The effects of anxiety and self-efficacy on finance students.

Because of their quantitative content, Finance courses are particularly difficult for business majors. Math-related material causes many students to become anxious, which can impede their learning and their performance. Also, students who think they will perform poorly on a task do worse than those who think they will succeed. The difference is the student's self-efficacy. This exploratory study attempted to examine "Finance anxiety" in business students by creating a Finance Anxiety Scale to measure that phenomenon, as well as its relation to the construct of self-efficacy. The objective of this research was to begin examining whether or not the critical message of finance could be made more accessible to students without diluting the necessarily rigorous nature of the discipline. The results and implications of this preliminary study are discussed, as well as essential future research.

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Even though knowledge of finance is considered critical to success in business, studies indicate that many business students have more difficulty with Finance courses than any other business discipline. Literature suggests that this is primarily due to the quantitative nature of Finance. Quantitative material causes many students to become anxious. Anxiety, in turn, is said to impede performance, causing students to fall behind in class and to postpone initiating remedial action. At the same time, reports show that students who think they can perform well on a particular task do better than those who think they will fail. This paper describes an attempt to measure and assess this Finance-course anxiety. Furthermore, it examines the relationship between Finance anxiety and self-efficacy--an individual's confidence in his or her ability to accomplish a task. Finally, the paper discusses the implications of this exploratory study and suggests necessary future research.

Review of Literature

Financial performance is considered the chief indicator of the success of organizational decisions and activities (Thompson, Strickland, & Gamble, 2006). As a consequence, a weak understanding of finance could have a very detrimental effect on a businessperson's decision making ability and career prospects. Yet according to the Educational Testing Service (2000), seniors at 388 colleges and universities taking the "Major Field Test in Business II" scored lower on the Finance section than for any other discipline--at the 38th percentile. Studies by individual undergraduate business programs have produced similar findings. Literature indicates that most business students find Finance courses to be particularly difficult and challenging (Balachandran & Skully, 2004),and students with weaker quantitative skills delay taking the required math or statistics courses that are typically prerequisites for Finance. This results in less well prepared and poorer performing students (Marcal & Roberts, 2001). Studies attribute this largely to the quantitative nature of a Finance curriculum (Krishnan, Chenchuramarah, Bathala, Khattacharya, & Ritchey, 1999). That is, mathematics anxiety manifests itself in all quantitatively related environments (Baloglu, 2002).

Math anxiety is defined as "any situation in which an individual experiences anxiety when confronted with mathematics in any way" (Byrd, 1982, p. 38). There is also agreement that anxiety is related to performance (Balachandran & Skully, 2004; Tobias & Everson, 1997), and that anxiety has been shown to have a debilitating effect on learning and achievement (Gaudy & Spielberger, 1971; Tobias, 1980). What is more, this phenomenon is wide spread. In a study of the learning and study characteristics of business students, Sizoo, Malhotra, and Bearson (2002) found that of the 10 subscales on the Learning & Study Strategies Inventory (LASSI),respondents uniformly scored lower on the Anxiety subscale. That is, whether they were male or female, American or international, adult or traditional-aged business students, anxiety was their greatest obstacle to learning. Furthermore, the anxiety was primarily math-related anxiety. Research also showed that successful efforts to reduce this anxiety could lead to dramatic improvements in academic success (Bogue, 1993).

According to Baloglu (2002),two major theories address the effects of anxiety: The Cognitive Interference Theory says that high levels of anxiety lead to poor performance (Wine, 1980); while the Deficit Theory assumes the opposite--poor performance leads to increased anxiety (Tobias, 1986). Extensive research by Sciutto (1996) supports the Cognitive Interference Theory, stating that "anxiety causes poor performance and not the contrary" (p. 30). Regardless of the particular theory, it is widely believed that math-related anxiety clearly impedes academic performance (Baloglu, 2002).

