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ILR STATS

# ILR STATS - 3:47:00 PM STATISTIC PRELIM 1 Chapter 2...

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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

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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 – the variable is

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