THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS. Fall 2013

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1 THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING 1 COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS Fall 2013 & Danice B. Greer, Ph.D., RN, BC Office BRB 1115 (903) Office Hours By Appointment

2 COURSE SCHEDULE NURS 5317 Fall Date Chapters Covered Reading (Gravetter & Wallnau)* Assignment for a grade 8/26 Ch. Introduction Ch. 1 Quiz 1 9/1 9/2 Ch. Frequency Distributions Ch. 2 Quiz 2 9/8 9/9 Ch. Central Tendency Ch. 3 Quiz 3 9/15 9/16 Ch. Variability Ch. 4 Quiz 4 9/22 Exam #1 (Chaps. 1-4) 9/22/2013 9/23 Ch. z-scores Ch. 5 Quiz 5 9/29 9/30 Ch. Probability Ch. 6 Quiz 6 10/6 10/7 Ch. Probability and Samples Ch. 7 Quiz 7 10/13 10/14 Ch. Introduction to hypothesis testing Ch. 8 Quiz 8 10/20 Exam #2 (Chaps. 5-8) 10/20/ /21 Ch. Introduction to the t statistic Ch. 9 Quiz 9 10/27 10/28 Ch. t-test for two independent samples Ch. 10 Quiz 10 11/3 11/4 Ch. t-test for two related samples Ch. 11 Quiz 11 11/10 Assignment due date **Every Sunday 11:59pm CST Exam #3 (Chaps. 9-11) 11/10/ /11 Ch. Estimation Ch. 12 Quiz 12 11/17 11/18 Ch. ANOVA Ch. 13 Quiz 13 11/24 11/25-12/1 Thanksgiving Break- ~No quiz or assignments due ~ 12/2 Ch. Correlation and Regression Ch. 15 Quiz 14 12/8 Exam #4 (Chaps. 12, 13, & 15) 12/8/2013 * All readings are required ** Assignments, quizzes, and exams will be due by 11:59 p.m. central time on the date shown. Availability of assignments can be found in Blackboard.

3 3 COURSE DESCRIPTION NURS 5317: Graduate Statistics for Health Professionals is a three credit graduate course with several goals that are intended to help students understand fundamental concepts and methods of statistics as applied to health related fields. The topics of this course include: introduction to basic concepts of descriptive and inferential statistics as they apply to health research; basic and intermediate concepts for testing statistical hypotheses, construction and interpretation of confidence intervals; and applying selected nonparametric techniques. Prerequisite: Undergraduate statistics course Course hours/credits: 3 hours COURSE OBJECTIVES By the end of the course, each student will be able to: 1. Demonstrate familiarity with statistical terminology and the purpose of statistics: When, how, and why they are used. 2. Organize data into regular or grouped frequency distribution tables, construct graphs, histograms, and polygons, and describe the shape of a distribution. 3. Define and compute measures of central tendency and variability including the mean, median, mode, variance, sum of squared deviations and standard deviation for both samples and populations. 4. Describe and understand the purpose for z-scores and the effects of standardizing a distribution through transforming raw scores, and demonstrate the process for transforming X values into z-scores and z-scores into X values. 5. Distinguish the link between z-scores, probability, frequency distributions, and inferential statistics. 6. Exhibit understanding the logic of hypothesis testing including the concepts of error (Type I and Type II), directional and non-directional hypothesis testing, effect size, Cohen s d and what it measures, power for a hypothesis test and factors that influence power. 7. List the assumptions that must be satisfied for parametric statistical tests. 8. Differentiate experimental situations for which an independent-measures t statistic, repeated-measures t statistic, or analysis of variance (ANOVA) is appropriate and the associated advantages and disadvantages of each design. 9. Recognize when post hoc tests are necessary and complete an analysis of variance using Tukey s HSD or the Scheffe post hoc test. 10. Report the results of an ANOVA using a summary table and an F-ratio, and interpret these reports when they appear in scientific literature. 11. Compute the Pearson correlation by the regular and z-score formulas, understand what aspect of a relationship Pearson correlation measures.

