In statistical analysis, tables are very important in terms of coming up with a conclusion and summarizing a certain set of data.
Descriptive Table
Descriptive are used to summarize your data. If your data is numerical, it generally measures the distribution, central tendency, and dispersion of a data set. Generally, these include mean, median, sample size, standard deviation, standard error, minimum, lower quartile (Q1), upper quartile (Q3), and the maximum.
If you data is more qualitative, you can summarize the counts in each category. For example, the table below shows Apple company’s survey results about the iMac users.
Contingency Table
Contingency table, also known as cross-tabulation, is a table that displays frequency distribution of categorical variable(s). It is useful examining relationships between two categorical variables. In addition, it provides a basic picture of the relationship between two variables and can find interactions between them. With contingency tables, one can use a Chi-Square test to test for association between the two categorical variables.
ANOVA Table
ANOVA tables are used to compare means from at least three or more groups from one variable. It shows the F-statistics, the ratio of the variance calculated among the means to the variances within the samples, sum of squares, degrees of freedom, and mean square.
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