Descriptive Statistics

# Descriptive Statistics - Descriptive Statistics Sampling...

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Descriptive Statistics Sampling and Statistics Statistics We start the discussion in the natural way. We all have a general feeling about what statistics is. In the course of these lecture notes, we will lay out the detail about what statistics is and how it is used. For now we give a quick definition. Statistics is the study of how to collect, organize, analyze, and interpret numerical information from data. Sampling and Types of Data Population vs. Sample We define the population the total set of individuals that we are interested about and a sample a subset of the individuals selected in a prescribed manner of study. Typically, population data is very hard or even impossible to gather. Statisticians and researchers will instead extract data from a sample. There are several types of data that is of interest. We can classify data into two types: 1. Numerical or Quantitative data is data where the observations are numbers. For example, age, height, on a scale from one to ten. .., distance, number of ,. .. 2. Categorical or Qualitative data is data where the observations are non-numerical. For example, favorite color, choice of politician, . .. There is a more refined way to classify data. Data can be put into one of several categories called levels of measurement a. The nominal level is synonymous with qualitative data. b. The ordinal level is data that involves ranking. For example Williams took second place in the US Open. There are no actual values assigned to each variable, but we can still compare one with another. c. The interval level is data such that one outcome can be compared with another outcome by taking differences. For example one outcome may be 12 degrees warmer than another, or an outcome may have occurred 35 minutes later than another. d. The ratio level is data that both differences and ratios can be taken. For example if the cost of a hamburger is \$2 and that of a steak is \$12 , it make sense to either say that the steak costs \$10 more or that the steak is 6 times more expensive.

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e. Boolean data is data that can achieve one of two values such as true or false, yes or no, on or off, etc. For example the outcome of a questionnaire asking if you agree with Bush's policy on the Middle East. Data is called univariate if it represents one attribute and bivariate if it contains two attributes . Bivariate data is often used to compare and contrast . For example, we may study weight gain and caloric intake. Numerical data is called discrete if the number of possible values within every bounded range is finite . Examples include: rolling dice, number of times that. .., . .. Otherwise, numerical data is called continuous . For example, height, weight, temperature, distance,. .. Random Samples
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Descriptive Statistics - Descriptive Statistics Sampling...

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