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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,
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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 the “Bar Chart” Option Select “Legacy Dialogs”
Select the “Simple” option Click “Define”
Select a variable from the list.
Your selected variable appears here Click OK and…
Testing Relationships What analysis would you use to find out if two variables are related? graph Well Doc, that would depend on the level of measurement of your variables!
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? NO Nominal YES NO Are there equal intervals? Ordinal YES NO Is there a true zero? Interval YES Ratio Process for determining level of measurement Adapted from: Walker, J. (1999). Statistics in Criminal Justice. Gaithersburg, Maryland: Aspen.
Testing Relationships graph What if we wanted to examine the relationship between gender and tobacco use ? Let’s run a simple crosstabs to answer that question!
Select “Analyze” from the Menu Select “Descriptive Statistics” Select the “Crosstabs” Option
Your Variables will Appear Here Select the Variables you want to Examine Click “OK”
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 graph What if we wanted to know if gender is related to binge drinking? Let’s run a simple bivariate correlation to answer that question!
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 “Bivariate” option Select the “Correlate” option
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 This is Heavy! Great Scott! Statistics are powerful!