Introduction to the Statistics - Syllabus | MATH 2400 | Assignments Statistics

Syllabus: Introduction to Statistics

Course: Math 2400 (3 hours)

Instructor: Robb Sinn

Office: NOC 221

Phone: 706-864-1676

Email: rsinn@ngcsu.edu

Textbook: All students are required to purchase the e-book version of Moore’s The Basic Practice of

Statistics. The product is called StatsPortal, is available in the NGCSU bookstore for ~ $67, and includes

extensive resources including online tutoring, animations, video clips and much more. The course will

include a online HW/Quiz module through StatsPortal. You MUST purchase this online product. You do

NOT need a traditional textbook for this course.

Prerequisite: Three hours of college mathematics. A student will not be allowed credit for MATH 2400

after completing MATH 3300 with a grade of "C" or above.

Catalog Description: A noncalculus introduction to descriptive and inferential statistics. Topics include

graphical and numerical methods of describing data, hypothesis testing, linear regression and correlation,

the normal distribution, and estimation.

Course Objectives: After completion of the course the student will be able to:

Distinguish the use of descriptive statistics from the use of inferential statistics.

Distinguish qualitative data from quantitative data.

Construct a frequency distribution and relative frequency distribution for a given set of data.

Construct a histogram polygon for a given set of data.

Compute and provide a qualitative interpretation for the mode, median, and mean of a given set of

data.

Compute and provide a qualitative interpretation for the range and standard deviation of a given set of

data.

Find the proportion of data between two given values for a normal distribution.

Find the value of a given percentile for a normal distribution.

Compare scores from two different normal distributions using standard scores.

Construct a scatterplot for a given set of paired data.

Compute and provide a qualitative interpretation for the correlation coefficient of a given set of paired

data.

Compute the slope and Y-intercept of the least squares prediction line and use the equation for the least

squares prediction line to predict the value of one variable from the value of the other.

Compute and provide a qualitative interpretation for the standard error of prediction of a given set of

paired data.

Provide a strategy for collecting a random sample from a given population.

Compute and provide a qualitative interpretation for the mean of all sample means and the standard

error of the mean for a given population and sample size.

Perform the six steps of hypothesis testing for a z-test, t-test, t-test for two independent samples, and t-

test for two matched samples.

Distinguish Type I errors from Type II errors and provide a strategy for minimizing the chance of one

or the other occurring.

Find and provide a qualitative interpretation for a confidence interval.

Perform the six steps of hypothesis testing for a chi-square test.

Determine the appropriate hypothesis test to use in a given situation.

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Syllabus: Introduction to Statistics

Course: Math 2400 (3 hours) Instructor: Robb Sinn Office: NOC 221 Phone: 706-864- Email: rsinn@ngcsu.edu Textbook : All students are required to purchase the e-book version of Moore’s The Basic Practice of Statistics. The product is called StatsPortal, is available in the NGCSU bookstore for ~ $67, and includes extensive resources including online tutoring, animations, video clips and much more. The course will include a online HW/Quiz module through StatsPortal. You MUST purchase this online product. You do NOT need a traditional textbook for this course. Prerequisite : Three hours of college mathematics. A student will not be allowed credit for MATH 2400 after completing MATH 3300 with a grade of "C" or above. Catalog Description : A noncalculus introduction to descriptive and inferential statistics. Topics include graphical and numerical methods of describing data, hypothesis testing, linear regression and correlation, the normal distribution, and estimation. Course Objectives : After completion of the course the student will be able to:  Distinguish the use of descriptive statistics from the use of inferential statistics.  Distinguish qualitative data from quantitative data.  Construct a frequency distribution and relative frequency distribution for a given set of data.  Construct a histogram polygon for a given set of data.  Compute and provide a qualitative interpretation for the mode, median, and mean of a given set of data.  Compute and provide a qualitative interpretation for the range and standard deviation of a given set of data.  Find the proportion of data between two given values for a normal distribution.  Find the value of a given percentile for a normal distribution.  Compare scores from two different normal distributions using standard scores.  Construct a scatterplot for a given set of paired data.  Compute and provide a qualitative interpretation for the correlation coefficient of a given set of paired data.  Compute the slope and Y-intercept of the least squares prediction line and use the equation for the least squares prediction line to predict the value of one variable from the value of the other.  Compute and provide a qualitative interpretation for the standard error of prediction of a given set of paired data.  Provide a strategy for collecting a random sample from a given population.  Compute and provide a qualitative interpretation for the mean of all sample means and the standard error of the mean for a given population and sample size.  Perform the six steps of hypothesis testing for a z-test, t-test, t-test for two independent samples, and t- test for two matched samples.  Distinguish Type I errors from Type II errors and provide a strategy for minimizing the chance of one or the other occurring.  Find and provide a qualitative interpretation for a confidence interval.  Perform the six steps of hypothesis testing for a chi-square test.  Determine the appropriate hypothesis test to use in a given situation.

