# STAT 500: Applied Statistics

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This graduate level course provides an introduction to the basic concepts of probability, common distributions, statistical methods, and data analysis. It is intended for graduate students who have one undergraduate statistics course and who wish to review the fundamentals before taking additional 500 level statistics courses. This course is cohort-based, which means that there is an established start and end date, and that you will interact with other students throughout the course.

Upon completion of this course students will:

• Appreciate and understand the role of statistics in your own field of study.
• Develop an ability to apply appropriate statistical methods to summarize and analyze data for some of the more routine experimental settings.
• Make sense of data and be able to report the results in appropriate table or statistical terms for inclusion in your thesis or paper.
• Interpret results from various computer packages (Minitab, SPSS, SAS) and be able to use Minitab to perform appropriate statistical techniques.

This graduate level course covers the following topics:

• An overview of statistics
• Data description: scales of measurement, how to describe data graphically for categorical data (pie chart, bar chart) and graphs for quantitative variables (histogram, stem-and-leaf plot and time plot)
• How to describe data by summary statistics: measures of central tendency and variability
• How to create a box plot
• How to use a statistical package (Minitab)
• How probability and probability distributionsare involved in statistics
• How binomial distributions are involved in statistics
• The role that normal distributions play in statistics
• Simple random sampling and sampling distribution of sample mean , central limit theorem, normal approximation to the binomial
• Differentiation between a population and a sample, how to use a statistic to estimate a population parameter, confidence interval and its interpretation, inferences of population proportion, margin of error and sample size computation
• Confidence interval for population mean, Sample size needed for estimating the population mean with a specified confidence level and specified width of the interval
• Hypothesis testing: in terms of how to set up Null and Alternative hypotheses, understanding Type I and Type II errors, performing a statistical test for the population mean
• How to compute power of a test and choosing the sample size for testing population mean
• p-value, how to compute it and how to use it
• Inferences about μ with σ unknown: the t-distribution and the assumptions required to check in order to use it
• How to compare the mean of two populations for independent samples: using pooled variances t-test versus separate variances t-test
• How to compare the mean of two populations for paired data
• How to compare two population proportions
• Using contingency table and the Chi-square test of independence
• Using an F-test to compare the variances of two populations
• Understanding concepts related to linear regression models including, least squares method, correlation, Spearman's rank order correlation, inferences about the parameters in the linear regression model
• Analyzing data using analysis of variance (ANOVA) methods
• Analyzing data using multiple regression methods

Here is a link to the Online Notes for STAT 500.

Ott, R. L. and Longnecker, M. (2016).  An Introduction to Statistical Methods and Data Analysis, 7th Edition, Cengage Learning.

ISBN 13: 978-1-305-26947-7,  ISBN 10: 1-305-26947-0

This course will use the statistical software program Minitab. See the Statisitical Software page for more information.

A graphing calculator is recommended for this course, especially for students enrolled or considering the MAS program. Otherwise, a basic calculator that includes factorials and combinations will suffice. Please note that for the final exam using a calculator on a device with internet capabilities (e.g. cell phone) will NOT be permitted.

Homework: Homework assignments will be submitted almost every week. Due dates will be specified in the course calendar.  Doing the homework promptly and carefully is necessary for learning the material. A reasonable amount of collaboration is allowed and encouraged on homework. However, each student must turn in his or her own written work which reflects his or her own understanding of the material. There is penalty for handing in homework late.

Assessments: 4 assessments / quizzes (short exams)

Mid-term Exams: 2 midterm exams

Final Exam: The final exam will be comprehensive.

PLEASE NOTE: This course may require you to take exams using certain proctoring software that uses your computer's webcam or other technology to monitor and/or record your activity during exams. The proctoring software may be listening to you, monitoring your computer screen, and viewing you and your surroundings. By enrolling in this course, you consent to the use of the proctoring software selected by your instructor, including but not limited to any audio and/or visual monitoring which may be recorded. (Read more...)

All Penn State policies regarding ethics and honorable behavior apply to this course. Academic integrity is the pursuit of scholarly activity free from fraud and deception and is an educational objective of this institution. All University policies regarding academic integrity apply to this course. Academic dishonesty includes, but is not limited to, cheating, plagiarizing, fabricating of information or citations, facilitating acts of academic dishonesty by others, having unauthorized possession of examinations, submitting work of another person or work previously used without informing the instructor, or tampering with the academic work of other students.

For any material or ideas obtained from other sources, such as the text or things you see on the web, in the library, etc., a source reference must be given. Direct quotes from any source must be identified as such.

All exam answers must be your own, and you must not provide any assistance to other students during exams. Any instances of academic dishonesty WILL be pursued under the University and Eberly College of Science regulations concerning academic integrity. For more information on academic integrity, see Penn State's statement on plagiarism and academic dishonesty.

The Eberly College of Science Code of Mutual Respect and Cooperation embodies the values that we hope our faculty, staff, and students possess and will endorse to make The Eberly College of Science a place where every individual feels respected and valued, as well as challenged and rewarded.

Penn State welcomes students with disabilities into the University's educational programs. If you have a disability-related need for reasonable academic adjustments in this course, contact the Office for Disability Services (ODS) at 814-863-1807 (V/TTY). For further information regarding ODS, please visit the Office for Disability Services Web site at http://equity.psu.edu/ods/.