Still, some people--when confronted with a quantitative challenge--figure out how to work their way through it, while other people resort to delay and denial (Scott, 2003). Bandura (1986) attributed this behavior to the individual's self-efficacy--the level of confidence individual's have in their ability to accomplish tasks. Those with high self-efficacy tend to persist in exhibiting new behaviors and, therefore, have greater opportunities for receiving feedback about their acquired skills than those with low self-efficacy. Research shows that self-efficacy was found to be significantly related to academic performance in general (Wood & Locke, 1987), and mathematics performance in particular (Campbell & Hackett, 1986).

Still, Finance (like mathematics) is a difficult, challenging course of study. Neither the student nor the discipline would be well served by diluting the course content or by consuming valuable course time with peripheral activities and exercises. At the same time, student-anxiety impairs performance in the Finance classroom, and neither the student nor the discipline is well served if the content cannot be made more accessible.

Research shows that there are strategies available to both enhance self-efficacy (Eisenberger, Conti-D'Antonio, Bertrando, 2000) and to ameliorate math-related anxiety (Tobias, 1995). These strategies may be useful for Finance students, faculty, mentors, and advisors.

To explore this issue more closely, the authors developed a measure of Finance anxiety and correlated its results to those of established self-efficacy measures. The next section of this paper describes that process. The results and implications are discussed later in the paper.

Methodology

To measure Finance anxiety, the authors used Alexander and Martray's (1989) 25-item Revised Mathematics Anxiety Rating Scale (RMARS) as a template. The RMARS has been widely used in academic research, rigorously tested, and found to be psychometrically sound. Also, its construct applies to the Finance discipline and is designed to facilitate remedial action. Self-efficacy was measured by a 17-item general self-efficacy scale (Sherer, Maddux, Mercandante, Prentice-Dunn, Jacobs, &. Rogers, 1982).

Participants of this exploratory study were a "convenience sample" of students easily accessible to the authors. Neither the institutions nor the students were selected randomly. As a consequence, the results cannot be generalized beyond the sample itself. Still, exploratory research is useful in clarifying and defining the nature of a problem or opportunity (Zikmund, 2006). The "Finance Anxiety Questionnaire" was distributed to 510 current or recent Finance students. The questionnaires were passed out toward the end of the semester, but not on the day of an examination (to avoid situational anxiety): 501 usable questionnaires were returned. Respondents were distributed as follows in Table 1:

Analysis and Presentation of Findings Estimates of Reliability

Using the methodology employed by Alexander and Martray (1989) in developing, and Baloglu (2002) in evaluating the Revised Math Anxiety Rating Scale--the template-instrument for this research--the 25-item Finance Anxiety Scale (FAS) was divided into three subscales: Test Anxiety, Numeric Anxiety, and Course Anxiety. To determine whether the 15-items that were summed to create the Test Anxiety score formed a reliable scale, Cronbach's alpha was computed (Table 2). The alpha of the 15-items was .929, which is very high according to Leech, Barrett, and Morgan (2005). While this result indicates the items form a scale of good internal consistency, it also suggests that the items are repetitious or that there are more items in the scale than is really necessary for a reliable measure of the concept. Similarly, the alphas for the 5-item Numeric Task Anxiety scale (.907), and the 5-item Course Anxiety scale (.848) indicate good internal consistency. In addition, the alpha for the total 25-item Finance Anxiety Scale was .934, reflecting good reliability and some repetition in the items. The alpha of the 17-item Self-Efficacy Scale (SES) was .831, reflecting a high level of internal consistency and strongly supporting the reliability of the measure. An analysis of these findings will be discussed later.

Estimates of Validity

Principal axis factor analysis with varimax rotation was conducted to assess the underlying structure for the 25-items of the Finance Anxiety Scale. Three factors were requested based on the fact that the items were designed to index three constructs: Test Anxiety, Numeric Anxiety, and Course Anxiety. After rotation, the first factor accounted for 24.1% of the variance, the second factor accounted for 16.9%, and the third factor accounted for 16.4%, for a total of 57.4%. Table 3 displays the items and factor loadings for the rotated factors, with loadings less that .40 omitted to improve clarity. Ten of the 15 Test Anxiety items loaded strongly on the first factor. All 5 Numeric Anxiety items loaded strongly on the second factor. Three of the 5 Course Anxiety items loaded, albeit not cleanly, on the third factor. Among the Test Anxiety items, questions 14, 20, 21 and 23 loaded more strongly on the Course Anxiety factor (the third factor), while question 12 failed to load significantly on any factor. Among the Course Anxiety items, question 32 and 33 cross-loaded on the Numeric Anxiety factor (second factor). Analysis of these findings will be discussed in the next section.

