# descriptive statistics

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Descriptive Statistics

Descriptive statistics is the analysis of data that summarize data in a way such that, meaningful patterns emerge from the data. Descriptive statistics do not allow us to reach to the conclusions beyond the data we have analyzed regarding any hypotheses we might have made. They simply describe our data.
Measures of Central Tendency: these are ways of describing the central position of a frequency distribution for a group of data through:
Mode: Sum of all observations divided by the number of observations.
Median: Middle of data. Use with ordinal data or when data contains outliners.
Mean: Most frequent observation. Use with nominal data.

Measures of Spread: these are ways of summarizing a group of data by describing how spread-out the scores are. Statistics available to describe the spreads includes: Range: Difference between the values of the maximum and minimum observation
Quartiles: more useful than range. Often used with median
Absolute deviation: average of distance of an observation of a distribution from its mean Variance: takes deviation from Mean
Standard deviation: positive square root of variance

SPSS Software to Measure of Central Tendencies
IBM SPSS Statistics (formerly known as Statistical Package for the Social Sciences) is a popular program for statistical analysis. The base software includes descriptive statistics, bivariate statistics, prediction for numerical outcomes and identifying groups.
Frequency table: can give you an idea about the spread of your data in a glance. SPSS uses the Frequency command to populate frequency tables
Bar charts: When you create a bar chart in SPSS, the x-axis is a categorical variable and the y-axis represents summary statistics such as means, sums or counts. Bar charts are accessed in SPSS through the Legacy dialogs command
Scatterplot: examine the linear nature of the relationship between two variables. SPSS has several different options for scatter plots:
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