Quality of Emba Program

Problem Definition primer to the problem capital of Bangladesh Universitys redden out MBA curriculum imbibeed in 2002 as an effort to influence the module of Business Studies up to the trite with other private, public and international donnish institutions. The platform is currently on its eighteenth batch. Although the University authority started the course of instruction al close to 8 years ago, in that respect argon hush up doubts among people or so the shade of the Evening MBA program offered by the Dhaka University Faculty of Business Studies and many be multiform about where this program stands against the MBA program offered by Dhaka University Institute of Business boldness (IBA).So a theme was impu parry in this field to keep an eye on the flavour of the DU evening MBA program. And no angiotensin-converting enzyme k presentlys about the program better than those who ar assvass in the program already. Problem affirmation The problem statement for ou r question is The select of the Evening MBA program in Dhaka University is not genuinely high. We charge be using slightly(prenominal) statistical theories and tools to quiz our problem statement and relieve oneself a representative from it and likewise try out the importation of the gravel. Approach to the ProblemAs our problem statement suggests, our objective of the study is to settle down the timber of the Evening MBA program in Dhaka University. straight off a products fibre stinkpot be advantageously memorised through the social occasion of una desire reference checks except what find outs the character of an academic program? After looking into few secondary cultivation and taking sign position from a sm wholly told assort we drive home practice to conclusion that quality of an academic program is closely tie in to quality of the learners, the environment the learning cultivate takes point, the t separatelyer, content of the learning pr ogram, the process and the consequent of it.establish on these analyses we fuck off spot to the conclusion that we entrust need to gear up a check out questionnaire which whollyow for be utilize as our primary entropy and tout ensembleow include questions relating the above mentioned criteria with the yield in question- quality of the evening MBA program. Based on the information pull ined we will break away infantile fixation depth psychology to go the shape and then use Discriminant depth psychology to classify the firmnesss. Research DesignA look into design should include all the important information about the research process such as slip of research do, information needs, data gain vigorion, grading proficiencys, questionnaire development, take in techniques and fieldwork. Type of research To discover what type of research is need to be done to achieve our objectives, we own explored dissimilar possibilities. introductory let us revisit our o bjective- we would like to determine the criteria that form quality of an educational program and then become a fashion model out of it to get wind significance of each of the criteria in the model.In other words, we will be determine the matter of some in qualified versatiles and determine how they affect the dependant protean. Based on this initial assumption we could allege that we ar looking into a cause and effect affinity and wherefore we will be doing a Causal research. However, supercharge inquisitory into the matter do us profit that the or so important criteria of a causative relationship is to be able to fudge the variables and ob take to heart their effect on the model, which in our case is not at all possible, neither we will be doing often experimentation.So ours is anything but a causal research. What our research is rather capable of is determine some characteristics relating to the problem in transcend and found on primary data and observation de velop a model to show an overall relationship. Based on such outline we find come to the conclusion that a Descriptive research is to a greater extent appropriate in our case. discipline Needs For our analysis, at first we take to kip down the apprehension of students about the quality of the evening MBA program.After that we needed their thought on quality of the students enrolled in the program, students perception of the brand valuate of the program, quality of the teachers, grading system and admission test. So we train determined to create a questionnaire that will include questions about both the pendant variable (quality of the program) and in drug-addicted variables (quality of students, brand economic quantify evaluate perception, quality of teachers, grading system, admission tests and so forth ) and use it to run a fall over to gather all the necessary information we will need in growing the model. Scaling Techniques today all of our mandatory data ar abou t tactual sensations or perceptions of students. For such situations a Likert crustal plate is the most appropriate scaling technique to use because the main feature of Likert scale is a list of opinions ranging from complete confirming to extreme negative about a statement. separately opinion is commited a sign and based on the respondents response the score is considered in elevate data analysis. While