Quantitative Research MethodsProject 3

Group 4AValerie BryanEmily LeakLori Moore

UWG

Fall

2011

Research Questions & Hypotheses

0What relationship exists between surveyed students’ self-reported rating for self-confidence and the students’ GPA? There is no significant correlation between surveyed students’

self-reported rating for self-confidence and the students’ GPA.

0 What relationship exists between surveyed students’ self reported rating for an understanding of others and the students’ GPA? There is no significant correlation between surveyed students’

self reported rating for an understanding of others and the students’ GPA.

0What relationship exists between surveyed students’ self reported rating for cooperativeness and the students’ GPA? There is no significant correlation between surveyed students’

self reported rating for cooperativeness and the students’ GPA.

Descriptive Statistics

 Under-

graduate GPA

Self Rating: Cooperativeness

Self Rating: Understanding

of others

Self Rating: Overall Self-Confidence

N

Valid 40186 39630 39598 39573

Missing 390 946 978 1003Mean 4.47 3.93 3.94 7.4526Median 5.00 4.00 4.00 8.0000Mode 5 4 4 8.00Std. Deviation 1.011 .738 .738 1.50216Skewness -.459 -.284 -.266 -.177Std. Error of Skewness .012 .012 .012 .012Kurtosis -.008 -.088 -.134 -.070Std. Error of Kurtosis .024 .025 .025 .025Range 5 4 4 8.00Minimum 1 1 1 2.00Maximum 6 5 5 10.00

Inferential StatisticsCoefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) 4.148 .036

 114.74

6.000

Self Rating: Overall Self-Confidence

.058 .004 .087 16.236 .000

Self Rating: Understanding of others

-.017 .008 -.012 -2.195 .028

Self Rating: Cooperativeness -.011 .008 -.008 -1.479 .139

a. Dependent Variable: Undergraduate GPA 

Regression Analysis

ANOVA

Results0 Multiple linear regression analysis was computed for students’

undergraduate GPAs based on self-ratings for self-confidence, understanding of others and cooperativeness.  This analysis did not produce a significant regression equation (R2 < 0.01).  However, it revealed a statistically significant variance explained by self-confidence levels (B = 0.09), with no significant variances explained by understanding of others or cooperativeness.

0 The data was further analyzed by computing a one-way ANOVA comparing college students’ undergraduate GPA by self-rated reports of self-confidence levels.  A significant difference was found for different levels of self-confidence ratings (F(8, 39379) = 67.54, p < 0.01).  Tukey’s HSD was used to determine the nature of the differences for students’ reporting different levels of self-confidence.  The analysis revealed that students reporting the highest level of self-confidence had significantly higher GPAs (M = 4.49, SD = .97) than students reporting the lowest level of self-confidence (M = 3.79, SD = 1.40).

FindingsBased on the results of statistical analysis… 0we accept the following hypotheses:

There is no significant correlation between surveyed students’ self reported rating for an understanding of others and the students’ GPA.

There is no significant correlation between surveyed students’ self reported rating for cooperativeness and the students’ GPA.

0we reject the following null hypotheses: There is no significant correlation between surveyed students’

self-reported rating for self-confidence and the students’ GPA.

0and for this case we accept the alternative hypothesis: There is a significant correlation between surveyed students’

self-reported rating for self-confidence and the students’ GPA.

Implications and Recommendations

0These results suggest that colleges should accept applicants exhibiting higher levels of self-confidence if it is the school’s goal to enroll students that are likely to be strong academic performers.

0Further research may be conducted to explore the effect on students’ GPAs resulting from introducing self-confidence boosting programs.