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TEAS prep course trends

TEAS prep course trends. YOUR FUTURE BEGINS TODAY Joel Collazo , MD Maria E Guzman, MPM. PROGRESS PER CAMPUS AND ALL DMC. ANALYSIS OF RESULTS OF STUDENTS THAT TOOK THE REVIEW. DMC all campuses. Hialeah-Miami Lakes Campus. Homestead Campus. Miami Campus. Hollywood campus.

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TEAS prep course trends

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  1. TEAS prep course trends YOUR FUTURE BEGINS TODAY Joel Collazo, MD Maria E Guzman, MPM

  2. PROGRESS PER CAMPUS AND ALL DMC ANALYSIS OF RESULTS OF STUDENTS THAT TOOK THE REVIEW

  3. DMC all campuses

  4. Hialeah-Miami Lakes Campus

  5. Homestead Campus

  6. Miami Campus

  7. Hollywood campus

  8. COMPARISON BETWEEN REVIEW AND NO REVIEW STUDENTS

  9. DMC: TOTAL OF STUDENTS THAT TOOK THE TEAS TEST (JAN-MAY 2012)

  10. HOMESTEAD:TOTAL OF STUDENTS THAT TOOK THE TEAS TEST (JAN-MAY 2012)

  11. MIAMI:TOTAL OF STUDENTS THAT TOOK THE TEAS TEST (JAN-MAY 2012)

  12. HOLLYWOOD: TOTAL OF STUDENTS THAT TOOK THE TEAS TEST (JAN-MAY 2012)

  13. MIAMI LAKES:TOTAL OF STUDENTS THAT TOOK THE TEAS TEST (JAN-MAY 2012)

  14. DATA COLLECTION • THE STATISTICAL ANALYSIS WAS DONE WITH DATA OBTAINED FROM ALL FOUR CAMPUSES WHERE THE TEAS PREPARATION COURSE IS CURRENTLY AVAILABLE. • BETWEEN JANUARY AND MAY 2012. • INCLUDE A TOTAL POPULATION OF 394 STUDENTS.

  15. DATA

  16. General Regression Analysis: X3 versus R, NR • Regression Equation • X3 = 1.13229 + 0.0215274 R + 0.129967 NR  • Coefficients • Term Coef SE Coef T P 95% CI • Constant 1.13229 2.81034 0.40290 0.704 (-6.09191, 8.35650) • R 0.02153 0.16012 0.13445 0.898 (-0.39007, 0.43313) • NR 0.12997 0.03560 3.65128 0.015 ( 0.03847, 0.22147)  • Summary of Model  • S = 2.52636 R-Sq = 88.26% R-Sq(adj) = 83.57% • PRESS = 96.3839 R-Sq(pred) = 64.55%  • Analysis of Variance  • Source DF Seq SS Adj SS Adj MS F P • Regression 2 239.962 239.962 119.981 18.7984 0.004720 • R 1 154.872 0.115 0.115 0.0181 0.898294 • NR 1 85.091 85.091 85.091 13.3318 0.014729 • Error 5 31.913 31.913 6.383 • Total 7 271.875

  17. General Regression Analysis: X4 versus R, NR   • Regression Equation • X4 = 4.74964 - 0.0736235 R + 0.146592 NR • Coefficients  • Term Coef SE Coef T P 95% CI • Constant 4.74964 3.56606 1.33190 0.240 (-4.41720, 13.9165) • R -0.07362 0.20318 -0.36236 0.732 (-0.59590, 0.4487) • NR 0.14659 0.04517 3.24558 0.023 ( 0.03049, 0.2627)  • Summary of Model • S = 3.20572 R-Sq = 88.29% R-Sq(adj) = 83.61% • PRESS = 151.251 R-Sq(pred) = 65.54%  • Analysis of Variance  • Source DF Seq SS Adj SS Adj MS F P • Regression 2 387.492 387.492 193.746 18.8531 0.004690 • R 1 279.240 1.349 1.349 0.1313 0.731893 • NR 1 108.252 108.252 108.252 10.5338 0.022808 • Error 5 51.383 51.383 10.277 • Total 7 438.875

  18. General Regression Analysis: X5 versus R, NR   • Regression Equation  • X5 = -8.57511 + 0.70737 R + 0.404303 NR  • Coefficients  • Term Coef SE Coef T P 95% CI • Constant -8.57511 6.50567 -1.31810 0.245 (-25.2985, 8.14824) • R 0.70737 0.37066 1.90841 0.115 ( -0.2454, 1.66018) • NR 0.40430 0.08240 4.90665 0.004 ( 0.1925, 0.61612)  • Summary of Model  • S = 5.84829 R-Sq = 88.16% R-Sq(adj) = 83.43% • PRESS = 689.874 R-Sq(pred) = 52.25%  • Analysis of Variance  • Source DF Seq SS Adj SS Adj MS F P • Regression 2 1273.86 1273.86 636.931 18.6224 0.004819 • R 1 450.43 124.57 124.566 3.6420 0.114620 • NR 1 823.43 823.43 823.432 24.0752 0.004449 • Error 5 171.01 171.01 34.202 • Total 7 1444.88

