Statistic Anxiety Research - Report Example

STATISTICS ANXIATY MAY 2010 Abstract Knowledge about statistics anxiety and attitude towards statistics can be a very important in helping students to face the challenges they face in statistical courses and education in general. The knowledge is also vital for lecturers as it gives them direction how to make students have a positive attitude towards statistics and overcome anxiety. The study involved 239 undergraduate psychology students who had enrolled in a course of introduction to research methods. From the study it was established that there exist a correlation of -.334 between statistics anxiety and attitude towards statistics. It was also established that the participants who were under 25 years had a higher anxiety towards statistics (43.7338) and had a more negative attitude (47.1081) as compared to those with over 25 years of age who had an average attitude value of (52.4865) and anxiety value of 43.3171. There was discussion of the results and then recommendations were given. Statistical anxiety and attitude towards statistics Many students have been found to have a problem with statistics and this affect their overall performance adversely. It is approximated that 80% of students have statistics anxiety and this makes the students to perform decimally in statistics and also perform unsatisfactorily in research methodology courses. Statistics anxiety can be defined as being apprehensive whenever one encounters statistics in different forms at any level (Onwuegbuzie, 2004). Statistics anxiety is specific to every situation even though there is the emergence of the symptoms at a particular moment especially when statistics is being applied in a formal situation (Zeidner, 1991). It has been found that statistics anxiety emerge in the students whenever they are faced with ideas, problems or issues that are statistical by nature, evaluative situations, or instructional situations (Feinberg & Halperin, 1978; Onwuegbuzie & Daley, 1996 ). Many students who enroll for statistics tend to procrastinate on taking their assignment. The issue of students having problems with statistics has attracted a lot of research attention. One of the researches done on statistics anxiety had the objectives of examining the procrastination on assignments among graduate students and to investigate the relationship that exist between six statistics anxiety dimensions. There was a revelation that many of the research participants experienced procrastination problems in their writing of term papers, when studying for their examinations in statistics and in completion of their weekly reading assignments. When a correlation was done in the research there was an indication that academic procrastination was as a result of fearing to fail and evading of tasks, class and test anxiety, fearing to ask for help, and the fear of the statistics teachers. There are six components that have been identified by use factor analysis. These factors are: the fear statistics, fearing to ask for help, computational self concept test and class anxiety and worth of statistics (Cruise et al, 1985, Hembree, 1988)). The authors define worth of statistics as being the perception the students have on the relevance of statistics, interpretation anxiety is the anxiety experienced by students whenever they are faced by a situation that requires of them to make a decision by interpreting statistics data. Test and class anxiety is the anxiety that is involved when one is taking statistics class or test and computational self concept is the anxiety that is involved in the attempt to solve mathematics and also the way the student perceive themselves in terms of doing mathematics. The fear of statistics teacher is the perception of the student about the statistics instructor while fear of asking for help comes about when the students are asking either their fellow students or instructors for help so they can have an understanding what has been covered in class or any other statistical data. Statistics anxiety has been found to have a relationship with self concept of mathematics, the number of courses that one has pursued previously, the length of time since one took his last mathematical course, ones academic status, mathematical ability, use of calculator, style used in learning, ethnicity and grade expectation(Benson, 1989; Zeidner, 1991; Wilson, 1997; Onwuegbuzie, 1999a). Several research that have been done have shown that there is a negative relationship of course performance and statistics (Zeidner, 1991; Elmore et al., 1993; Lalonde & Gardner, 1993; Onwuegbuzie & Seaman, 1995). To support this it has been established that statistics anxiety is the best indicator of research methodology and also statistics (Fitzgerald et al., 1996; Hollander & Wolfe, 1973). According to a research by Onwuegbuzie and Seaman (1995) it was established that the graduate students that recorded high statistics anxiety on being randomly assigned a statistics examination that was administered in a condition of timing had poor performance when compared to the low anxiousness counterparts who were given the same test in un timed conditions. Statistical anxiety has also been found to have a relationship with the age of the students. Students who are pursuing their degree courses with age of 25 years or above have been found to perform poorly because of the different challenges they face