Correlation Analysis

A correlation analysis was conducted to determine if certain demographic or performance characteristics were significantly related to the measures of Finance anxiety or self-efficacy being used, or whether or not the FAS was significantly related to the SES. Research cited in the Review of Literature suggests that math anxiety and self-efficacy would have a significant inverse relationship. The same could be inferred for the two scales under examination.

Indeed, Table 4 does show the Pearson Correlation Coefficient for the FAS and the SES was a significant, negative relationship: [r.sub.s] (464) = -.2211, p=.000 (2-tailed). But an closer examination in Table 5 shows that the relationships for the Student Subgroups, while negative, was not significant for Undergrads 25 and Over. Since the literature cited above indicates that subgroups of college students have different learning characteristics (Sizoo et al., 2002), and that different remedies are designed for high math anxiety vs. low self-efficacy, the authors examined this relationship further.

Comparison of Means: Finance Anxiety to Self-Efficacy

Analysis of variance was conducted on each scale for paired subgroups. Table 6a shows that none of the three subgroups had significantly different mean scores when compared to each other. However, Table 6b shows that Undergrads-Under 25 had significantly lower SES means than either Undergrads-25 & Over or Graduate MBA students. The difference for the Over 25 or Grad students was not significant. To examine the FASSES relationship even further, the authors employed the median-split procedure.

Determining "High" vs. "Low" Finance Anxiety and Self-Efficacy

The median-split procedure--widely used in social psychology research to identify how certain groups relate to a particular measure (Harrison, Chadwick, & Scales, 1996)--was employed to ascertain which students would be considered to have a "high" score for FAS or SES, and which would have a "low" score. For this study, students scoring above the median FAS for the total sample (2.84) were considered to have "high finance anxiety." Those scoring below the median, "low finance anxiety." Table 7a reveals that the Undergrad-Under 25 students leaned toward "high" anxiety--52.5% vs. 47.5%. Undergrads 25 & Over had FAS scores that also leaned toward "high" finance anxiety (51.7% above the median and 48.3 % below), while Grad students leaned toward "low" anxiety (46.7% above and 53.3% below).

For the SES (Table 7b), the median split of 4.71 for the total sample had Under-25 students scoring low (46.2% with "high" score vs. 53.8% with "low" scores), compared to 25 & Over students (67.4% "high" and 32.6% "low"), and Grad students (75% "high" and 25% "low"). This suggests that for this sample, self-efficacy is a very significant issue for the Under-25 subgroup

Discussion

The results of any exploratory study have to be interpreted with caution. The institutions and individuals participating in this study were selected purely for their availability. As a consequence, the results for this convenience sample cannot be generalized to any larger population. Still, even with its limitations, exploratory research can be useful in defining and clarifying the nature of a problem or opportunity. This study indicates that the Finance Anxiety Scale--using the Revised Mathematics Anxiety Rating Scale as a template--provides a useful measure of anxiety toward the study of Finance. Measures of internal consistency were strong and estimates of validity were satisfactory. Still, the results also suggest that the scale might be improved by simply eliminating some of its weaker items.

Future Research 1: collect a larger, random sample

A larger, random sample will allow researchers to perform more rigorous analysis of the data. It would also allow analysts to examine the psychometrics of a more parsimonious scale. Recall from Table 3 that of the 15 items on the Test Anxiety subscale, two loaded more strongly on Numeric Anxiety. While questions 12 ("Taking the math section of a college entrance exam") did not load significantly on any factor. These items will be among the likely candidates for elimination.

Recall also from Table 4 that estimates of reliability suggested that items were repetitious or that there were more items in the scale than is really necessary for a reliable measure of the concept. Interestingly, question 12, which did not load on any factor, also had relatively low "Correct Item-Total Correlation" results in reliability analysis, and the alphas increased if the item was deleted from their respective scales. This supports the suggestion that careful deleting of individual items will improve the scale as a whole.