  19. General Regression Analysis: X6 versus R, NR   • Regression Equation • X6 = -0.609787 + 0.400043 R + 0.183717 NR  • Coefficients  • Term Coef SE Coef T P 95% CI • Constant -0.609787 7.05776 -0.08640 0.935 (-18.7523, 17.5328) • R 0.400043 0.40211 0.99485 0.365 ( -0.6336, 1.4337) • NR 0.183717 0.08939 2.05519 0.095 ( -0.0461, 0.4135) • Summary of Model • S = 6.34460 R-Sq = 52.92% R-Sq(adj) = 34.09% • PRESS = 554.867 R-Sq(pred) = -29.79% • Analysis of Variance • Source DF Seq SS Adj SS Adj MS F P • Regression 2 226.231 226.231 113.115 2.81004 0.152091 • R 1 56.206 39.840 39.840 0.98972 0.365488 • NR 1 170.025 170.025 170.025 4.22380 0.095013 • Error 5 201.269 201.269 40.254 • Total 7 427.500

  20. General Regression Analysis: X7 versus R, NR • Regression Equation • X7 = -0.475285 + 0.0450222 R + 0.00546112 NR  • Coefficients  • Term Coef SE Coef T P 95% CI • Constant -0.475285 0.253513 -1.87479 0.120 (-1.12696, 0.176392) • R 0.045022 0.014444 3.11705 0.026 ( 0.00789, 0.082151) • NR 0.005461 0.003211 1.70079 0.150 (-0.00279, 0.013715) • Summary of Model • S = 0.227896 R-Sq = 70.32% R-Sq(adj) = 58.45% • PRESS = 1.47961 R-Sq(pred) = -69.10% • Analysis of Variance • Source DF Seq SS Adj SS Adj MS F P • Regression 2 0.615316 0.615316 0.307658 5.92370 0.047984 • R 1 0.465079 0.504617 0.504617 9.71598 0.026340 • NR 1 0.150237 0.150237 0.150237 2.89269 0.149724 • Error 5 0.259684 0.259684 0.051937 • Total 7 0.875000

  21. INTERPRETATION OF Y-INTERCEP AND SLOPE COEFFICIENTS

  22. INTERPRETATION OF THE COEFFCIENT OF MULTIPLE DETERMINATION • R2 = proportion of variation in the dependent variable ŷ that is explained by variation in the independent variables Xί. When R2 is close to 1, it is an indication that the model is a good fit to the data.

  23. INTERPRETATION OF THE COEFFICIENT OF CORRELATION • The correlation coefficient is a number that range from -1 to +1. Positive values indicate a relationship between X and Y variables such that a values X increases, values for Y also increase

  24. F-TEST HYPOTHESIS • Ho : β1…..β10 = 0 • No linear relationship between the dependent variable and the independent variables. • Ha : β1 ≠ 0 • Linear relationship between the dependent variable and the independent variables.

  25. Reject Ho at level of significance if F (model) > Fα, otherwisedo not reject Ho. Using α= 0.05 level of significance to find the critical value of the F distribution with ( 2/5)

  26. t-TEST • Ho : β1 = 0 versus Ha : β1 ≠ 0 • If we reject Ho at the 0.05 level , we can conclude that X1 is significantly related to the dependent variable ŷ.

  27. CONCLUSIONS 1. The TEAS preparation course is significantly effective. 2. For the dependent variable: • X3 (50-59%): Higher incidence of No Review (12.99%) • X4 (60-69%): Higher incidence of No Review (14.72%) • X5 (70-79%): Higher incidence of Review (70.73%) • X6 (80-89%): Higher incidence of Review (40.00%) • X7 (90-100%): Higher incidence of Review (4.50 %) • We can conclude that those students that take the students that take the TEAS preparation course at DMC achieve the best scores in the TEAS test. 2. All Models (Regression) explain above 70% of the total of the variation in predicting the scores of the TEAS test takers.

  28. 3. The Correlation Coefficient indicates a strong positive correlation, meaning that any increase in each interval depends on the increase of Review and No Review students that take the TEAS test. • F-test: we reject Ho, concluding that at least ONE on the independent variable is significant. • The t-test shows: That there is a strong evidence that Review and No Review are significantly related with X3; X5; X6 and X7. There is a strong evidence that No Review is significantly related with X4. There is no evidence that Review be significantly related with X4.

  29. RECOMMENDATIONS • Continue offering the program to prospective students. • Offer the program to students that did not pass the TEAS and did not took the preparation course offered at DMC. • Implement a system that allows the flow of information between admissions departments and the coordination of the program (enrollment lists, attendance, etc.) • Regulate the enrollment of students to fixed start terms to be able to control as much as possible the appointments for the TEAS test. • We suggest that the students have a priority date to take the TEAS after finishing their preparation. • To perform a prospective study to analyze the relationship between Review and No Review students, their academic trajectory and the results at NCLEX.

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