# Descriptive Statistics

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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: A Simple Scatter Plot plots one variable against another.

A Matrix Scatter Plot plots all possible combinations of two or more numeric variables against each other A Simple Dot Plot plots one categorical or one continuous variable. An Overlay Scatterplot plots two or more pairs of variables. 3D Scatterplots are 3-Dimensional plots of three numeric variables.

Pie chart: SPSS gives you a lot of options for creating pie charts. This includes the ability to split variables into rows and columns and choose labels. Box plot: shows the spread and centers of a data set. SPSS allows you to create two types of boxplots: simple and clustered Histograms: useful tool for graphically displaying a set of data. The easiest way to make an SPSS histogram is by using the legacy graph option Crosstabs: used to examine relationship between two variable Microsoft Excel:

Box and Whiskers Chart

Bar Graph

Histogram

Scatter Plot

Frequency Distribution Table

Pie Chart

Minitab:

Boxplot

Histogram

Bar Graph