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LectureNotes2 - Topic 2. Descriptive Statistics: Part I Cyr...

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Topic 2. Descriptive Statistics: Part I Cyr Emile M’LAN, Ph.D. mlan@stat.uconn.edu Descriptive Statistics – p. 1/33
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Introduction Text Reference : Introduction to Probability and Statistics for Engineers and Scientists, Chapter 2. Reading Assignment : Sections 2.1-2.2, September 3-September 8 Descriptive statistics is a preliminary analysis steps concerned with organizing and summarizing the data to identify patterns through the use of tabular tools ( frequency tables or frequency distribution ), graphical data display tools ( pie chart, bar chart, dotplot, stem-and-leaf plot, histogram, boxplot, scatterplot, time plot ), numerical summarizes such as measures of central tendency ( mean, median, trimmed mean, mode ), measures of relative standing ( percentile, z-score ), and measure of variability ( range, interquartile range, variance, standard deviation). Descriptive Statistics – p. 2/33
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Variable and Data Variable — A variable is a any characteristic being counted or measured whose value may change from one object to another in the population ( blood type, eye color, height, weight, age, ethnicity, blood pressure, cholesterol level, packs of cigarettes smoked per day ). — There are two types of variables: quantitative (numerical) and qualitative (categorical). — The actual observed value of a variable is called an observation . A collection of observations is called data . Data — Analogous to variable, there are two types of data: qualitative data and quantitative data. Descriptive Statistics – p. 3/33
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Variable and Data Types of Data univariate : Data consists of one variable. bivariate : Data consists of two variables. multivariate : Data contains more than two variables Descriptive Statistics – p. 4/33
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Quantitative Variable — We can do arithmetic with quantitative variables. — There are two types of quantitative variables: continuous and discrete . A continuous variable is one that can take any value in an interval, which usually measures how much or what percentage. Examples include Height, Weight, Size, Volumn, Age, Time, and so on. A discrete variable is one that can take values only in a discrete set, which describes how many such as Counts. Examples include Number of Meals Eaten in a Day, Number of Pages in a Textbook, Number of Processor in a Desktop Computer, Number of Chairs of Uconn Classroom, Number of Housing Units Sold. Descriptive Statistics – p. 5/33
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Qualitative (Categorical) Variable — A variable is categorical if it defines categories. — Two types of categorical variables: intrinsically categorical and derived categorical . — Examples for “intrinsically categorical" variable include Gender, Race, Color, Brand Name, Type of Defect, Type of Transmission of an Automobile. — A
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This note was uploaded on 10/01/2009 for the course CHEM 334 taught by Professor Lei during the Spring '09 term at UConn.

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LectureNotes2 - Topic 2. Descriptive Statistics: Part I Cyr...

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