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Elementary Statistics: STEM vs. nonSTEM Dave Usinski: [email protected] Lynn Meslinsky: [email protected]

Elementary Statistics: STEM vs. nonSTEM

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Elementary Statistics: STEM vs. nonSTEM. Dave Usinski : [email protected] Lynn Meslinsky : [email protected]. Our Question. What are the best predictors of success in Statistics and how can we use these to determine whether this course should be STEM or nonSTEM?. Overview. - PowerPoint PPT Presentation

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Page 1: Elementary Statistics: STEM vs. nonSTEM

Elementary Statistics:STEM vs. nonSTEM

Dave Usinski: [email protected] Meslinsky: [email protected]

Page 2: Elementary Statistics: STEM vs. nonSTEM

Our Question

What are the best predictors of success in Statistics and how can we use these to determine whether this course should be STEM or nonSTEM?

Page 3: Elementary Statistics: STEM vs. nonSTEM
Page 4: Elementary Statistics: STEM vs. nonSTEM

Overview

• Revisit MT112/MT116 non-STEM Pathway– Has it been successful?

• Incorporate Placement Data• Kendall’s Tau B (rows = columns) and C

– Contingency table rank correlation coefficients between numeric vs ordinal and ordinal vs ordinal

• Binary Logistic Regression Analysis– Predicting future course success

Page 5: Elementary Statistics: STEM vs. nonSTEM

We looked at our other non-STEM courses

How did lessening the algebra prerequisite requirements affect the course success rates?

Page 6: Elementary Statistics: STEM vs. nonSTEM

Overall College Fall Headcount, Number of Students Passing MT112/116 in Fall,

Number of Students Passing MT112/116 in entire Year

02/FA 03/FA 04/FA 05/FA 06/FA 07/FA 08/FA 09/FA 10/FA 11/FA 12/FA0

2000

4000

6000

8000

10000

12000

14000

16000

Student Totals

Fall HeadcountFall passing MT112/MT116Year passing MT112/MT116St

uden

ts

Page 7: Elementary Statistics: STEM vs. nonSTEM

Same as Previous except as Percent Change from Fall 2002

02/FA 03/FA 04/FA 05/FA 06/FA 07/FA 08/FA 09/FA 10/FA 11/FA 12/FA-20.00%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

Percent Change based on Fall 2002

% change Fall Headcount% change Fall Passing MT112/MT116% change Yearly passing MT112/MT116

Perc

ent C

hang

e

Page 8: Elementary Statistics: STEM vs. nonSTEM

We looked at the last course taken prior to taking Statistics

Which courses had the best predictive value in terms of success in Statistics?

Page 9: Elementary Statistics: STEM vs. nonSTEM

We also compared placement results in reading to placement

results in algebra/math.

Which Accuplacer or SAT result had a higher correlation to success with Statistics?

Page 10: Elementary Statistics: STEM vs. nonSTEM

Correlation CoefficientDescribing Strength of Association

Characterizations

>.5 high association

.3 to .5 moderate association

.1 to .3 low association

0 to .1 little if any association

Page 11: Elementary Statistics: STEM vs. nonSTEM

MT143 (Statistics) PredictorsPredictor Kendall’s Tau

B or CCorrelation Coefficient95% Confidence Interval

AccuPlacer Reading (55 to 110)

C n=953 0.135 (0.089 to 0.181)

AccuPlacer Algebra (55-110) C n=793 0.107 (0.059 to 0.156)SAT M (300-700) C n=2722 0.146 (0.120 to 0.172)SAT V (300-700) C n=2675 0.091 (0.064 to 0.119)MT013 (Elementary Algebra) B n=707 0.265 (0.206 to 0.325)MT112 (Survey of Math) B n=931 0.328 (0.278 to 0.378)MT125 (College Alg. & Trig I) B n=2156 0.380 (0.349 to 0.412)MT126 (College Alg. & Trig II)

B n=690 0.360 (0.305 to 0.415)

MT175 (Survey of Calculus) B n=735 0.340 (0.286 to 0.395)

Page 12: Elementary Statistics: STEM vs. nonSTEM

MT175

MT126

MT125

MT112

MT013

SAT M

SAT V

AP Alg

AP Reading

0.450.400.350.300.250.200.150.100.05Data

Boxplot of AP Reading, AP Alg, SAT V, SAT M, MT013, MT112, MT125, ...

Page 13: Elementary Statistics: STEM vs. nonSTEM

43210

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

grade

Y-Da

ta

0.6

>=B- Probability>=C+ Probability>=C Probability>=C- Probability

Variable

MT013 grade vs MT143 grade

Page 14: Elementary Statistics: STEM vs. nonSTEM

43210

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

grade

Y-Da

ta

0.6

>=B- Prob>=C+ Prob>=C Prob>=C- Prob

Variable

MT112 grade vs MT143 grade

Page 15: Elementary Statistics: STEM vs. nonSTEM

Conclusion

There is little difference in the predictive value of Developmental Algebra vs. Liberal Arts Math in determining a grade in Statistics.

Page 16: Elementary Statistics: STEM vs. nonSTEM

120100806040200

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

score AP Read

Y-Da

ta

0.6

0.75

>=B- Prob APREAD>=C+ Prob APREAD>=C Prob APREAD>=C- Prob APREAD

Variable

AccuPlacer Read vs MT143 Prob

Page 17: Elementary Statistics: STEM vs. nonSTEM

120100806040200

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

score AP Alg

Y-Da

ta

0.6

0.75

>=B- Prob APALG>=C+ Prob APALG>=C Prob APALG>=C- Prob APALG

Variable

AccuPlacer Algebra vs MT143 Prob

Page 18: Elementary Statistics: STEM vs. nonSTEM

Conclusion

An Accuplacer reading score of about 63 is needed to have a 60% chance of C or better in Statistics while an Accuplacer Algebra Score of about 30 will do the same thing.

Page 19: Elementary Statistics: STEM vs. nonSTEM

800700600500400300200

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

score SAT M

Y-Da

ta

0.6

0.75

>=B- Prob SATM>=C+ Prob SATM>=C Prob SATM>=C- Prob SATM

Variable

SAT MATH vs MT143 Prob

Page 20: Elementary Statistics: STEM vs. nonSTEM

800700600500400300200

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

score SAT E

Y-Da

ta

0.6

0.75

>=B- Prob SATE>=C+ Prob SATE>=C Prob SATE>=C- Prob SATE

Variable

SAT Eng vs MT143 Prob

Page 21: Elementary Statistics: STEM vs. nonSTEM

Conclusion

SAT score showed the opposite! A higher SAT Math, 270, was needed to show 60% chance of C or better in Statistics while only a SAT Verbal had no impact.

Page 22: Elementary Statistics: STEM vs. nonSTEM

Questions?

• Dave Usinski: [email protected]• Lynn Meslinsky: [email protected]