For the sample as a whole, there was strong support for the proposition that FAS and SES would be negatively correlated (Table 5). But for the student subgroups, significance was only reported for the Undergrads, under-25 and the Graduate students. This led to a closer examination of the FAS-SES relationship using ANOVA and median-split analysis (Tables 6 and 7 respectively). It appears that for the Undergrad, under-25 subgroup, feelings of low self-efficacy could be more of an impediment to success in a Finance classroom than feelings of high Finance anxiety. For the Undergrad, 25 & over group, it tended to be the other way around. Faculty familiar with these adult learners confirm that, in general, they have returned to the college with rusty quantitative skills and the attendant math anxiety. On the other hand, they have learned over time (average age = 36) that they can get through challenging situations, hence the high self-efficacy score. These results indicate that any remedies for low self-efficacy, or high Finance anxiety will have to be tailored to the particular student group, if not the individual student.

Future Research 2: Conduct separate experiments to test strategies to remedy high Finance anxiety or low self-efficacy.

The review of literature indicated that there were strategies to enhance low self-efficacy and ameliorate high math anxiety. Obviously, the math anxiety strategies have to be examined for their appropriateness to the Finance classroom. In time, separate pretest post-test experiments could be conducted. One experiment would include a control group experiencing no intervention, and a treatment group experiencing interventions aimed at reducing Finance anxiety. The other experiment's treatment group would include interventions that enhance self-efficacy. Finally, an experiment could include both finance anxiety and self-efficacy interventions. Needless to say, identifying the most effective remedies for each construct could be a very long process. Nevertheless, given the importance of the Finance discipline to businesspeople (in both for-profit and not-for-profit organizations), it seems worthy of examination.

Summary

Business students have considerable difficulty with Finance and literature suggests that it is largely because of the quantitative nature of the discipline. This exploratory study examined this phenomenon of Finance anxiety. A Finance Anxiety Questionnaire was developed which included measures for both Finance Anxiety and Self-Efficacy. Initial results of this limited study indicate that further research in this area is worthwhile. The objective of this research would not be to dilute the Finance discipline in any way, but to make its critical message somehow more accessible to its students.

References

Alexander, L., & Martray, C. (1989). The development of an abbreviated version of the Mathematics Anxiety Rating Scale. Measurement and Evaluation in Counseling and Development, 22, 143-150.

Balachandran, B., & Skully, M. (2004, Spring). Student perceptions of introductory business finance accounting and finance versus other business majors. Advances in Financial Education, 2, 22-33.

Baloglu, M. (2002). Construct and concurrent validity and internal consistency, split-half, and parallel-model reliability of the revised mathematics anxiety rating scale. Unpublished doctoral dissertation, Texas A&M University-Commerce. Texas, College Station, TX.

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, N J: Prentice-Hall, Inc.

Bogue, C.(1993).Studying in the content areas: social science. Clearwater, FL:H & H Publishing.

Byrd, P. (1982). A descriptive study of mathematics anxiety: Its nature and antecedents. Unpublished doctoral dissertation. Indiana University, Bloomington, IN.

Campbell, N. K., and Hackett, G. (1986). The effects of mathematics task performance on math self-efficacy and task interest. Journal of Vocational Behavior, 28, 149-162.

Educational Testing Service. (2000). Major Field Tests: Comparative Data Guide. Princeton, NJ: ETS.

Eisenberger, J., Conti-D'Antonio, & Bertrando, R. (2000). Self efficacy: Raising the bar for students with learning needs. Larchmont, NY: Eye on Education.

Gaudry, E. & Spielberger, C. D. (1971). Anxiety and educational achievement. New York: Wiley.

Harrison, J. K., Chadwick, M., & Scales, M. (1996). The relationship between cross-culture adjustment and the personality variables of self-efficacy and self-monitoring. International Journal of Intercultural Relations, 20(2), 167-188.