4 4 Required Textbook: 12. Understand the Spearman correlation and how it differs from the Pearson correlation in terms of the data it uses and the type of relationship it measures. 13. Calculate the linear regression equation for a set of data and evaluate the significance of the linear regression equation by computing the appropriate F-ratio. MATERIALS NEEDED Gravetter, F., & Wallnau, L. (2010). Essentials of Statistics for the Behavioral Sciences (7 th ed.). Belmont, CA: Thomson Wadsworth. ISBN-13: ISBN-10: x Internet: Students are expected to have and access to the Internet. The preferred browser is Internet Explorer. Using other browsers may cause problems with your use of Blackboard. Be sure to set your browsers according to the browser setting directions on the homepage of the course. Calculator: For the first two sections a hand-held calculator with the following functions will be beneficial: SQUARE ROOT, EXPONENTIAL FUNCTIONS, and some MEMORY CAPABILITIES. Although not required, having a calculator will help you double check your work. ASSIGNMENTS, EVALUATIONS, AND GRADING POLICY Quizzes: You will be responsible for taking a timed quiz on each of the chapters covered. These quizzes will be located on Blackboard. You may use your book and any notes you have including websites. However, these must be done independently and not with other students. You are required to complete all of the chapter quizzes. The quizzes will be automatically graded by Blackboard right after you take them. For the quizzes, you are allowed two attempts and your highest score will be counted. The timeframe and associated deadlines for each of the quizzes are provided below on the course schedule. Quizzes need to be completed by 11:59 p.m. on the day they are due. Exams: The student will earn a satisfactory grade on four exams. The format of the test will range from multiple-choice type of questions to essay type of questions. Exams will focus on concepts and computational applications. The online exams will be completed in the allotted timeframe as outlined in the course schedule and will be taken in accordance with the following policies: Exam Protocol (for the four exams, not for the chapter quizzes) 1. Exams must be taken in the allotted time period. 2. The exam will be timed. You will have three hours to complete it. 3. The exam must be taken in one sitting. You cannot do part of it and then come back to do the other part later. 4. Do not download or print out the test (or any quiz). 5. Do not distribute the exam, in any manner, to any other person. 6. Unless the exam is proctored, do not take the exam in the same room with another person. 7. Blackboard will monitor how you take the exam. Like quizzes, exams also need to be completed by 11:59 p.m. on the day they are due.

5 5 Readings: Assigned chapters must be completed as assigned for each instructional unit. Evaluation Methods: Exams (60%): Quizzes (40%): 60 total possible points for four exams at 15 points each. 40 total possible points (2.85 points for each of the 14 quizzes) Total (100%): 100 points possible CLASS POLICIES Attendance: The class will be organized through online Powerpoint lectures, demonstrations, discussions, and practice of information covered in the textbook and lecture. Questions are encouraged at any time and I encourage you to be active in this course. I also strongly encourage you to form and attach yourselves to a study group (as distance allows). Missed Quizzes and Exams: If an assessment is missed, the makeup quiz or exam will be conducted at my discretion. The student must arrange these exams, and the makeup should be completed prior to the next class period (or lesson) or as soon as possible. Course Structure and Schedules: With any online course, we will all have different schedules and work hours. Although online courses afford some flexibility to navigate individual schedules, the course calendar provides a structured sequence for learning. All learning chapters will be available but quizzes and exams are set by the course calendar dates and will only open up per the calendar. COLLEGE AND UNIVERSITY POLICIES Grading Policy for the College of Nursing and Health Sciences: A B C D F Below 60 Students Rights and Responsibilities To know and understand the policies that affect your rights and responsibilities as a student at UT Tyler, please follow this link: Grade Replacement/Forgiveness If you are repeating this course for a grade replacement, you must file an intent to receive grade forgiveness with the registrar by the 12th day of class. Failure to do so will result in both the original and repeated grade being used to calculate your overall grade point average. Undergraduates will receive grade forgiveness (grade replacement) for only three course repeats; graduates, for two course repeats during his/her career at UT Tyler.

6 6 State-Mandated Course Drop Policy Texas law prohibits a student who began college for the first time in Fall 2007 or thereafter from dropping more than six courses during their entire undergraduate career. This includes courses dropped at another 2-year or 4-year Texas public college or university. For purposes of this rule, a dropped course is any course that is dropped after the 12th day of class (See Schedule of Classes for the specific date). Exceptions to the 6-drop rule may be found in the catalog. Petitions for exemptions must be submitted to the Registrar's Office and must be accompanied by documentation of the extenuating circumstance. Please contact the Registrar's Office if you have any questions. Disability Services In accordance with federal law, a student requesting accommodation must provide documentation of his/her disability to the Disability Support Services counselor. If you have a disability, including a learning disability, for which you request an accommodation, please contact Ida MacDonald in the Disability Support Services office in UC 282, or call (903) Student Absence due to Religious Observance Students who anticipate being absent from class due to a religious observance are requested to inform the instructor of such absences by the second class meeting of the semester. Student Absence for University-Sponsored Events and Activities If you intend to be absent for a university-sponsored event or activity, you (or the event sponsor) must notify the instructor at least two weeks prior to the date of the planned absence. At that time the instructor will set a date and time when make-up assignments will be completed. Social Security and FERPA Statement: It is the policy of The University of Texas at Tyler to protect the confidential nature of social security numbers. The University has changed its computer programming so that all students have an identification number. The electronic transmission of grades (e.g., via ) risks violation of the Family Educational Rights and Privacy Act; grades will not be transmitted electronically. Emergency Exits and Evacuation (we re online, but in the event of face-to-face meetings): Everyone is required to exit the building when a fire alarm goes off. Follow your instructor s directions regarding the appropriate exit. If you require assistance during an evacuation, inform your instructor in the first week of class. Do not re-enter the building unless given permission by University Police, Fire department, or Fire Prevention Services. Note: The content of this syllabus is subject to change at the discretion of the faculty leaders according to current learning needs.