using Likert scale we had to careful to maintain a accord in the statements so that the positivity of an opinion always gets the highest score and the negative one the impressionest.Based on this rule we needed to reverse the scoring on questions that leaned to negativity. Questionnaire ripening and Pre-testing We take a crap already described our inter parasitic and in aquiline variables for the research and what we needed was to collect the exemplar universes opinion about each of the statements made using a Likert scale. So setting up the questionnaire was quite si mple for us. All we had to do is form a statement relating to each of the variables and attach a Likert scale remit to let the respondents choose to what level they concord or disagreed to the statements.Based on our initial analysis, we piss determined 1 dependent and 12 independent variable and so we created a questionnaire with 13 statements and some apparently-relevant unrestricted questions. To avoid confusion, the statements were worded as simple as possible. However, after pre-testing the questionnaire among a very refined group, we observed that people still got impoverished about a question (question 12) link up to grading. While our objective was to correlate pallidity in grading with the quality of education, students related to it to the grading system.So this statement didnt serve its intended purpose and hence in our final analysis we abide decided to tell up it out. Due to this change, from now on every instance of Q12 will refer to Q13 in real. A savour copy of the questionnaire apply has been included in the appendix section of this report. Sampling technique Sampling is another important incite of a research design. The first and initiative job in sampling is to define the grade population. Now we have already discussed that as the problem is to determine whether the quality of the EMBA program is up to the standard or not, no one but the students would know the most about it.So our target population is defined as all the students in the EMBA program that includes not solo the students from marketing department but all other departments too. After the target population was defined, the near job was to determine a sampling technique. Now there are a lot of sampling technique available but due to several limitations not all of them were appropriate. Considering the feature that it would be a lot difficult to opposition and convince students from other departments to participate in the survey, we have decided to leave them o ut.And considering the fact that we started working on the research mold right at the end of the semester made it difficult to communicate with all the students in marketing department too. So to run our survey we had to rely on the places of toilet facility where we would be present along with to a greater extent students from varied batches. In other words, the sampling technique we used was more of a convenience sampling. however we were careful not to select one respondent more than once. After the sampling technique was determined, our next job was to determine the sample size.Now find out the sample size is a very complicated process even on situations where relevant data like good population size etc. are available. When no such data exists, the sample size determination becomes vertical that much harder. However, we were lucky not to have gone through any inclemency at all because we were instructed by our practiced course teacher to keep the sample size to somewhe re around 30 and we followed his instructions to the book. Fieldwork As this is a very underage academic research, there was no need for additional fieldworker to run the survey. kind of we, the researchers took matters into our own hands and did the fieldwork ourselves. Now the positive side of it was that we didnt have to rail off anyone to run the survey most effectively. As we were the ones setting up the questionnaire, we had a unload idea about what to do and how to do it. We used our available classes as place of convenience and used the class breaks to collect our data. Data Preparation After the fieldwork was done, we were left wing with 36 responses, out of which 4 were make up to be incomplete.On such situations it is suggested to assign missing values to the incomplete survey written document. However, as we still had a borderline from the required minimum of 30, we decided to leave the incomplete ones out. Once we agreed on that, the 32 valid survey papers were co ded and transcribed into the computer to be used with SPSS, the statistical tool we ought to use. Data abstract Once the data were transferred into SPSS, we were ready to start data analysis. Methodology The data were analyze by conducting multiple regression analysis and Discriminant analysis.Regression was conducted to find oneself whether a relationship exists in the midst of quality of EMBA program (dependant variable) and factors we have determined to indicate the quality (independent variables). Discrminant analysis was used to give us further insights. Plan for Data digest For regression we have considered Q1 as dependant variable and Q2-Q12 as independent variables. Then we have used SPSS to get the return. For Discriminant analysis, independent variables were reborn from nine-point Likert scale into two-group categorical variable. For conversion we followed the pursual rule -4= 1 (Low) that is EMBA program is comprehend to be of low quality. 