Descriptive statistical analysis method is a method of application classification, tabulation, graphical data and indicators to summarize the general distribution of books, and inferential statistical analysis method is through the application of statistical random sampling method, the sample data obtained conclusions to data analysis overall.
Statistically, it is necessary to summarize the information contained in the sample data, integration and abstraction, resulting in composite indicator reflects the sample data. These indicators called statistics. Feature amount data describing statistics can be divided into two categories: one represents the center position data, such as mean, median, and other public; represents another degree of dispersion of data, such as variance, standard deviation, range, etc. with to measure the extent of individual off-center.
For a given class, the number of cases falling within such frequency is referred to, falling within mainly by the frequency distribution table, bar charts, pie charts, and histograms in the class and the ratio of the number of cases integrated number of cases referred to the relative frequency analysis Fig.
In frequency analysis, pie and bar charts generally apply to lower the number of categories of categorical variables, the number of categories if more, such as more than 10 categories, recommended to choose the histogram.
The central tendency of a set of data refers to the tendency to move closer to a center value. In statistics, the statistics description data distribution center position is referred to as counter statistics.
Indicators for continuous variables and ordinal variable describing data center trends are the mean, median, mode, five percent at the end homogeneous, for qualitative variables indicators of trends in the data center is only a mode description.
The observed values in ascending order, the mean portion excluding both ends of the numerical sequence data obtained after sorting out, called trimmed mean.
The smaller impact of median affected by extreme values, the data has a maximum or minimum value, the mean and median are often more representative of the central tendency of the data.
The mode is the most frequently observed value of the value appears, this reaction the central tendency of the set of observations.
The mode is qualitative data, the central area is only used temporary, but the mode can be used for system data.
Standard deviation is a measure of the observed value deviates from the average size, corresponding to an average deviation may be directly described in the data of degree of deviation from the mean. For homogeneous data, a large standard deviation, values representative of the difference between the average of the majority of the large difference between the observed values greater, a smaller standard deviation, representing these values closer to the mean value, little difference between the observed values.
To measure the mean standard error of the mean differences between different samples, if the difference between two sample means and standard error ratio is less than - two or more than two, there can be concluded that the two means significant difference, and thus concluded that two samples from two different overall.
The biasing of the variable value is used to describe the distribution oblique direction, measuring the distribution of symmetric or not, and the degree of asymmetry of the distribution direction.
It can be descriptive statistical analysis spss many menus, provide descriptive statistical indicators of output. In the independent sample T-test, ANOVA, factor analysis, and many other analysis, spss custom table module can also generate most of the descriptive statistical indicators.