Krishnan, V.S., Chenchuramarah, T., Bathala, T. K., Bhattacharya, & Ritchey, R. (1999, Spring/ Summer). Teaching in the introductory finance course: What can we learn from student perceptions and expectations. Financial Practice and Education, 9(1), 70-82.

Leech, N. L., Barrett, K. C., & Morgan, G. A. (2005). SPSS for Intermediate Statistics: Use and Interpretation (2nd Edition). Mahwah, N J: Lawrence Erlbaum Associates.

Marcal, L., & Roberts, W. R. (2001, Fall). Business statistics requirements and student performance in financial management. Journal of Financial Education 27, 12-28.

Sciutto, M. J. (1996). Effects of behavioral instructions on affective outcomes in introductory statistics courses. Unpublished doctoral dissertation. Hofstra University, New York, NY.

Scott, R. V. (2003). Perceived self-efficacy versus anxiety as a predictor of performance in statistics classes. Unpublished doctorial dissertation. Boston University.

Sherer, M., Maddux, J. E., Mercandante, B., Prentice-Dunn, S., Jacobs, B., &. Rogers, R. W. (1982). The self-efficacy scale: Construction and validation. Psychological Reports, 51, 663-671.

Sizoo, S. L., Malhotra, N. K., & Bearson, J. M. (2002). Learning characteristics of adult vs. traditional-aged business students. International Journal of Business Disciplines, 12(1), 21-27.

Thompson, Jr. A.A., Strickland III, A. J., & Gamble, J. E. (2006). Crafting and Executing Strategy: Quest for Competitive Advantage (14th ed.). New York: McGraw-Hill Irwin.

Tobias, S. (1980). Math anxiety: What can you do about it. Today's Education, 69, 26-29.

Tobias, S. (1986). Anxiety and cognitive processing of instructions. In R. Schwarzer (Ed.), Self-related cognitions in anxiety and motivation. Hillsdale, N J: Erlbaum Associates.

Tobias, S. (1995). Overcoming math anxiety. New York: W. W. Norton & Company.

Tobias, S.,& Everson, H.T. (1997). Studying relationship between affective and metacognitive variables. Anxiety, Stress, and Coping, 10, 59-81.

Wine, J. (1980). Cognitive-attentional theory of text anxiety. In I.G. Sarason (Ed.), Test anxiety: Theory, research, and applications. (pp. 349-385). Hillsdale, N J: Erlbaum Associates.

Wood, R. E., & Locke, E.A. (1987). The relation of self-efficacy and grade goals to academic performance. Educational and Psychological Measurement, 47.1013-1024.

Zikmund, W. G. (2006). Exploring Marketing Research (9th ed.). Fort Worth, TX: Dryden Press.

Steve Sizoo, Associate Professor, Comparative Cultures Collegium. Robert Jozkowski, Assistant Professor, Eckerd College. Naveen Malhotra, Professor, Eckerd College. Morris Shapero, Assistant Professor, Eckerd College.

Correspondence concerning this article should be addressed to Steve Sizoo at [e-mail].

Table 1
Sample Participants

                               Gender
Student Subgroups          Male    Female   Total

Undergraduate, under 25      220      142     362
Undergraduate, 25 over        35       52      87
Graduate student (MBA)        34       18      52
Total                        289      212     501

Table 2
Estimates of Reliability

                                Cronbach's
Scale/Subscales         Items   Alpha

Finance Anxiety         25             934
 Test Anxiety           15            .929
Numeric 'Task Anxiety                0.907
Course Anxiety                       0.848
Self-Efficacy           17           0.83

Table 3
Factor Loadings for the Rotated Factors

Question
Number     Item                           Factor Loading

           Thinking about an upcoming
             Finance test day before        0.832
           Thinking about an upcoming
             Finance test hour before         809
           Taking an exam (final)
             of a Finance course            0.795
           Study for Finance test             749
           Taking quiz in
             Finance course                   706
           Given a "pop" quiz               0 636
           Receiving your
             final Finance grade            0.618
           Thinking about Finance
             test one week before           0 612
           Difficult homework problems        584
           Study for Finance test             560
           Problem involving
             multiplication                           0 929
           Problems involving
             subtraction                              0 912
           Problems involving division                  862
           Problems moving addition                     763
           Reading a cash
             register receipt                         0.504
           Signing up Finance course                  0 420
           Picking up textbook
             to begin difficult
             assignment
           Listening to another
             student explaining
             a formula
           Teacher working
             equation blackboard                        442
           Picking up Finance
             book for homework              0 400
           Walking into Finance course
           Opening textbook to
             begin difficult problems         516
           Realize must take
             Finance classes                  501
           Buying a finance textbook
           Eigenvalues                      5.708     4.725
           % of variance                   24.133    16.838