7 CONTENT OBJECTIVES 7 Note: Students will be required to read appropriate content, participate in discussion forums for clarification and discussion, and post assignments as directed. Lessons are organized according to the content for each week and include Powerpoint lectures, discussion forums, and quizzes each week. Additionally, exams will cover three to four instructional lessons and allocated to integrated content. Please refer to the annotated course schedule for weekly content. Lesson 1: Course Introduction, Introduction to Statistics Introduce the basic terminology that will be used in statistics Explain how statistical techniques fit into the general process of scientific research Introduce some of the notation that will be used throughout the course differentiation of populations and samples, descriptive versus inferential statistics, parametric versus nonparametric procedures, and parameters and statistics Lesson 2: Frequency Distributions and Tables, Graphs, and Distribution Shapes Introduce the concept of a frequency distribution as a descriptive statistical technique Describe how a frequency distribution can be presented in a regular or grouped table Describe how a frequency distribution can be presented in a graph Transformation of data into percentiles ranks and graphical description of frequencies using stem and leaf and box-and-whiskers displays Lesson 3: Measures of Central Tendency Introduce central tendency as a descriptive statistical procedure Introduce the three basic measures of central tendency: the mean, the median, and the mode Describe how measures of central tendency are related to the shape of a distribution Describe how central tendency is presented in research reports, including presentation in graphs Lesson 4: Variability Introduce the concepts of variability and describe its importance as a descriptive measure and component of inferential statistics Introduce the basic techniques for measuring and describing variability Demonstrate the properties of the standard deviation Demonstrate how the mean and standard deviation, working together, can provide a detailed description for a set of scores Lesson 5: z-scores Introduce z-scores as a method for describing exact locations in a distribution Demonstrate how raw scores (X values) are transformed into z-scores, and how to reverse the transformation Demonstrate the concept of standardizing a distribution by transforming all of the scores into z- scores Demonstrate how z-scores can be used to create a standardized distribution with any predetermined values for the mean and standard deviation. Lesson 6: Probability Introduce the concept of probability Demonstrate how the unit normal table can be used to find proportions of a normal distribution corresponding to any specific z-score location Demonstrate how the combination of z-scores and the unit normal table can be used to find probabilities on any score (X value) from a normal distribution, and how the table can be used to find the score corresponding to any specific proportion Demonstrate how probability will be used as part of the inferential statistics in future chapters

8 8 Lesson 7: The Distribution of Sample Means Introduce the distribution of sample means and identify its parameters Demonstrate how z-scores can be used to identify the location of a specific sample mean within the distribution of sample means Demonstrate how the unit normal table can be used to find probabilities for sample means Introduce the concept of standard error as an integral component of inferential statistics Lesson 8: Hypothesis Testing Introduce the statistical technique of hypothesis testing Introduce the concepts of null hypothesis, alpha level, and critical region Introduce the types of errors that can occur in a hypothesis test Demonstrate the differences between one-tailed and two-tailed tests Introduce the concept of effect size as a supplement to a hypothesis test Introduce the concept of power for a hypothesis test Lesson 9: Introduction to the t Statistic Introduce the t statistic as an alternative to the z-score hypothesis test Demonstrate the calculation of estimated standard error and the t statistic Introduce the t distributions and their relation to degrees of freedom Demonstrate the entire process of hypothesis testing with the t statistic Demonstrate the measurement of effect size for the t statistic Lesson 10: The t Test for Two Independent Samples Introduce the basic characteristics of an independent-measures (or between subjects) research design. Demonstrate the process of hypothesis testing with the independent-measures t statistic Introduce the assumption of homogeneity of variance Demonstrate the measurement of effect size for the independent-measures t Lesson 11: The t Test for Two Related Samples Introduce the basic characteristics of a repeated-measures (or within-subjects) research design Demonstrate the process of hypothesis testing with the repeated-measures t statistic Demonstrate the measurement of effect size for the repeated measures t Discuss the advantages and disadvantages of a repeated-measures design compared to an independent-measures design Lesson 12: Estimation Introduce the statistical technique of estimation as an alternative to a hypothesis test Demonstrate point and interval estimates for the single-sample t, the independent-measures t, and the repeated measures t Demonstrate how the width of a confidence interval is related to the sample size and the level of confidence Lesson 13: Analysis of Variance (ANOVA) Introduce the logical foundation for ANOVA Demonstrate the process of hypothesis testing with ANOVA Demonstrate the use of post hoc test to help interpret the results from an ANOVA Demonstrate the measurement of effect size for an ANOVA Demonstrate the relationship between ANOVA and the independent-measures t test for a study comparing exactly two samples or treatment conditions

9 Lesson 14: Correlation and Regression Introduce the concept of a correlation and what it measures Demonstrate the Pearson correlation to measure linear relationship Demonstrate the Spearman correlation to measure relationships for ordinal data Demonstrate the Point-Biserial Correlation and the Phi-Coefficient Introduce the process of linear regression Demonstrate the analysis of regression to evaluate the significance of a linear regression equation 9

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