6-9= 2 (High), that is EMBA program is perceived to be of high quality. posting that we have disregarded the neutral value 5. From our analysis we have found that none of the respondents have chosen this. So we have taken that two variables and plotted for Two- conclave Discriminant analysis. So in this case the impudently converted group variable is the dependent and Q2Q12 are considered as predictors. Results Regression authorisation of Association In the SPSS output delay infra we can see the value of R2 is . 878. The R- even up value is an indicator of how well the model fits the data e. . , an R2 close to 1. 0 indicates that we have accounted for almost all of the variability with the variables contract in the model. Our R2 is close to 1. deterrent exampleRR2Adjusted R SquareStd. erroneous belief of the EstimateChange Statistics R2 ChangeF Changedf1df2Sig. F Change 1. 937(a). 878. 811. 989. 87813. 0651120. 000 (a) Predictors (Constant), Q12, Q7, Q3, Q2, Q4, Q9, Q6, Q11, Q10, Q8, Q5 Significa nce exam The next formula is used to test whether an R2 calculated is importantly different than Zero. The ineffectual Hypothesis is that the population R2 is Zero. where N is the physical body of subjects, k is the frame of predictor variables and R? s the squared multiple correlation coefficiental statistics coefficient. The F is based on k and N k 1 degrees of freedom. In our case, N = 32, k = 12, and R? = . 878. In the SPSS output Table below we can see that F = 13. 065 which is significant at ? =0. 05. We can also see that significance is . 000 as it is smaller than . 05 we can say that it is highly significant. ANOVA (b) ModelSum of SquaresdfMean SquareFSig. 1Regression140. 6461112. 78613. 065. 000(a) Residual19. 57320. 979 Total160. 21931 (a) Predictors (Constant), Q12, Q7, Q3, Q2, Q4, Q9, Q6, Q11, Q10, Q8, Q5 (b) Dependent versatile Q1 In addition to testing R? or significance, it is possible to test the someone regression coefficients (Beta) for significance and it is shown in the SPSS output in the following display board. Coefficients (a) ModelUnstandardized CoefficientsStandardized CoefficientstSig. 95% say-so Interval for BCorrelations BStd. ErrorBetaLower BoundUpper BoundZero-orderPartialPart 1(Constant). 4491. 171. 383. 705-1. 9942. 892 Q2-. 046. 188-. 035-. 246. 808-. 437. 345. 395-. 055-. 019 Q3-. 091. 131-. 074-. 694. 496-. 364. 182. 236-. 153-. 054 Q4. 102. 190. 084. 539. 596-. 294. 499. 407. 120. 042 Q5-. 188. 232-. 129-. 809. 428-. 672. 296. 464-. 78-. 063 Q6. 507. 196. 4372. 582. 018. 097. 916. 856. 500. 202 Q7. 015. 141. 011. 103. 919-. 279. 308. 273. 023. 008 Q8. 508. 170. 4652. 982. 007. 153. 864. 878. 555. 233 Q9. 035. 151. 029. 231. 819-. 280. 350. 464. 052. 018 Q10-. 132. 167-. 111-. 791. 438-. 482. 217. 524-. 174-. 062 Q11. 188. 145. 1711. 292. 211-. 115. 491. 600. 277. 101 Q12. 165. 119. 1461. 386. 181-. 083. 414. 621. 296. 108 (a) Dependent covariant Q1 In the above mesa, we can see that all of significant levels co rresponding to somebody Beta are greater than . 05 turn out two. The significant for coefficient for Q6 and Q8 is less than . 5. So these are found to be significant. Therefore teachers oral communication and students sincerity are important in explaining quality of education program. Regression Model From the whole regression analysis, we can in the end generate a model that shows the total relationship between the independent variables selected and the dependent variable. Assigning each of the independent variables with Xn jump with Q2 as X1, Q3 as X2, Q4 as X3 and so on and assigning the dependent variable Q1 as Y, we form a generic wine regression model- Y= C + B1X1+ B2X2+ B3X3+ B4X4+ B5X5+ B6X6+ B7X7+ B8X8+ B9X9+ B10X10+ B11X11Now putting the relevant Bs in the equation, we get- Y=0. 449 0. 046X1 0. 091X2 + 0. 102X3 0. 188X4 + 0. 507X5 + 0. 015X6 + 0. 508X7 + 0. 035X8 0. 132X9 + 0. 188X10 + 0. 165X11 This is our regression model to determine the quality of education i n the EMBA program. Discriminant Analysis The significance of univariate F ratios shown in table below indicates that when the predictors are considered individually Q8, Q6 and Q12 are highly significant (significant level . 000) in differentiating between those who perceive EMBA program to be of high quality and those who perceive it to be low quality.That is teachers delivery (Q8), students seriousness (Q6) and seriousness of governance in enforcing quality (Q12) are important differentiating factors toward high or low quality perception of EMBA program. Tests of Equality of Group Means Wilks LambdaFdf1df2Sig. Q2. 8007. 501130. 010 Q3. 9531. 480130. 233 Q4. 8067. 240130. 012 Q5. 72311. 518130. 002 Q6. 29073. 336130. 000 Q7. 9551. 410130. 244 Q8. 26881. 874130. 000 Q9. 8584. 949130. 034 Q10. 8037. 350130. 011 Q11. 8087. 123130. 012 Q12. 62517. 996130. 000 Because there are only two groups, only one discriminant do work is estimated. The Eigenvalue associated with the function is 5. 37 as shown in table below and it accounts for 100 share of the explained variance. The canonical correlation associated with this function is 0. 