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Instructor: Dr. Brian G. Smith |
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Office: Lommen 214 G |
Phone: 218 477-5890 |
Email: smithb@mnstate.edu |
Office Hours: Monday and Wednesday -- 10:00am
-12:00pm & 1:00pm - 4:00pm |
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Nature of the Course: |
This course is designed to help students acquire
the necessary statistical skills needed to conduct and be
critical consumers of scientific educational research. It is
a course
aimed at producing careful and accurate researchers as well
as astute readers of professional manuscripts and articles
from
a wide variety of educational settings. The basic areas to
be covered in this course will include measurement and descriptive
statistics, frequency distributions, measure of central tendency,
measures of dispersion, standard normal distributions, and
standard
scores. The more advanced topics will include correlation,
regression, hypothesis testing, “t” tests, and analysis of
variance (ANOVA)
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Structure of the Course: |
This is a distance education/online course; most of the material and assessment
is on line, but some aspects of the course will require a visit
to the mailbox. As an online course,
it is possible to take advantage of technology and
create a
learning
environment
that allows for variability
among students while efficiently covering all the material.
The lessons are set up to be completed on a weekly basis-one
for each week of a winter/spring semester.
Note: The constructed response quizzes set up by subject area, like Counseling/Student Affairs, or Nursing, are intended to be Homework only. In order for you to see my feedback for each question, I must have you submit it for grading. This resulting "grade" is not downloaded anywhere else. It will NOT count toward your final grade. Only the lesson quizzes, which are multiple choice, count toward your final grade. You may take the lesson quizzes twice, the highest score will be recorded.
The primary advantage of the course is that you may
proceed at your own pace in your chosen location up to
the midterm and the final.
Midterm
and
final assessments must done on a print out of the emailed exams since it is extremely cumbersome to "show all of your math work" in a word processing program. When a student has completed the required lessons to
take the midterm or final exams, they will be given an email
by the instructor with the files attached.
Secondly, this course contains multiple options for the same
material presented in ways relevant to the area of study of
most of the students. Each lesson contains four different
versions of homework: Counseling and Student Affairs; Education
Leadership; and Special Education. Each version uses
separate samples of homework relevant to that area of study
throughout the course. Any student may may do the assignments
from any area. It is recommended to try more than one area
prior to
taking
the lesson final quiz. |
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Required
Text: |
Statistics for the Behavioral Sciences,
6th Ed., Gravetter, Frederick & Wallnau, Larry;
Thomson/Wadsworth Publishers, Belmont CA.
ISBN:0-534-60246-0
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CONCEPTUAL FRAMEWORK OF THE MSUM TEACHER
EDUCATION UNIT
MSUM candidates are professionals who are knowledgeable,
reflective, humanistic, and creative.
Knowledgeable: MSUM candidates display competence in their
subject matter, built upon a strong grounding in liberal
studies. MSUM
candidates understand the principles of learning, assessment
and technology. They understand and apply legal and ethical
considerations to all aspects of their work. MSUM candidates
are able to integrate
theory and practice, and view learning as an active process.
MSUM candidates demonstrate the ability to model connections
between philosophical foundations and best practices in
the field. As life-long learners, MSUM candidates engage in
research
and
complex thinking. They design opportunities for others
to seek knowledge and to understand themselves as members of
the world
community.
Reflective: MSUM candidates engage in thoughtful analysis
of the meaning and significance of their actions, decisions,
and
results with regard to their work in order to assess
progress in meeting this guiding principle. It is through this
reflective
process that candidates improve instruction, implement
new ideas, abandon ineffective methodologies, and enhance
learning
outcomes
for their students. MSUM candidates are skilled at analyzing
their teaching from a variety of perspectives and identifying
connections between teaching strategies and student learning.
In addition, candidates utilize a variety of techniques
to question their procedures and consider alternatives
for instruction
and
student growth. MSUM candidates recognize learning, motivational,
and developmental variables and relate those dimensions
to their teaching practices. Finally, MSUM candidates
bring a questioning
spirit to received wisdom and conventional practice when
needed.
Humanistic: MSUM candidates value the personal worth
of each individual. This is based on a belief in people's
potential
and innate ability to develop to their fullest. MSUM
candidates'
actions are grounded in knowledge of different cultural
and ethnic
groups within the world community, and in knowledge
of the influence of culture and history, ethnicity, language,
gender
and socio-economics
on one's life. This knowledge base informs candidates'
decision-making as they create environments that promote
freedom, compassion,
and success for all learners. MSUM candidates are fair-minded
in their interactions with others, as well as sensitive
to and accepting of individual differences. Further,
MSUM candidates
have an understanding of aesthetics and the diversity
that is
part of the human experience and will incorporate this
knowledge into their work. MSUM candidates recognize
and accommodate
a variety of linguistic and nonlinguistic interpersonal
skills in their actions with others. MSUM candidates
foster resiliency
in the students with whom they work and model these
qualities
in their own work.