in class. These challenges include unrealistic goals, poor self image, social-familial problems and excessive practical orientation (Bill, 2010). Research has also been done to establish the relationship between anxiety and academic procrastination. It was established that there was a positive correlation between the two. Although a lot of research has been done in the area of statistics anxiety there are gaps that need to be filled by more research work. One of the areas that may need more research and which this study addressed was attitude of students towards statistics and its relationship with statistics anxiety. The hypothesis of the study were that there is a negative correlation between statistics anxiety and the attitude towards statistics, that the over 25 students have higher statistics anxiety and more negative attitude towards statistics as compared to those who are below 25 years. Another hypothesis of the study was that most of the research participants had had a previous experience of beyond year 12. Method The research involved the administering of Statistics Anxiety Rating Scale (STARS) and statistical attitude (SA) to 239 undergraduate psychology students who had enrolled in a course of introduction to research methods. A questionnaire was presented to the participants and they were to fill it voluntarily. The participants gave their demographic details in the questionnaire including their age and sex. Out of the 239 students a total of 198 students managed to feel the questionnaire and gave permission for their data to be used in the study. Out of the 198 female students were 160 while the 38 were male. For the female participants, 126 belonged to group 1 (less than 25 years of age) while for the male 31 belonged to this group. The number of those who belonged to group 2 is as shown in the table. The participants also gave information about their previous Maths experience 71 of the participants indicated that they had a less than year 12 math experience while 128 had year 12 experience of mathematics. This in agreement with the hypothesis that most of the students who took part in the research had had up to year 12 maths experience.The age of the participants was further been described in raw 3 of the table where the minimum, maximum and median of the age has been given. The value of the median, minimum age and maximum age when the participants are in the same group was 22, 18 and 65 respectively while when the participants are placed into groups the values changed as shown in the table. TABLE 1 Demographics of research participants Group 1 Group 2 Total Sex Males Females n=31 n=126 n=7 n=34 n=38 n=160 Previous Maths Experience Less than Year 12 Year 12 n=50 n=107 n=21 n=21 n=71 n=128 Age Median=19 Min= 18 Max=24 n=155 Median=33 Min= 25 Max=65 n=43 Median=22 Min= 18 Max=65 N=198 Design There was use of a quasi-experiment between groups’ design where the independent variable was age while dependant variables were attitude and anxiety Materials Data collection involved a questionnaire being delivered on line by a Tellus. The first item on the questionnaire was an open ended question where the students were asked what they thought would be involved in studying statistics. In the questionnaire there were two scales; Statistics Anxiety scale and Attitudes Towards Statistics scale which are adapted from Trembley. In each of the scale there were five questions which were worded positively and five which were worded negatively on a Liker scale. The scale consists seven points that range from strongly disagree to strongly agree. In both of the scales the minimum score was given a value of 1 while the maximum score was given a value of 7. If a participant had a high SA value it was an indication of high anxiety on the other hand a high value of ATSS is and indication of positive attitude. Some of the SA items that were responded to by the participants were: When I know the proper statistical procedure involved in a problem, I feel confident that I can obtain the correct solution and I do not feel anxious about statistics class. For the ATSS some of the items that were to be responded to were: Statistics should not be a requirement for a Psychology degree, Statistics is not as important as some lectures suggest and Personally, I think there is really no need to learn statistics to be a good psychologist. The age sex and previous Math experience was also supposed to be given by the participants on the questionnaire. Procedure In the first lecture the students were asked by their course instructor to complete the online survey before three weeks into the course. The students were assured of confidentiality of the information given on the questionnaire. The student students got access to the questionnaire through a hyperlink on the course home webpage. The students were also to choose whether to or not to allow their data to be used. There was debriefing of students in the subsequent classes. RESULTS Correlations between anxiety and attitude From the table it can be seen that there is a negative correlation between anxiety and attitude. The correlation value between the two variables is -0.334 at 0.000 level of significance. This is an indication that students who have negative attitude (law total values) registered high values of statistics anxiety. This is in agreement with the hypothesis that was stated earlier. For the t-test the result was as