Question                                  Factor
Number     Item                           Loading   Communality

           Thinking about an upcoming
             Finance test day before                  0.745
           Thinking about an upcoming
             Finance test hour before                 0.690
           Taking an exam (final)
             of a Finance course                      0.639
           Study for Finance test                     0.628
           Taking quiz in
             Finance course                             583
           Given a "pop" quiz                         0.498
           Receiving your
             final Finance grade                      0.511
           Thinking about Finance
             test one week before                     0.590
           Difficult homework problems                0.539
           Study for Finance test                     0 617
           Problem involving
             multiplication                           0 913
           Problems involving
             subtraction                              0.868
           Problems involving division                  846
           Problems moving addition                   0.673
           Reading a cash
             register receipt                         0.397
           Signing up Finance course        0 656     0 685
           Picking up textbook
             to begin difficult
             assignment                     0 635     0 627
           Listening to another
             student explaining
             a formula                      0 612     0 612
           Teacher working
             equation blackboard            0 610     0 601
           Picking up Finance
             book for homework              0 602       583
           Walking into Finance course      0 600       544
           Opening textbook to
             begin difficult problems         540     0 646
           Realize must take
             Finance classes                  508     0 613
           Buying a finance textbook        0.457       349
           Eigenvalues                      3.602
           % of variance                   16.397    57.368

Table 4
Variables With At Least One Significant Correlation

                             Test        Numeric
                            Anxiety      Anxiety
Variable                   (Q11-25)     (Q26-30)

Education Class
  Pearson Crrl               -0 043           75
  Sig (2-tail)                0 356          105
Age
  Pearson Crrl                0.210          074
  Sig (2-tail)                0 658          113
Gender
  Peat son Crrk                 235       -0.066
  Sig. (2-tail)               0 000          158
English native language?
  Pearson Crrl               -0.058          297
  Sig (2-tail)                  210          000
Citizen?
  Pearson Crrl               -0.028          193
  Sig (2-tail)                  541          000
Current GPA
  Pearson Crrl               -0.960          234
  Sig (2-tail)                0.038          000
In Finance course now?
  Pearson Crrl                  114       -0.610
  Sig (2-tail)                0 014        0.189
Test Anxiety
  Pearson Crrl                  000          353
  Sig (2-tail)                   --          000
Numeric Anxiety
  Pearson Crrl                  353          000
  Sig. (2-tail)               0 000           --
Course Anxiety
  Pearson Crrl                  508        0.630
  Sig (2-tail)                0 000          000
Finance Anxiety
  Pearson Crrl                0.925#       0.642#
  Sig. (2-tail)               0 000#       0 000#
Self Efficacy
  Pearson Crrl               -0.144#      -0.263#
  Sig. (2-tail)               0.002#       0.000#

                             Course      Finance
                             Anxiety     Anxiety
Variable                    (Q31-35)    (Q11-35)

Education Class
  Pearson Crrl                -0.016          52
  Sig (2-tail)                   730       0.259
Age
  Pearson Crrl                -0.013         006
  Sig (2-tail)                   784         904
Gender
  Peat son Crrk               -0 026         147
  Sig. (2-tail)                  576         001
English native language?
  Pearson Crrl                 0.163       0 068
  Sig (2-tail)                   000         145
Citizen?
  Pearson Crrl                   080         044
  Sig (2-tail)                   085         339
Current GPA
  Pearson Crrl                   207      -0.174
  Sig (2-tail)                   000         000
In Finance course now?
  Pearson Crrl                   019         072
  Sig (2-tail)                   688         119
Test Anxiety
  Pearson Crrl                 0.508         925
  Sig (2-tail)                   000         000
Numeric Anxiety
  Pearson Crrl                   630         642
  Sig. (2-tail)                0 000         000
Course Anxiety
  Pearson Crrl                   000         757
  Sig (2-tail)                    --         000
Finance Anxiety
  Pearson Crrl                 0.757#      1.000#
  Sig. (2-tail)                0 000#         --
Self Efficacy
  Pearson Crrl                -0.230#     -0.221#
  Sig. (2-tail)                0.000#      0.000#