Creative: MSUM candidates understand the powerful resources
of the arts and sciences and use their knowledge
of these areas
to bring the best of their imaginative and creative
acts into the classroom. MSUM candidates recognize
the important
role creativity
plays in the design of instruction and classroom
environment. They will, for themselves and for their students,
meet
new situations with resourcefulness, excitement and
curiosity, with an investigative
attitude, and with the ability to pose, seek and
design solutions
to problems. MSUM candidates are cognizant of the
aesthetic elements of the world and draw on that knowledge
to
make curricular decisions
designed to help students not only learn about aesthetics,
but to also learn how to think about the world at large. |
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Graduate Expectations:
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It is expected that this course
will challenge the participant to expand their present and
past experiences in the field of education to include a scientific
approach to their field. This course should build on and be
integrated into the program courses and field research of each
participant’s advanced degree program. A scientific approach
to research is fairly rigid with specific procedures designed
to investigate professional questions that grow from practitioner
observations. It is this inquisitiveness that will be maximized
in this course. Prior knowledge of statistics is not necessary.
An open mind is necessary.
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Course Objectives:
The curriculum and methods of instruction are
carefully selected to facilitate the acquisition of the following
learning objectives:
- Understand the basic statistical tools
that are commonly used in educational research.
- Know the appropriate methods for analyzing
statistical data.
- Recognize situations in which parametric
or nonparametric tests should be applied.
- Know how to conduct some specific parametric
and nonparametric tests.
- Be able to employ statistics in order to
answer specific research questions.
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Grading: |
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Quizzes |
20% |
Midterm |
40% |
Final Exam |
40% |
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Special Accommodations:
Special accommodations can be made for students who have disabilities that represent
a barrier to full participation in this course. If you think you may have a
disability, please contact the instructor at your convenience for consultation.
Keep in mind, however, that this is an on line course, and accomodations may
be limited. This course is also offered in a regular
classroom setting.
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Course Outline:
Lesson
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Topic
of Study
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Readings
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Objectives
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1
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Intro, Why Stats, Why Ed Research |
Chapter 1 |
* Understand what is Statistics.
* Understand why Statistics are necessary. |
2
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Basic Concepts and Symbols in Stats |
Chapter 1 |
* Understand the science of Statistics.
* Define populations and samples.
* Describe various sampling methods.
* Detect biases in samples. |
3
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Ethical issues in Stats and Research |
Web Based |
* Understand the ethical issues involved in statistics
and research.
* Critically examine existing research. |
4
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Freq. Dist., %tile ranks, graphing |
Chapter 2 |
* Create frequency distributions of grouped and ungrouped
scores.
* Present frequency distributions graphically.
* Analyze shapes of frequency distributions.
* Calculate percentiles and percentile ranks |
5
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Measures of Central Tendency |
Chapter 3 |
* Calculate the mode, median and mean of a sample.
* Compare the mode, median and mean of a sample.
* Draw conclusions about a sample from comparisons of the mode, median,
and mean. |
6
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Measures of Variability |
Chapter 4 |
* Calculate various range measures of a sample.
* Calculate the Standard Deviation of a sample.
* Calculate the Variance of a sample.
* Draw conclusions about a sample based on measures of variability. |
7
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Normal Curve, Standard Scores |
Chapter 5 |
* Understand the concept of a normal distribution.
* Draw and label a standard normal curve.
* Calculate a z-score.
* Calculate the percentage of scores above or below a given score. |
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Midterm
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On Campus |
8
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Correlation |
Chapter 16 |
* Draw scatterplots.
* Discuss the relationship between 2 variables based on the scatterplots.
* Calculate the Pearson Correlation Coefficient (Pearson r) for 2 variables.
* Test the statistical significance of the Pearson r.
* Report the results of a correlational study in laymanís terms.
* Calculate the Spearman rank-order correlation coefficient for curvilinear
relationships. |
9
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Regression |
Chapter 17 |
* Plot a regression line.
* Predict scores from a regression line.
* Calculate the amount of error in a prediction from a regression line.
* Discuss how the concept of regression toward the line affects predicted
scores. |
10
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Inferential Statistics |
Chapter 7 |
* Calculate the standard error of the mean.
* Understand the difference between mathematical difference and statistically
significant difference between means.
* Use the z-test to test a hypothesis |
11
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One sample T- Tests and Confidence Intervals |
Chapter 9 |
* Use a one sample t-test for testing a hypothesis.
* Report findings from a t-test in an appropriate format.
* Construct confidence intervals for a population mean.
* Interpret t-test results in a clear and concise manor. |
12
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Two group T- Tests |
Chapter 10 |
* Describe the basic research process.
* Use a two sample t-test for hypothesis testing.
* Understand the concept of power in statistics.
* Understand the difference between Type I and Type II errors. |
13
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One factor ANOVA (between subjects) |
Chapter 13 |
* One factor ANOVA between subjects |
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Final Exam |
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On Campus |
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This is
meant as a roadmap for the course. Changes may be made without
notice. |
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