ILR STATS - 03/03/2008 15:47:00 ← ← STATISTIC PRELIM 1...

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Unformatted text preview: 03/03/2008 15:47:00 ← ← STATISTIC PRELIM 1 ← ← Chapter 2 • Answering the who, what, when, where, why and how questions provide context for data values. o If you can’t answer the who or the what there is no data • The people we experiment on are the subjects or participants, people who answer questions are the respondents • Characteristics recorded about each individual are called variables • When a variable named categories and answers question about how cases fall into those categories, names categories they are categorical variables • When a measured variable with units answered questions about the quantity of what is measured they are , numbers act as numeric values, quantitative variables • Counts are used in two different ways o When we count the cases is each category of a categorical data, the categories are labeled at the What and the Who – summarize the data o other times counting focuses on the amount of something – quantitative • How the data is collected makes the difference between insight and nonsense WHAT CAN GO WRONG? o Don’t label a variable as categorical or quantitative without thinking about the question you want to answer o Just because your variable’s values are number, don’t assume that its quantitative o Always be skeptical • Who = cases, What = variables, Why helps us decide how to treat the variables ← ← Chapter 3 – Categorical Data • Make a picture with the data o Reveal things you are not likely to see in table – think clearly o Show the important features of the patterns o Best way to tell others Categorical Data • We can organize counts into frequency tables • Counts are useful but sometimes it better to use proportions, percentages • Relative frequency table displays the percentages (instead of the counts) o Can describe the distribution • The best data displays observe the area principle, which says that they are occupied by a part of the graph, should correspond to the magnitude of the value it represents. • Bar chart – check categorical data condition o Displays the distribution of a categorical variable, showing the sound for each category next to each other for easy comparison o Small spaces between the bars o Relative frequency bar chart Draws attention to the relative proportion of passengers falling into each of the categories • Pie charts – check categorical data condition o Quick expression of how the whole group is partitioned into smaller groups • Contingency Tables o Shows how individuals are distributed along each variable, contingent of the values of the other variables o Margins give totals o Margins of a contingency table, the frequency distribution of one of the variables is called its marginal distribution o Conditional distribution are created when they show the distribution of one variable just for those cases that satisfy the condition on another variable o When the distribution of one variable is the same for all categories of another...
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This note was uploaded on 05/09/2008 for the course ILRST 2100 taught by Professor Vellemanp during the Spring '07 term at Cornell University (Engineering School).

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ILR STATS - 03/03/2008 15:47:00 ← ← STATISTIC PRELIM 1...

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