First lecture examples[1]

First lecture examples[1] - W hat is Statistics Statistics...

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What is Statistics? Statistics is the science of reasoning from data, so a natural place to begin your study is by examining what is meant by the term data . You will find that data vary, and variability abounds in everyday life and in academic study. Indeed, the most fundamental principle in statistics is that of variability. If the world were perfectly predictable and showed no variability, you would not need to study statistics. Thus, you will learn about variables and consider their different classifications. You will also begin to experience the interesting research questions that you can investigate by collecting data and conducting statistical analyses. How can statistics be used to help decide the guilt or innocence of a nurse accused of murdering some of her patients? If chief executive officers tend to be taller than average, would this convince you that being tall provides advantages in the business world? Do some students do worse on standardized tests when they are first asked to indicate their race than when they are not, perhaps due to negative stereotypes of their academic ability? Vocabulary Supplemental Exercises Chapter 1 1. Statistics is a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting and drawing conclusions based on the data. 2. A population is the complete collection of all elements (scores, people, measurements, and so on) to be studied. The collection is complete in the sense that it includes all subjects to be studied. 3. A sample is a subcollection of elements selected from a population. Example: In a study of household incomes in a small town of 1000 households, one might conceivably obtain the income of every household. However, it is probably very expensive and time consuming to do this. Therefore, a better approach would be to obtain the data from a portion of the households (let’s say 125 households). In this scenario, the 1000 households are referred to as the population and the 125 households are referred to as a sample. 4. A parameter is a numerical measurement describing some characteristic of a population and computed from all of the population measurements. 5. A statistic is a numerical measurement describing some characteristic of a sample drawn from the population. Example: In the household incomes example from above, the average (mean) income of all 1000 households is a parameter, whereas the average (mean) income of the 125 households is a statistic. 6. Discrete data result when the number of possible values is either a finite number or a countable number. (That is, the number of possible values is 0 or 1 or 2 and so on.) Example: The numbers of fatal automobile accidents last month in the 10 largest US cities
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7. Continuous data result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps. Example: The finishing times of a marathon
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This note was uploaded on 12/11/2011 for the course STA 2122 taught by Professor Staff during the Fall '08 term at FIU.

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First lecture examples[1] - W hat is Statistics Statistics...

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