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Add a table of the raw data in the appendix. Include a table with the appropriate descriptive statistics e.g. the mean, mode, median, and standard deviation. Identify the level or data. Include a graph.
Descriptive Results Include a table with the appropriate descriptive statistics e.g. the mean, mode, median, and standard deviation. The descriptive statistic should be relevant to the aim of study. It should not be included for the sake of it. If you are not going to use the mode anywhere, don't include it.
Descriptive statistics are used to describe or summarize data in ways that are meaningful and useful. For example, it would not be useful to know that all the participants in our example wore blue shoes. Central tendency describes the central point in a data set. Variability describes the spread of the data.
Descriptive statistics are broken down into measures of central tendency and measures of variability (spread). Measures of central tendency include the mean, median, and mode, while measures of variability include the standard deviation, variance, the minimum and maximum variables, and the Kurtis and skewness.
Descriptive statistics involves summarizing and organizing the data, so they can be easily understood. Descriptive statistics, unlike inferential statistics, seeks to describe the data, but do not attempt to make inferences from the sample to the whole population. Here, we typically describe the data in a sample.
Descriptive statistics are specific methods basically used to calculate, describe, and summarize collected research data in a logical, meaningful, and efficient way. Descriptive statistics are reported numerically in the manuscript text and/or in its tables, or graphically in its figures.
Step 1: Type your data into Excel, in a single column. For example, if you have ten items in your data set, type them into cells A1 through A10. Step 2: Click the Data tab and then click Data Analysis in the Analysis group. Step 3: Highlight Descriptive Statistics in the pop-up Data Analysis window.
Descriptive Data Analysis. Descriptive techniques often include constructing tables of means and quantiles, measures of dispersion such as variance or standard deviation, and cross-tabulations or “cross tabs” that can be used to examine many disparate hypotheses.

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