6230lectinuse - 4/6230 lecture notes Xiangrong Yin Abstract...

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4/6230 lecture notes Xiangrong Yin * January 13, 2010 Abstract The lecture notes combines the content in the textbook as well as previously used notes. Modification can happen often as the course goes on. Typos may exist in many places–please let me know if you spot them. Lecture basically starts with chapter 2 in the textbook. First lab to use hw0.sas. c Xiangrong Yin. This material is restricted to be used for this course only, not to be distributed in any other sense to the outside of this class. * Department of Statistics, 204 Statistics Building, UGA, Athens, GA 30602. 1
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Chapter 1 For this course, we should have known the content in chapter 1 of the textbook. That is, you are already famil- iar with basic concepts in chapter 1. After my quick re- view of these concepts, if you still have difficulties, please review again by yourself; Otherwise, you need to with- draw from this course. 1. Statistics is the science of data, which involves col- lecting, classifying, summarizing, organizing, analyz- ing, and interpreting data. 2. An experimental unit is an object (person or thing) upon which we collect data. 3. A variable is a characteristic (property) of the ex- perimental unit with outcomes (data) that vary from one observation to the next. 4. Quantitative data are observations measured on a naturally occurring numerical scale, while quali- tative data are nonnumeric data that can only be classified into one of a group of categories. 2
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5. A Population data set is a collection of data mea- sured on all experimental units of interest to you. 6. A Sample is a subset of data selected from a popu- lation. 7. A Statistical inference is an estimate, predic- tion, or some other generalization about a popula- tion based on information contained in a sample. 8. A measure of reliability is a statement (usually quantified with a probability value) about the degree of uncertainty associated with a statistical inference. 9. A representative sample exhibits characteristics typical of those possessed by the population. 10. A random sample of n experimental units is one selected from the population in such a way that ev- ery different sample of size n has an equal probability (chance) of selection. 3
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11. A class is one of the categories into which qualita- tive data can be classified. 12. The class frequency is the number of observations in the data set falling in a particular class. 13. The class relative frequency is the class fre- quency divided by the total number of observations. 14. Graphical methods: bar graph , pie chart , stem- and-leaf plot , histogram , etc. 15. The sample Mean of a sample of size n , say y 1 , · · · , y n is ¯ y = n i =1 y i n = y 1 + · · · + y n n . The population mean is E ( y ) = μ . 16. The range of a sample is the difference between the largest and the smallest measurements in the sample.
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