SBI listserv participants,
We are happy to announce three new posts for you to enjoy:
- "Teaching computation as an argument for simulation-based inference
<https://www.causeweb.org/sbi/?p=971>" by Mine Cetinkaya-Rundel in our
series on 'Why use simulated based methods?"
- "Reflections after two years of simulation-based inference in AP
statistics <https://www.causeweb.org/sbi/?p=954>" by Andrew Walter in our
series on 'Incorporating simulation-based methods in the HS classroom"
- "Using simulation-based methods in New Zealand
<https://www.causeweb.org/sbi/?p=976>" by Stephanie Budgett in our new
series on "Simulation-based methods around the world"
We hope that these posts will challenge and encourage you. These posts and
more are available at http://www.causeweb.org/sbi
Feel free to continue to suggest other potential topics for the blog, post
your questions/comments directly to the blog and/or send your thoughts
using this listserv.
If you aren't aware of it already, encourage your students with excellent
class projects to consider submitting them to the USPROC competition which
has prizes for all levels of student projects (intro stat and beyond; see
www.causeweb.org/usproc for details)
Nathan
--
Nathan Tintle, Ph.D.
Associate Professor of Statistics and Dept. Chair
Director for Research and Scholarship
Dordt College
Sioux Center, IA 51250
nathan.tintle(a)dordt.edu
Phone: (712) 722-6264
Office: SB1612
Statistics education colleagues,
We currently have two introductory stats courses here at Central College.
* Applied Statistics (MATH 215) is intended for more mathematically/technically mature/advanced students. We use Rossman and Chance's ISCAM book, and students learn how to use Minitab to do statistical tests and intervals.
* Intro to Statistics (MATH 105) is intended for students who are not as sophisticated mathematically/technically. We use Tintle's Introduction to Statistical Investiations book, and students use the accompanying applets to do much of the work for them.
We are struggling with finding an effective prerequisite to use to put students in these two courses. Does anyone have ideas?
The biggest difference between the two courses is how fast and how deep we can go with the material. In Applied Stats, we go faster and make some deeper connections with the material. We also expect that students can fill in some of the gaps as we go along. But in Intro to Stats, we go slower and spend more time filling in gaps and making connections for the students.
We are struggling with finding an effective prerequisite to use to put students in these two courses. In particular, we'd like to have an enforceable prerequisite for each course that would keep good students from just taking the easy road with Intro to Stats. Does anyone have ideas?
Currently, we simply use math placement results to decide this. Students placing at or above Calc I or having completed (at least) Precalculus are not eligible to enroll in MATH 105. However, as strange as this seems, our current registration system cannot check/enforce this prereq, so any student can actually enroll in either course. So we end up having to police these criteria ourselves--usually removing students from Intro to Stats and encouraging them to enroll in Applied Stats. (Not a happy job...)
Lately, we have begun to wonder if using a math placement result that is based on a scale from College Algebra to Multivariable Calculus is really the best way to measure what will make a student successful in a particular stats class.
We have done some analysis of a number of different possible predictors of student success, and the one that seemed to be the strongest was cumulative GPA. A GPA of 2.7 seemed to be the low end for students who successfully completed Applied Stats. So we proposed a pre-req of GPA <= 2.7 for Intro to Stats and GPA >= 2.7 for Applied Stats, but our Registrar doesn't like it and has asked us to consider a different pre-req.
We've talked a lot about this as a department, and we really don't know where to go.
If anyone out there with a similar situation of having two intro courses has an easy, effective, and enforceable way to determine student placement, then I would enjoy hearing from you. Please just reply directly to me and not to the SBI mailing list.
Thanks!
Mark
Dr. MARK A. MILLS
Professor of Mathematics | Central College
812 University Street | Campus Box 06 | Pella, Iowa 50219
Mark-
Thanks for your email. Here's what we're doing here at Dordt---but I, too,
would love to hear more.
1. We have two intro courses. The AP stat equivalent which uses the ISI
book you are using and another 'accelerated' intro stats which does the ISI
book in half a semester and then does a half semester of multivariable
applied statistics.
2. Our placement criteria for the second course is (a) taken calculus (even
though we don't use any), or (b) prior experience with statistics (e.g., AP
statistics or some other college or HS course)
3. We do have some students take the 'easier' intro course instead of the
longer one, but not that many so it's not an issue. When we get overbooked
in the regular intro course these better students are the first to go... :)
Again, curious what others are doing as well.
Nathan
On Fri, Dec 4, 2015 at 2:55 PM, Mark Mills <MillsM(a)central.edu> wrote:
> Statistics education colleagues,
>
>
>
> We currently have two introductory stats courses here at Central College.
>
> - Applied Statistics (MATH 215) is intended for more mathematically/
> technically mature/advanced students. We use Rossman and Chance's
> ISCAM book, and students learn how to use Minitab to do statistical tests
> and intervals.
> - Intro to Statistics (MATH 105) is intended for students who are not
> as sophisticated mathematically/technically. We use Tintle's *Introduction
> to Statistical Investiations* book, and students use the accompanying
> applets to do much of the work for them.
>
> We are struggling with finding an effective prerequisite to use to put
> students in these two courses. Does anyone have ideas?
>
>
>
> The biggest difference between the two courses is how fast and how deep we
> can go with the material. In Applied Stats, we go faster and make some
> deeper connections with the material. We also expect that students can
> fill in some of the gaps as we go along. But in Intro to Stats, we go
> slower and spend more time filling in gaps and making connections for the
> students.
>
>
>
> We are struggling with finding an effective prerequisite to use to put
> students in these two courses. In particular, we'd like to have an
> enforceable prerequisite for each course that would keep good students from
> just taking the easy road with Intro to Stats. Does anyone have ideas?
>
>
>
> Currently, we simply use math placement results to decide this. Students
> placing at or above Calc I or having completed (at least) Precalculus are
> not eligible to enroll in MATH 105. However, as strange as this seems, our
> current registration system cannot check/enforce this prereq, so any
> student can actually enroll in either course. So we end up having to
> police these criteria ourselves--usually removing students from Intro to
> Stats and encouraging them to enroll in Applied Stats. (Not a happy job...)
>
>
>
> Lately, we have begun to wonder if using a math placement result that is
> based on a scale from College Algebra to Multivariable Calculus is really
> the best way to measure what will make a student successful in a particular
> stats class.
>
>
>
> We have done some analysis of a number of different possible predictors of
> student success, and the one that seemed to be the strongest was cumulative
> GPA. A GPA of 2.7 seemed to be the low end for students who successfully
> completed Applied Stats. So we proposed a pre-req of GPA <= 2.7 for Intro
> to Stats and GPA >= 2.7 for Applied Stats, but our Registrar doesn't like
> it and has asked us to consider a different pre-req.
>
>
>
> We've talked a lot about this as a department, and we really don't know
> where to go.
>
>
>
> If anyone out there with a similar situation of having two intro courses
> has an easy, effective, and enforceable way to determine student placement,
> then I would enjoy hearing from you. Please just reply directly to me and
> not to the SBI mailing list.
>
>
>
> Thanks!
>
>
>
> Mark
>
>
>
> *Dr. MARK A.** MILLS*
> Professor of Mathematics | Central College
> 812 University Street | Campus Box 06 | Pella, Iowa 50219
>
--
Nathan Tintle, Ph.D.
Associate Professor of Statistics and Dept. Chair
Director for Research and Scholarship
Dordt College
Sioux Center, IA 51250
nathan.tintle(a)dordt.edu
Phone: (712) 722-6264
Office: SB1612