                           Self Eficacy
                               Scale
Variable                     (Q36-52)

Education Class
  Pearson Crrl                   144
  Sig (2-tail)                 0.002
Age
  Pearson Crrl                   172
  Sig (2-tail)                 0 000
Gender
  Peat son Crrk                0 068
  Sig. (2-tail)                  145
English native language?
  Pearson Crrl                -0 090
  Sig (2-tail)                 0.052
Citizen?
  Pearson Crrl                   109
  Sig (2-tail)                 0 018
Current GPA
  Pearson Crrl                   286
  Sig (2-tail)                 0 000
In Finance course now?
  Pearson Crrl                 0.087
  Sig (2-tail)                 0 062
Test Anxiety
  Pearson Crrl                   144
  Sig (2-tail)                 0 002
Numeric Anxiety
  Pearson Crrl                -0.263
  Sig. (2-tail)                0 000
Course Anxiety
  Pearson Crrl                  -230
  Sig (2-tail)                 0 000
Finance Anxiety
  Pearson Crrl                -0.221#
  Sig. (2-tail)                0 000#
Self Efficacy
  Pearson Crrl                 1.000#
  Sig. (2-tail)                   --

(2-tailed) 466
(2-tailed) Key measures Bold type

Note: Bold type indicated with #.

Table 5
Correlation of Finance Anxiety and Self-Efficacy

Under 25      338   -0.206 **     0.000
25 Over        87   -0.151        0.158
Graduate       47   -0.386 **     0.000
Total         472   -0.218 **     0.000

** 0.010 (2-tailed)

Table 6a
Comparison of Means for Finance Anxiety

Subgroup             Mean    Std. Dev

Under 25       339   2.927       0.86
vs. 25 Over     87     862        934

Under 25       339   2.927       0.86
vs. Grad        45      74       0.86

25 Over         87   2.862      0.934
vs. Grad        45     741       .846

Subgroup      F-Value    Sig.

Under 25
vs. 25 Over    0.391     0.532

Under 25
vs. Grad       1.862       172

25 Over
vs. Grad       0.53        468

Table 6b
Comparison of Means for Self-Efficacy

Subgroup                   Mean     Std. Dev

Under 25          360      4.551      0.656
vs 25 Over         87      4.913      0.511

Under 25          360      4.551        656
vs. Grad           52      4.977       0.54

25 Over            87         13        .51
vs. Grad           52      4.977       0.54

Subgroup       F-Value    Sig.

Under 25
vs 25 Over     23.556     0.001 **

Under 25
vs. Grad       19.946     0.00 **

25 Over
vs. Grad          494       484

** p<0. (2-tailed)

Table 7a. Median-Split Results for
Finance Anxiety

                          Above     Below
Subgroup    Number      ("High")   ("Low")    Total
           percent       Median    Median

                            178        16       339
Under 25         %        52.5%     47.5%    100.0%
                             45        42        87
25 & Over        %        51.7%     48.3%    100.0%
                             21        24        45
Graduate         %        46.7%     53.3%    100.0%
                            244       227       471
Total            %        51.7%     48.2%    100.0%

Table 7b. Median-Split Results for Self-Efficacy

                        Above      Below
Subgroup   Number /    ("High")   ("Low")     Total
            percent     Median    Median

                            166       193       359
Under 25       %          46.2%     53.8%    100.0%
                             59        28        87
25 Over        %          67.8%     32.2%    100.0%
                             39        13        52
Graduate       %          75 0%     25.0%    100.0%
                            264       234       498
Total          %          53.0%     47.0%    100.0%