Predictive Analytics Software: What Statistics Can Do for You Brett Deneckere Dr. Kimberly Dodson April 26, 2011 A “Living Legend” Production.

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Predictive Analytics Software: What Statistics Can Do for You Brett Deneckere Dr. Kimberly Dodson April 26, 2011 A “Living Legend” Production

Why Do We Use Statistics In Research? To understand the professional literature, To understand the rational underlying research in the behavioral sciences, and To conduct behavioral science research: – Explaining, predicting, and controlling social behavior. – Tentative conclusions about the existence and strength of social relationships.

What Are Statistics? The recording, organizing, analyzing, and reporting of quantitative information; A collection of numerical data that measure something; and Numerical tools used by researchers to help them describe and explain phenomena.

Descriptive Statistics Descriptive statistics show the relationship between variables. They are used to describe and summarize a particular data set.

Creating a Bar Graph How do you create a graph? graph Well Doc, it’s actually not that hard. Let me show you!

Select “Graphs” from the Menu Select “Legacy Dialogs” Select the “Bar Chart” Option

Select the “Simple” option Click “Define”

Select a variable from the list.

Your selected variable appears here Click OK and…

SHAZAM! Bar Graph

Testing Relationships Well Doc, that would depend on the level of measurement of your variables! What analysis would you use to find out if two variables are related? graph

Variables Variable type is important to determine the level of measurement and the techniques available to analyze data. – Continuous Can assume an infinite number of values – Examples: time, age, length – Discrete Can assume only a finite number of whole unit values – Examples: sex, political affiliation, number of children in a family

Levels Of Measurement Nominal – Variables can be placed in mutually exclusive, exhaustive categories, but can’t be ordered any further. Languages: English, Spanish, Chinese, Klingon Ordinal – Variables can be categorized as well as ranked according to the degree to which a certain attribute is present I love my mother: Strongly Agree, Agree, Neutral, Disagree, Strongly Disagree

Levels Of Measurement Interval – A scale with an arbitrary zero point, but equal distance (intervals) between any two adjacent units. Temperature in Celsius: 1°-100° Ratio – Contains all the properties of the first three levels, but with an inclusion of an absolute zero point. How much money is in your pocket: $4, $12, $20, $7,596

Can the data be ordered ? Is there a true zero? Ratio Are there equal intervals? Interval Ordinal Nominal YES NO Process for determining level of measurement Adapted from: Walker, J. (1999). Statistics in Criminal Justice. Gaithersburg, Maryland: Aspen.

Testing Relationships Let’s run a simple crosstabs to answer that question! graph What if we wanted to examine the relationship between gender and tobacco use ?

Select “Analyze” from the Menu Select “Descriptive Statistics” Select the “Crosstabs” Option

Select the Variables you want to Examine Your Variables will Appear Here Click “OK”

Hit “Continue” and…

Boom Boom Pow! A Crosstabulation

Crosstabs Results The results indicate that males (54%) are more likely than females (32%) to use tobacco. Cramer’s V tells us the strength and direction of the relationship between two nominal level variables. There is a weak positive relationship between gender and tobacco use with males reporting more use than females.

Testing Relationships Let’s run a simple bivariate correlation to answer that question! graph What if we wanted to know if gender is related to binge drinking?

Bivariate Correlation Bivariate correlation is a statistical technique that gives us the strength and direction of a relationship between two variables.

Select “Analyze” from the menu Select the “Correlate” option Select the “Bivariate” option

Select your variables

Both of your variables will appear here Click “OK” and…

WHOOPAH! A Bivariate Correlation Chart

Bivariate Correlation Results There is a weak positive relationship between gender and binge drinking (r =.26, p =.01). In other words, males are more likely to binge drink than females.

Conclusions Statistics are powerful! Great Scott! This is Heavy!