shown in Table 3 below. From the table the t- values are higher for anxiety as compared to those of attitude. The significance value is much smaller for anxiety when they are compared for those of attitude. This is an indication that the difference in means of attitude score for the two groups is likely to be due to actual difference in the means of the two groups than by chance while the converse is true for the case of anxiety. TABLE 2 Correlations between anxiety and attitude Anxiety Total Attitude Total Anxiety Total Pearson Correlation 1 -.334(**) Sig. (2-tailed) . .000 N 194 188 Attitude Total Pearson Correlation -.334(**) 1 Sig. (2-tailed) .000 . N 188 190 Correlation is significant at the 0.01 level (2-tailed). TABLE 3 Independent-Sample Tests Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Attitude Total Equal variances assumed 2.855 .093 -.570 186 .570 -.6794 1.19242 -3.03182 1.67297 Equal variances not assumed -.533 108.619 .595 -.6794 1.27439 -3.20533 1.84648 Anxiety Total Equal variances assumed 2.931 .089 -2.083 192 .039 -3.5535 1.70562 -6.91762 -.18929 Equal variances not assumed -2.013 124.446 .046 -3.5535 1.76568 -7.04810 -.05881 Descriptive Statistics From the table below it can be observed that mean of anxiety for group 1 was 43.0654 which is lower than that of group 2 which had a value of 43.3171. While the mean of all participants was registered as 43.1186. The standard deviation in group1, group2 and the total were as shown in the table. On the other hand the means attitude scores for group1, group 2 and the two groups combined was found to be 47.6689, 52.4865 and 48.6170 respectively. This means that our hypothesis that the group two students are more anxious of statistics and have a more negative attitude as compared to group 2 is not true. TABLE 4 Descriptive statistics of Anxiety and Attitude Group 1 Group 2 Total Statistics Anxiety Mean=43.0654 SD=10.56289 N=153 Mean=43.3171 SD=14.37435 N=41 Mean=43.1186 SD=11.43268 N=194 Attitude Towards Studying Statistics Mean=47.6689 SD=7.33460 N=151 Mean=52.4865 SD=8.34540 n=37 Mean=48.6170 SD=7.76198 N=188 Descriptive statistics Z scores N Minimum Maximum Mean Std Skewness Kurtosis Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error Zscore(Attitude) Attitude Total 188 -2.39849 2.62600 .0000000 1.00000000 -.195 .177 -.284 .353 Zscore(Anxiety) Anxiety Total 194 -2.54696 2.08888 .0000000 1.00000000 -.224 .175 -.404 .347 Valid N (listwise) 186 Descriptive statistics N Minimum Maximum Mean Std Skewness Kurtosis Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error Attitude Total 188 30.00 69.00 48.6170 7.76198 -.195 .177 -.284 .353 Anxiety Total 194 14.00 67.00 43.1186 11.43268 -.224 .175 -.404 .347 Valid N (listwise) 186 Discussions From the study it has been established that many of the students do experience statistics anxiety and also have a negative attitude towards statistics. From the comments the students gave regarding the statistics course it revealed that the students had an idea of the course involving calculations. The comments also revealed that the students may not be having any positive attitude towards courses that involve mathematics. The students also have a feeling of the course not being not interesting and consuming more time than other courses which they study that do involve calculations. It is therefore a challenge to the educators to make the statistics courses to be appealing to the learners. One of the ways that has been identified that can achieve this is through the combining of application oriented teaching methods and the instructors paying more attention to the students. From the study it has shown that group1 students have a more negative attitude towards statistics and also a high statistics anxiety than the group 2. This is in disagreement with the expectation that the group two students will have higher anxiety and a more negative attitude towards statistics because of the fact that they have many issues that make them not to concentrate on their academics. This could mean that the group 2 students may not have been sincere in filling the questionnaires. This could be as a result of feeling that they are old and they should not admit having this “weakness” of being anxious and having a negative attitude towards statistics. On the other hand this could because of the fact that the group 2 students may have met many statistics situations probably at work place and therefore they understand the need to study statistics. The findings of this study can benefit both educators and students of statistics. The students should come to the realization that having a negative attitude towards statistics leads to poor performance in statistics related courses. For the students to have a solution they should first ask themselves the reason they have a bad attitude and anxiety towards statistics. One of the reasons could be that they feel that the course is not useful in their present and even future life or the course is just generally hard to understand. The educators also have the responsibility of looking into the factors that leads to bad attitude and anxiety towards statistics. Incase the educators for example come to the realization that students are having a bad attitude towards statistics because of feeling that the knowledge is not useful in their present or future jobs, the lecturer should take the initiative to explain to the students how useful the