means that you will have to be very precise about the values at which the other variables in the model are held.

Interaction terms Many researchers have difficulty interpreting and understanding the meaning of interaction terms in statistical models, so this is often one of the most challenging parts of the results section to write. Measures of Descriptive Statistics All descriptive statistics are either measures of central tendency or measures of variability.

The coefficient for the variable female is the expected change in the outcome when the variable read is held at 0.Reporting Statistics in APA Format PSYC â€”Burnham Reporting Results of Descriptive and Inferential Statistics in APA Format The Results section of an empirical manuscript (APA or non-APA format) are used to report the quantitative.

Descriptive Statistics Practice Exercises. Work these exercises without using a computer.

Do use your calculator. At the end of the document you fill find the answers. Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures.

Online Statistics Calculators - Solvers Use this calculator if you want to compute the main descriptive statistics of a given dataset: Type the sample (comma or space separated) Name of the variable (Optional). Get the free "Descriptive Statistics Calculator" widget for your website, blog, Wordpress, Blogger, or iGoogle.

Find more Widget Gallery widgets in Wolfram|Alpha.

More About Descriptive Statistics. Descriptive Statistics corresponds to measures and charts that are derived from sample and are intended to provide information about the population being studied. Two basic types of descriptive statistics are the measures of central tendency and the measures of dispersion.

The measures of central tendency .

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