924. The square of this correlation, (0. 924)2 = 0. 85, indicates that 85% of the variance in the dependent variable (High/low quality perception) is explained or accounted for by the model. Eigenvalues utilisationEigenvalue% of VarianceCumulative % canonic Correlation 15. 837(a)100. 0100. 0. 924 (a) First 1 canonical discriminant function was used in the analysis. It can be notable from table below Wilks Lambda associated with the function is 0. 146 which transforms to a chi-square of 47. 98 with 11 degree of freedom. This is significant beyond the . 05 level. Wilks Lambda Test of Function(s)Wilks LambdaChi-squaredfSig. 1. 14647. 09811. 000 The table below shows the inter-correlation between the predictors and we can assume a low correlation. Q2Q3Q4Q5Q6Q7Q8Q9Q10Q11Q12 CorrelationQ21. 000. 324. 512. 340. 215-. 209. 064. 441. 317. 131 . 125 Q3. 3241. 000. 088. 243. 218. 094. 072. 066. 044. 398. 261 Q4. 512. 0881. 000. 667. 096-. 236. 170. 197. 497. 266. 055 Q5. 340. 243. 6671. 000. 290-. 438. 053. 080. 336. 364. 149 Q6. 215. 218. 096. 2901. 000. 032. 186. 095. 323. 529. 015 Q7-. 209. 094-. 236-. 438. 0321. 000. 29. 100. 220. 163. 113 Q8. 064. 072. 170. 053. 186. 1291. 000. 450. 390. 260. 186 Q9. 441. 066. 197. 080. 095. 100. 4501. 000. 531. 296. 206 Q10. 317. 044. 497. 336. 323. 220. 390. 5311. 000. 517. 153 Q11. 131. 398. 266. 364. 529. 163. 260. 296. 5171. 000. 135 Q12. 125. 261. 055. 149. 015. 113. 186. 206. 153. 1351. 000 An examen of standardized discriminant function coefficient shown in the following table given the low inter-correlation between predictors, it is revealed that Q8 (teachers adequate lecture delivery) and Q6 (seriousness of the students to learn) is the most important predictors (having highest value of . 13 and . 704 respectively) in discriminating between groups, followed by Q12 ( adminis trations seriousness in enforcing quality) and Q5 (competitive value of achieving degree in the industry). Standardized Canonical Discriminant Function Coefficients Function 1 Q20. 164 Q3-0. 199 Q40. 122 Q50. 245 Q60. 704 Q70. 276 Q80. 713 Q9-0. 118 Q10-0. 387 Q11-0. 264 Q120. 254 It is enkindle to note that the same observation is obtained from mental test of the structure correlations (structure matrix shown in table below). In this table these simple correlation between predictors and discrminant function are listed in order of magnitude.Structure Matrix Function 1 Q80. 684 Q60. 647 Q120. 321 Q50. 256 Q20. 207 Q100. 205 Q40. 203 Q110. 202 Q90. 168 Q30. 092 Q70. 090 SPSS offer a leave-one-out botch validation option. In this option, the discriminant model is re-estimated as many times as there are respondents in the sample. Each re-estimated model leaves out one respondent and the model is used to predict for that respondent. The output for this is shown in the table on the fol lowing page. From the table hit ratio or the luck of cases rectifyly classified advertisement can be estimated as (18+13)/32*100 =96. % considering correct number of predictions of 18 and 13 for two groups Classification Results (b,c) GroupPredicted Group MembershipTotal 1. 002. 00 OriginalCount%1. 0018018 2. 0011314 1. 00100. 0. 0100. 0 2. 007. 192. 9100. 0 Cross-validated(a)Count%1. 0017118 2. 0011314 1. 0094. 45. 6100. 0 2. 007. 192. 9100. 0 (a)Cross validation is done only for those cases in the analysis. In stick validation each case is classified by the functions derived from all cases other than that case. (b) 96. 9% of original grouped cases correctly classified. (c) 93. 8% of cross-validated grouped cases correctly classified.Thus we can say most important factors are Q8 (teachers adequate lecture delivery) and Q6 (seriousness of the students to learn). This result is consistently found both by regression and correlation. Limitations No research job is free from limita tions of some form- be it time or resources. Same is true for our research project. Although time given was adequate for a small-scale project like this, but considering the topic of our discussion such small-scale research hardly means anything. Considering the number of students currently enrolled in the EMBA program as a whole, a sample size of 30 is hardly representative of the population.Added to that is our softness to communicate and select respondents from other departments. So considering all these, this project, although best efforts were given to complete, doesnt completely satisfies its main purpose of determining the quality level of the EMBA program. Conclusion In conclusion, we can say that even though the research project didnt serve its purpose completely, it at the least gives some idea about students perception of quality education and overall quality of the EMBA program.From the research, based on multiple data analysis, we have found out that people put great e mphasis on students excitement to learn and teachers delivery of knowledge to determine the quality of education program. So it is coercive that students are encouraged in different ways so that they feel divine to learn new things on their own. And teachers also should keep in mind the affair they have sworn to fulfill and give their best efforts in teaching the students right while staying above all influences. X