statistics knowledge is beneficial so as to give the students a motivation. Incase the students feel anxious and have a bad attitude of statistics because of poor mathematics background then the students can be advised on how to improve in mathematics by studying appropriately. This could be through allocating more time for studying mathematics. The students can also improve in statistics by working towards combating negative thoughts towards mathematics related courses like statistics. The three methods that can be used to achieve this is through improving attitude, positive self talk, by one visualizing themselves succeeding and preparing for any mathematical situation in advance. Other useful tips are for one to join a support group and to learn about stress management. There are some shortcomings in the research that can be addressed in any future research in this area. The research did not put into consideration the race of the participants. Though research similar to this done by Clark and Hill revealed that there was no variation due to race (Clark and Hill,1994).Onwuegbuzie (1999a) reported that for Africa-America graduate students recorded higher levels of statistics anxiety than Caucasian-American graduate students. It therefore follows that the present findings may not be applicable for any graduate students of any ethnicity. This therefore calls for more research in this area that will put into consideration the race of the participants. Due to the fact that this research was done via self assessed instrument and not through an actual behaviour it could also be a limitation of study due to the fact that students may give answers that they think are socially appealing. It will be advisable therefore in future research a consideration should be given to using behavioral measures of statistics anxiety and attitude. REFERENCES Benson, J. (1989).Structural components of statistical test anxiety in adults: an exploratory model,Journal of Experimental Education, 57, 247–261. Bill J. A. (2010). Statistics Anxiety: The Nontraditional Student. Retrieved on 20th May 2010 from Cruise, R. J., Cash, R. W., & Bolton, D. L. (1985). Development and validation of an nstrument to measure statistical anxiety, paper presented at the Annual Meeting of the Statistical Education Section. Proceedings of the American Statistical Association, August. Cruise, R. J. & Wilkins, E. M. (1980). STARS: Statistical Anxiety Rating Scale. Unpublished manuscript, Andrews University, Berrien Springs, MI. Elmore, P. B., Lewis, E. L. & Bay, M. L. G. (1993). Statistics achievement: a function ofattitudes and related experience, paper presented at the Annual Meeting of the American Educational Research Association (ERIC Document Reproduction Service No. 360 324). Feinberg, L. & Halperin, S. (1978). Affective and cognitive correlates of course performance in introductory statistics, Journal of Experimental Education, 46(4), 11–18. Fitzgerald, S. M., Jurs, S. & Hudson, L. M. (1996). A model predicting statistics achievement among graduate students, College Student Journal, 30, 361–366. Hembree, R. (1988) Correlates, causes, effects and treatment of test anxiety, Review of EducationalResearch, 58, 47–77. Hollander, M. & Wolfe, D. A. (1973). Nonparametric statistical methods (New York, John Wiley). Lalonde, R. N. & Gardner, R. C. (1993). Statistics as a second language? A model for predicting performance in psychology students, Canadian Journal of Behavioral Science, 25, 108–125. Onwuegbuzie, A. J. 2004. Academic procrastination and statistics anxiety Assessment &Evaluation in Higher EducationVol. 29, No. 1, February 2004 Onwuegbuzie, A. J. (1999a). Statistics anxiety among African-American graduate students: an affective filter? Journal of Black Psychology, 25, 189–209. Onwuegbuzie, A. J. & Daley, C. E. (1996).The relative contributions of examination-taking coping strategies and study coping strategies on test anxiety: a concurrent analysis, Cognitive Therapy and Research, 20, 287–303. Onwuegbuzie, A. J. & Seaman, M. (1995). The effect of time and anxiety on statistics achievement, Journal of Experimental Psychology, 63, 115–124. Onwuegbuzie, A. J. (2000a). Academic procrastinators and perfectionistic tendenciesamong graduate students, Journal of Social Behavior and Personality, 15, 103–109. Onwuegbuzie, A. J. (2000b). Statistics anxiety and the role of self-perceptions, Journal ofEducational Research, 93, 323–335. Onwuegbuzie, A. J. & Wilson, V. A. (2003). Statistics anxiety: nature, etiology, antecedents, effects and treatments: a comprehensive review of the literature, Teaching in Higher Education, 8, 195–209. Ramirez, O. M., & Dockweiler, C. J. (1987). Mathematics anxiety: a systematic review,in: R. Schwarzer, H. M. van der Ploeg & C. D. Spielberger (Eds) Advances in test anxiety research(vol. 5) (Lisse, Swets & Zeitlinger), 157–175. Tomazic, T. J., & Katz, B. M. (1988). Statistical anxiety in introductory applied statistics, paper presented at the Annual Meeting of the American Statistical Association, New Orleans, LA, August. Wilson, V. (1997). Factors related to anxiety in the graduate statistics classroom, paper Presented at the Annual Meeting of the Mid-South Educational Research Association, Memphis, TN Zeidner, M. (1991) Statistics and mathematics anxiety in social science students—some interesting parallels, British Journal of Educational Psychology, 61, 319–328. Read More

