Examples of Presentations

The following are examples of presentations of regression tables and their interpretations.

These interpretations target a “nonacademic” audience, and would be appropriate for presenting information to those not familiar with statistics.

These examples assume presenters have time constraints, and audiences have limited knowledge about regression analysis. The interpretations are succinct and simplified.

Please note. Slides are to be used only as simplified examples of how regression can be used and interpreted. They are not research presentations.

Example OneHypothesis: Regression

How people feel about women becoming CEOs is impacted by the extent to which they were nontraditional in their political and gender role views.

Example OneMeasurement of Indicators

Attitudes toward female CEOs was measured by using a statement to which respondents indicated their level of agreement.

Gender role ideology was measured by asking respondents to (1) rank their political views from very conservative to very liberal, (2) indicate the extent to which they were independent from their parents, and (3) compare the value of career relative to family.

Regression: Support Women as CEOs by Political Views, Independence from Family, and Valuing Job Over their Family____________________________________________________________Independent Parameter StandardizedVariable Estimate EstimatePolitical view .73** .31**

Independence .63* .24*

Job Over Family .24** .25**

Intercept .00 7.31

F statistic 10.42***R square 0.25Adjusted R square 0.22______________________________________________________________ *p<.01 **p<.05***p<.001______________________________________________________________

FINDINGS: Regression

Respondents who were (1) more liberal in their political views, (2) more likely to view themselves as independent thinkers, and (3) put a greater emphasis on work relative to family were more likely to believe women should seek CEO positions. .

The R-square was .24 indicating a moderately strong relationship between the independent variables and the dependent variable. Political views had the biggest impact on the attitude toward women as CEOs (with a standardized estimate of .31).

Attitudes Toward The Death Attitudes Toward The Death PenaltyPenalty

Presentation: Tandi McBridePresentation: Tandi McBride

Modifications: Carol AlbrechtModifications: Carol Albrecht

Example TwoExample TwoHypothesis: RegressionHypothesis: Regression

The more traditional a student’s views, the The more traditional a student’s views, the greater their support for the death penalty.greater their support for the death penalty.

Views on the perceived fairness of the Views on the perceived fairness of the current legal system, religious attendance, current legal system, religious attendance, and political ideology are related to the and political ideology are related to the extent to which respondents support the extent to which respondents support the death penalty.death penalty.

Example TwoExample TwoMeasurement of IndicatorsMeasurement of Indicators

Students were asked to indicate the extent to which they Students were asked to indicate the extent to which they agreed with the death penalty.agreed with the death penalty.

Students were asked to indicate the extent to which they Students were asked to indicate the extent to which they agreed the current legal system is fair.agreed the current legal system is fair.

Students were asked to indicate the number of times per Students were asked to indicate the number of times per year they attended a religious service.year they attended a religious service.

Students were asked to rank their political views from very Students were asked to rank their political views from very conservative to very liberal.conservative to very liberal.

FindingsFindingsRegression TableRegression Table

Table 5Table 5 Regression: Support for the Death Penalty by Religious Attendance, Political Regression: Support for the Death Penalty by Religious Attendance, Political Ideology, and Support for the Current Legal System.Ideology, and Support for the Current Legal System.

______________________________________________________________________________________________________________________________________ Independent Variables Parameter Estimate Standardized EstimateIndependent Variables Parameter Estimate Standardized Estimate ________________________________________________________________________________________________________________________________________ Religious Attendance Religious Attendance .01* .20*.01* .20*

Political ViewsPolitical Views - .19 - .11 - .19 - .11

Perceive Legal System as Fair .47*** .45***Perceive Legal System as Fair .47*** .45*** Intercept Intercept 0.000.00 5.36 5.36

F statistic 14.14***F statistic 14.14*** R square .27R square .27 Adjusted R square .25Adjusted R square .25 *p<.05*p<.05***p<.001***p<.001

ConclusionsConclusions

As reported in Table 5, there is a significant relationship between the As reported in Table 5, there is a significant relationship between the independent variables and the dependent variable – attitudes toward independent variables and the dependent variable – attitudes toward the death penalty. the death penalty.

Religious attendance was positively and significantly related to Religious attendance was positively and significantly related to attitudes toward the death penalty although the relationship was not attitudes toward the death penalty although the relationship was not strong. Political ideology was not significantly related to death penalty strong. Political ideology was not significantly related to death penalty when controlling for religious attendance and attitudes toward the when controlling for religious attendance and attitudes toward the current legal system. Perception that the current legal system is fair current legal system. Perception that the current legal system is fair was strongly and positively related to attitudes toward the death was strongly and positively related to attitudes toward the death penalty. penalty.

Attitudes on President Attitudes on President Bush and the War in IraqBush and the War in Iraq

Constructed by Leesa PettusConstructed by Leesa Pettus

Modified by Dr. Carol AlbrechtModified by Dr. Carol Albrecht

Example ThreeExample ThreeHypothesis: RegressionHypothesis: Regression

Political ideology, gender, and Political ideology, gender, and religious attendance have an effect religious attendance have an effect on attitudes toward US involvement on attitudes toward US involvement in war.in war.

Regression TableRegression TableTable 2 Pro-War Attitudes by Political Affiliation, Table 2 Pro-War Attitudes by Political Affiliation,

Gender and ReligiosityGender and Religiosity

Independent VariablesIndependent Variables Standardized Estimate Parameter Standardized Estimate Parameter EstimateEstimate

Political AffiliationPolitical Affiliation -0.76-0.76****** --1.511.51******

GenderGender -0.07-0.07 -0.47-0.47

ReligiosityReligiosity 0.01 0.01 0.00 0.00

InterceptIntercept 0.00 0.00 16.22 16.22

F StatisticF Statistic 47.9247.92****** R SquareR Square 0.600.60 Adjusted R SquareAdjusted R Square 0.590.59 ***p<.0001***p<.0001

Regression AnalysisRegression Analysis Political affiliation was my only significant independent variable and Political affiliation was my only significant independent variable and

has a probability <.0001 suggesting a strong relationship between has a probability <.0001 suggesting a strong relationship between this variable and attitudes toward war.this variable and attitudes toward war.

