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Unformatted text preview: Chapter 2 Notes We are constantly collecting data but what does it mean? How can we understand what it is telling us? What are the underlying patterns that are emerging? If we are going to be correct in our interpretation we first must believe in our data. We must be sure our sample really represents our population so that we can answer the questions we asking. We design our study so we can eliminate Bias . Once we are confident we have gathered the information correctly we now need to organize it to understand our results, identify patterns or trends in the data and gain new information. Vocabulary: ⇾ Variable ⇾ Qualitative Data ⇾ Quantitative Data ⇾ Discrete data ⇾ Continuous data ⇾ Proportion o Percentage o Relative frequencies Types of Data Variable • A variable is any characteristic that is recorded for the subjects in a study • Observations: data variables • A variable can be classified as either o Categorical, or o Quantitative (Discrete, Continuous) Quantitative and Categorical Variables • Categorical Variable: each observation belongs to one of a set of categories. o key feature is the percentage of observations in each of the categories • Quantitative Variable: observations on it take numerical values that represent different magnitudes of the variable – not all numbers are quantitative (#’s on a baseball shirt) o key features are the center and spread (variability) Quantitative Variables • Discrete quantitative variables o A quantitative variable is discrete if it is countable • Continuous Quantitative Variable o A quantitative variable is continuous if its possible values form an interval 1 Chapter 2 Notes AG 15:49:31 o Continuous variables have an infinite number of possible values Class Problem #1 • Identify the variable type as either categorical or quantitative o Number of siblings in a family o County of residence o Distance (in miles) of commute to school o Marital status Class Problem #2 • Identify each of the following variables as continuous or discrete o Length of time to take a test o Number of people waiting in line o Number of speeding tickets received last year o Your dog’s weight We want to determine new information so we collect information and record it in a database. 125 256 147 25 13 1300 58 95 21 458 254 489 85 98 1256 487 289 247 496 314 7841 596 56 235 458 598 47 125 25 369 741 256 845 985 125 478 986 326 145 258 1222 1400 258 456 179 139 713 931 785 569 236 452 125 258 314 25 189 125 194 463 258 879 458 784 895 963 159 753 489 438 258 139 489 782 763 94 125 489 1230 … … ⇾ What is the data telling us? What do we want to know? Why was the data taken? What is the data telling us?...
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This note was uploaded on 05/18/2010 for the course MATH math 208 taught by Professor C.eckerle during the Winter '10 term at Delta MI.
 Winter '10
 C.Eckerle
 Math

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