MA 331 Intermediate StatisticsPowerPoint PresentationGradesGrades (cont.)Slide 5TextbooksRData, Data, Data, all around us !ExampleWhat is statistics?Structure of the courseChapter 1Variable types:Information on employees of CyberstatnetDistribution of a variable:For the Categorical VariablesBar GraphPie ChartEXAMPLE - Child poverty before and after government intervention—UNICEF, 1996ExerciseGraphical tools for quantitative dataStemplot example (FYI)Stemplot (FYI)Back-to-back stemplot (FYI)Histograms (example)Histogram (cont)Frequency TableUsing RExamining distributionsInterpreting histogramsMost common distribution shapesSlide 32What do you see?Quantitative Variables-Graphical DisplaySlide 35Newcomb’s data (dealing with outliers)OutliersTime plots. Newcomb’s data.Slide 39Slide 40How to create a histogramSlide 42IMPORTANT NOTE: Your data are the way they are. Do not try to force them into a particular shape.Time seriesSlide 45Slide 46Slide 47Exercises: Learn to input data in RSummaryMA 331 Intermediate MA 331 Intermediate StatisticsStatisticsInstructorInstructorIonut FlorescuIonut FlorescuInstructor : Ionut FlorescuInstructor : Ionut FlorescuOfficeOffice: Kidde 227 Phone 201-216-5452: Kidde 227 Phone 201-216-5452Office hoursOffice hours: TR 12:00-13:00, or by : TR 12:00-13:00, or by appointment.appointment.Please print off the course information Please print off the course information posted on web.posted on web.EmailEmail:: [email protected]@stevens.eduMailboxMailbox: in Math. Dept office.: in Math. Dept office.GradesGradesHomework (30%) – almost every week, Homework (30%) – almost every week, usually due on Thursdays. usually due on Thursdays. Midterm (20%) Midterm (20%) Final paper and Finalized project (30%) – Final paper and Finalized project (30%) – during the finals week, closed books/notes.during the finals week, closed books/notes.Project 1, Project 2 and Attendance (20%)Project 1, Project 2 and Attendance (20%)Attendance is not mandatory, however if Attendance is not mandatory, however if you get into the habit of skipping the you get into the habit of skipping the lecture I will deduct points. Participation in lecture I will deduct points. Participation in the lecture is rewarded here as well.the lecture is rewarded here as well.Grades (cont.)Grades (cont.)For the first part of the project you will be For the first part of the project you will be required to find an interesting dataset required to find an interesting dataset suitable for analysis. You will write a suitable for analysis. You will write a proposal detailing a description and proposal detailing a description and interesting features of the dataset, questions interesting features of the dataset, questions that would be useful to answer, and that would be useful to answer, and proposed methods.proposed methods.For the second part of the project you will For the second part of the project you will implement methods learned in class to implement methods learned in class to analyze the dataset from the first part of the analyze the dataset from the first part of the project.project.Grades (cont.)Grades (cont.)You should assume regular cutoffs You should assume regular cutoffs (90%-100% A etc.), however (90%-100% A etc.), however depending on the performance of the depending on the performance of the class the final percentages may be class the final percentages may be curved.curved.R is needed for the class. You will R is needed for the class. You will need to use it for the project and need to use it for the project and homework problems and I may test homework problems and I may test your knowledge of R in the exam and your knowledge of R in the exam and quizzes. quizzes.TextbooksTextbooksIntroduction to the Practice of Introduction to the Practice of StatisticsStatistics, , 6th edition6th edition, by David S. , by David S. Moore, George P. McCabe and Bruce Moore, George P. McCabe and Bruce A. Craig.A. Craig. Introductory Statistics with R, Introductory Statistics with R, by by Peter Dalgaard, second edition.Peter Dalgaard, second edition.RRPlease see the Introduction to R files Please see the Introduction to R files on the website.on the website.You are expected to read the second You are expected to read the second textbook and familiarize yourself with textbook and familiarize yourself with RRIf you need help ask questions and If you need help ask questions and seek answers from your project seek answers from your project mates, class mates and myselfmates, class mates and myselfData, Data, Data, all around us !Data, Data, Data, all around us !We use data to answer research We use data to answer research questionsquestionsWhat evidence does data provide?What evidence does data provide?Example 1:Example 1:Subject SBP HR BG Age Weight TreatmentSubject SBP HR BG Age Weight Treatment11 120 84 100 45 140 1120 84 100 45 140 122 160 75 233 52 160 1160 75 233 52 160 133 95 63 92 44 110 295 63 92 44 110 2. . . . . . .. . . . . . .How do I make sense of these numbers How do I make sense of these numbers without some meaningful summary?without some meaningful summary?ExampleExampleStudy to assess the effect of exercise on Study to assess the effect of exercise on cholesterol levels. One group exercises and cholesterol levels. One group exercises and other does not. Is cholesterol reduced in other does not. Is cholesterol reduced in exercise group?exercise group?people have naturally different levelspeople have naturally different levelsrespond differently to same amount of respond differently to same amount of exercise (e.g. genetics)exercise (e.g. genetics)may vary in adherence to exercise regimenmay vary in adherence to exercise regimendiet may have an effectdiet may have an effectexercise may affect other factors (e.g. exercise may affect other factors (e.g. appetite, energy, schedule)appetite, energy, schedule)What is statistics?What is statistics?•Recognize the randomness, the Recognize the randomness, the variability in data.variability in data.•““the science of understanding data the science of understanding data and making decisions in face of and making