Test and class anxiety is the anxiety that is involved when one is taking statistics class or test and computational self concept is the anxiety that is involved in the attempt to solve mathematics and also the way the student perceive themselves in terms of doing mathematics. The fear of statistics teacher is the perception of the student about the statistics instructor while fear of asking for help comes about when the students are asking either their fellow students or instructors for help so they can have an understanding what has been covered in class or any other statistical data.

Statistics anxiety has been found to have a relationship with self concept of mathematics, the number of courses that one has pursued previously, the length of time since one took his last mathematical course, ones academic status, mathematical ability, use of calculator, style used in learning, ethnicity and grade expectation(Benson, 1989; Zeidner, 1991; Wilson, 1997; Onwuegbuzie, 1999a). Several research that have been done have shown that there is a negative relationship of course performance and statistics (Zeidner, 1991; Elmore et al.

, 1993; Lalonde & Gardner, 1993; Onwuegbuzie & Seaman, 1995). To support this it has been established that statistics anxiety is the best indicator of research methodology and also statistics (Fitzgerald et al., 1996; Hollander & Wolfe, 1973). According to a research by Onwuegbuzie and Seaman (1995) it was established that the graduate students that recorded high statistics anxiety on being randomly assigned a statistics examination that was administered in a condition of timing had poor performance when compared to the low anxiousness counterparts who were given the same test in un timed conditions.

Statistical anxiety has also been found to have a relationship with the age of the students. Students who are pursuing their degree courses with age of 25 years or above have been found to perform poorly because of the different challenges they face in class. These challenges include unrealistic goals, poor self image, social-familial problems and excessive practical orientation (Bill, 2010). Research has also been done to establish the relationship between anxiety and academic procrastination.

It was established that there was a positive correlation between the two. Although a lot of research has been done in the area of statistics anxiety there are gaps that need to be filled by more research work. One of the areas that may need more research and which this study addressed was attitude of students towards statistics and its relationship with statistics anxiety. The hypothesis of the study were that there is a negative correlation between statistics anxiety and the attitude towards statistics, that the over 25 students have higher statistics anxiety and more negative attitude towards statistics as compared to those who are below 25 years.

Another hypothesis of the study was that most of the research participants had had a previous experience of beyond year 12. Method The research involved the administering of Statistics Anxiety Rating Scale (STARS) and statistical attitude (SA) to 239 undergraduate psychology students who had enrolled in a course of introduction to research methods. A questionnaire was presented to the participants and they were to fill it voluntarily. The participants gave their demographic details in the questionnaire including their age and sex.

Out of the 239 students a total of 198 students managed to feel the questionnaire and gave permission for their data to be used in the study. Out of the 198 female students were 160 while the 38 were male. For the female participants, 126 belonged to group 1 (less than 25 years of age) while for the male 31 belonged to this group. The number of those who belonged to group 2 is as shown in the table. The participants also gave information about their previous Maths experience 71 of the participants indicated that they had a less than year 12 math experience while 128 had year 12 experience of mathematics.

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