My F statistic is also significant with a probability <.0001 indicating My F statistic is also significant with a probability <.0001 indicating that I can generalize my findings to the population.that I can generalize my findings to the population.

My R2 shows that I can increase my ability to predict the index My R2 shows that I can increase my ability to predict the index score on pro-war by .60 (60%) if I know a person’s religious score on pro-war by .60 (60%) if I know a person’s religious attendance, political affiliation and gender. attendance, political affiliation and gender.

My parameter estimate for political affiliation shows that for every My parameter estimate for political affiliation shows that for every

one point increase on the political affiliation index, there is a 1.5 one point increase on the political affiliation index, there is a 1.5 point decrease on the pro-war index. As individuals become more point decrease on the pro-war index. As individuals become more liberal in their political affiliation, they are less “pro-war”. liberal in their political affiliation, they are less “pro-war”.

Factors Influencing High School Students’ Perception of Current and Future Education.

Constructed by Lorena Garcia

Modified by Dr. Carol Albrecht

Example FourHypothesis: Regression

• Race, predicted grade and perception of relationship with teacher is related to satisfaction with overall academic success.

Example FourMeasurement of Indicators

• Respondents indicated whether or not they were Latino

• Respondents predicted their final grade in the class.

• Respondents reported the level to which they agreed that they had a good relationship with the teacher.

• Respondent reported their level of satisfaction with their

academic success. .

Satisfaction with Academic Performance by Race, Relationship with Teacher and Final Grade

Independent Parameter Standardized Variables Estimate Estimate

Race -0.14 -.04

Teacher Relationships 0.75*** .44***

Final Grade in Class 0.23** .13**

Intercept 3.43 0

F-Statistic 22.29*** R-Square 0.24 Adjusted R 0.23 **p<.001

***p<.0001

In Conclusion…• For my Regression model, I was able to reject the null

hypothesis (with an F value of 22.29 and p<.0001),thus indicating that at least one of my independent variables was related to my dependent variable (satisfaction).

• Race was not related to satisfaction.

• Prediction of final grade and perception of relationship with the teacher were related to satisfaction.

• Students who predicted a higher grade and reported a more positive relationship with their teacher were more likely to report that they were satisfied.

Attitudes Towards the Attitudes Towards the Legalization of Legalization of

MarijuanaMarijuana

Constructed by Chelsea Moore

Modified by Dr. Carol Albrecht

Example FiveExample FiveHypothesis: RegressionHypothesis: Regression

There is a significant relationship between the There is a significant relationship between the index score measuring the degree of support for index score measuring the degree of support for keeping marijuana illegal and at least one of the keeping marijuana illegal and at least one of the following independent variables: student’s following independent variables: student’s political affiliation, the number of times a student political affiliation, the number of times a student skips class per month, and the students’ gender. skips class per month, and the students’ gender.

Example FiveExample FiveMeasurement of IndicatorsMeasurement of Indicators

Respondents were asked to indicate their gender.Respondents were asked to indicate their gender.

Respondents were asked to report the number of times Respondents were asked to report the number of times they skipped class in a “typical” month.they skipped class in a “typical” month.

Respondents were asked to rank their political ideology Respondents were asked to rank their political ideology from very conservative to very liberal.from very conservative to very liberal.

Respondents were asked to indicate the extent to which Respondents were asked to indicate the extent to which they supported laws making possession of marijuana they supported laws making possession of marijuana illegal.illegal.

Regression TableRegression TableTable 2. Regression: Degree of Support for Keeping Marijuana Illegal by Political

Affiliation, the Number of Times a Student Skips Class Per Month, and Gender

Independent Parameter Estimate Standardized Estimate

Political Affiliation 3.10*** 0.42***

Classes Skipped (per month) -0.78* -0.26*

Gender

Intercept

2.63

11.13

0.16

F Statistic

R Square

Adjusted R Square

*p<0.05***p<0.001

14.22***

0.32

0.30

ConclusionsConclusions The R Square is 0.32 indicating a moderate to strong relationship.The R Square is 0.32 indicating a moderate to strong relationship.

The F statistic is 14.22 and the probability is less than 0.001, so The F statistic is 14.22 and the probability is less than 0.001, so we can reject the null hypothesis. At least one of the we can reject the null hypothesis. At least one of the independent variables is related to the dependent variable. independent variables is related to the dependent variable.

When looking at the independent variables individually, we see When looking at the independent variables individually, we see that:that:– Gender is NOT significantly related to marijuana legalization.Gender is NOT significantly related to marijuana legalization.– The more conservative a student’s political ideology, the more The more conservative a student’s political ideology, the more

support for keeping marijuana illegal. Political ideology has support for keeping marijuana illegal. Political ideology has the greatest impact on attitudes toward marijuana. the greatest impact on attitudes toward marijuana.

– The more often students skip class, the less supportive of The more often students skip class, the less supportive of keeping marijuana illegal. keeping marijuana illegal.

For More Information, For More Information, Contact:Contact:

Dr. Carol AlbrechtDr. Carol Albrecht– Utah State Extension Assessment Utah State Extension Assessment

SpecialistSpecialist– (979) 777-2421(979) 777-2421– carol.albrecht@usu.educarol.albrecht@usu.edu