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Unformatted text preview: STA 3024 Introduction to Statistics 2 Chapter 1: Preparations “ Statistics is the art and science of designing studies and analyzing the data that those studies produce. Its ultimate goal is translating data into knowledge and understanding of the world around us. In short, statistics is the art and science of learning from data. ” 1 PART I  BASIC CONCEPTS The three main aspects of statistics are design, description, and inference. Design refers to how to obtain data to answer the questions of interest. Description means exploring and summarizing patterns in the data. Inference means making decisions or predictions based on the data. 1.1 Populations and Samples The entities that we measure in a study are called the subjects . The population is the set of all the subjects of interest. However, more than often in reality, we don’t have enough resources (money, time, labour, etc.) to collect data from the whole population. Hence, we’d try to collect data from a sample of the population instead. A sample is a subset of the population. Example: We want to know how much UF students like the vanilla flavor. The sub jects of interest here is UF students, and the population is the whole student body of the university. Now, say the research is lack of funding because not that many people are in terested in the raised question, except for our local Baskin Robbins. Thus, we only have enough money to survey 100 students. Free vanilla ice cream for the first 100 students, they say. That 100 students is a subset of the whole student body, and is a sample in our study. N Simple random samples: When each subject in the population has the same chance of being included in a sample, that sample tends to be a good reflection of its population. The idea is the basis of random sampling, which is designed to make the sample good representative of the population. The best way to ensure this is to choose subjects from the population using a truly ran dom procedure, like drawing names out of a hat, or more commonly, using random numbers generated by a computer. The result is a simple random sample, or SRS. Question: Is that first 100 students who get free ice cream a SRS? 1.2 Descriptive vs. Inferential Statistics Using the difference between samples and populations, we can now distinguish between description and inference in statistical analyses. Descriptive statistics refers to methods for summarizng the data. The summaries usually consist of graphs and numbers such as averages and percentages. Although data are usually available only for a sample, descriptive statistics are also useful when data are availble for the entire population, such as in a census. By contrast, inferential statistics are useful when data are only available for a sample but we want to make a decision or prediction about the entire population....
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This note was uploaded on 12/15/2011 for the course STA 3024 taught by Professor Ta during the Spring '08 term at University of Florida.
 Spring '08
 TA
 Statistics

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