Remarkable: Weakest Link Hypothesis
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I will frequently cover topics not in your textbook, and I will stress those topics I feel are most important. An example are the tables given on pages 3 and 7 of your textbook.
Notice that the variable GenderCode, although it uses numbers, is actually categorical, as the use of the number 0 for Male and 1 for Female is arbitrary. Also note that this data set is using a traditional binary classification of gender and is not inclusive of all possible categories.
Introduction
Beyond just qualitative vs quantitative variables, we sometimes talk about four Levels of Measurement, where types of data are arranged from weakest to strongest, in the sense of what sort of statistics can be computed. Examples include your sex and your favorite color.
Ordinal level: this is the next strongest form of data, and is the first one involving Weakest Link Hypothesis quantitative variable. Examples include when you ranked your love of chocolate on a 1-to scale, when you evaluate your instructors on a 1-to-5 scale often called a Likert scaleand when a football coach ranks his three quarterbacks from 1 to 3, with Weakest Link Hypothesis being the best player, 2 the second best, and 3 the worst. Interval level: this is numerical data that goes beyond just ranking, but where there is no fixed zero point and the ratio between two numbers does not make sense.
The standard example is temperature. For instance, suppose it is 30 degrees C in one city and 10 degrees in another. Here, there is a fixed Weakest Link Hypothesis point and the ratio between two numbers does make sense. For example, suppose the height of two indivuals are 6 feet tall and 5 feet tall. We can convert to inches, getting 72 and 60 inches, respectively. Multiply inches by 2. The ratio is the same no matter which units you use. In the GPAGender data set, a college admissions officer might wish to predict the college GPA of new students, using the SAT score that they got when they took this test in high school. We can also use a categorical variable as the explanatory variable. If the response variable I want to understand is number of Piercings, I http://pinsoftek.com/wp-content/custom/stamps/gogols-identity-in-the-book-namesake.php notice that the female students tend to have a higher number probably because most women have pierced ears, where most men do not and I could use Sex as the explanatory variable.
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A census is the collection of data from an entire population. It is usually not possible to conduct a census. A sample is a subset of a population that we collect data from. We hope to be able to make generalizations Hypthesis the population based on the sample. If the sample is collected properly, methods of statistical inference can help us with such conclusions. For example, we could determine if a drug is Weakest Link Hypothesis in lowering cholesterol or what percent of the population will vote for a political candidate.
A parameter is a numerical characteristic of a population. It is usually not known, so we estimate it by collecting a sample and calcuating a statistic. It is customary although there are exceptions to use Greek letters to describe population parameters and Roman letters for Weakest Link Hypothesis statistics. The most Weakst example is the mean average.]
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