Grading: There are 4 components of the students’ course average: test average on 2 in-class exams, (35%), two projects (30%), final exam (20%) and HW/Quiz/Participation (15%). Participation is expected and includes (among other things) class attendance, iClicker student response questions, completing the StatsPortal homework problems, bringing the required calculator to class each day, staying awake in class, and joining class discussions. No test scores are dropped, but a test score may be replaced with (a portion of) the exam grade if this improves the students’ overall average. Grading Scale: A 90% - B 80% - 89% C 70% - 79% D 60% - 69% Best Contact: Email is by far the best way to reach me. I check my email almost hourly, even when away from work. You may call (706-864-1676) during office hours or leave a message with the department secretary any time between 8 am and 5 pm, Monday - Friday. I do give out my home phone and/or cell number, but I don’t post them on the internet (intentionally). Office Hours. Tues/Thurs 11 – 12:30, Wed 11 - 12 & 1:30 - 3:30 PM Methods of Instruction : The methods of instruction are determined by the instructor; however, the instructor is expected to use a variety of methods. These methods may include, but are not limited to lecture; problem-solving sessions with informal assessment by the student or instructor; discussion; group projects; timely feedback from test, quiz, or project results (formative assessment); question and answer; computer or calculator based explorations; and student presentations. Students will be encouraged to assess and monitor their own problem-solving process to determine when an error has been made or a new strategy should be used. Metacognitive Model and Teacher Education Program Competencies: The NGCSU Secondary Mathematics Education Program prepares teachers to assume within the school community the roles of Decision-Maker, Facilitator, and Leader as identified in the metacognitive model. Twelve Teacher Education Program competencies reflecting the model are aligned to a specific role. Overlap into more than one role and mathematics course may occur. Current research and professional standards identify these competencies as important for effective teaching (NBPTS and ASCD Framework). Decision-Maker Facilitator Leader Assessment Individual Differences Ethical Perspectives Planning Subject Matter Knowledge Reflection/Metacognition Problem Solver Communication Professional Leadership Methods, Materials, Resources Classroom Management Research & Evaluation Evaluation Methods : Formative assessment will be in the form of written tests and/or short quizzes and summative assessment will be in the form of a final examination. Special projects and daily grades may be used at the discretion of the instructor. Course Content :

Graphical and numerical methods of describing data.
The normal distribution.
Correlation and linear regression.
Hypothesis testing.
Estimation.

Make-Up Work. No late assignments are accepted. Make-up tests and quizzes will not be allowed. The lowest quiz grade is dropped, but no additional quizzes will be dropped no matter the circumstances. If a student misses a test and has a valid, properly-documented reason, the exam grade may count in place of that test score. Attendance Policy. Attendance each day in class is mandatory. I take attendance about 2/3’s of the days class meets. If a student misses 5 or more class meetings without valid, extreme circumstances documented, he or she will be withdrawn from the class and assigned a grade of WF. If you must miss class for any reason, please notify me (rsinn@ngcsu.edu) before the absence. If an emergency arises, please notify me as quickly as is reasonably possible. Tardiness is not acceptable. Students who show up to class several minutes late may be marked absent for the period. There is an attendance bonus of 1% added to the final semester average for students who miss one or fewer class meetings. Exam Exemption Policy. I reward certain “valued behaviors” with eligibility for a final exam exemption. The valued behaviors for Stats 2400 are:  Perfect attendance, or nearly perfect attendance  Strong performance (95% or better) on “effort” assessments: StatsPortal and iClicker  Professional participation as team member during Linear Regression Project  A’s on both in-class tests, especially Test 2 I reserve the right to confer an exam exemption to anyone who demonstrates strong commitment to the valued behaviors. The following criteria guarantee a final exam exemption: an A average for both StatsPortal and iClicker portions together with either (a) perfect attendance, or (b) a 90% or better on both in-class tests. If you qualify for a final exam exemption and decide to take the final, the final exam grade cannot lower your semester average. Early Alert/Early Intervention Policy : NGCSU has implemented this new program. I will refer you to other persons/services at the university designed to help you achieve your academic goals. You will be expected to take advantage of the help offered to you. Class Evaluations : Class evaluations at NGCSU are now conducted on-line through Banner. Evaluation of the class is considered a component of the course and students will not be permitted to access their course grade until the evaluation has been completed. The evaluations will be accessible beginning one week prior to Final Exam week. Disabilities and Accommodations. North Georgia College & State University is committed to equal access to its programs, services and activities for people with disabilities. If you believe that you have a disability requiring an accommodation, reasonable prior notice needs to be given to the instructor and the Office of Student Disability Resources. In this case, contact Elizabeth McIntosh, Coordinator, Student Disability Resources at 122 Barnes Hall, 867-2782, emcintosh@ngcsu.edu.

Introduction to the Statistics - Syllabus | MATH 2400, Assignments of Statistics

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Download Introduction to the Statistics - Syllabus | MATH 2400 and more Assignments Statistics in PDF only on Docsity!

Syllabus: Introduction to Statistics