ST_370_Exam_1_Review

# ST_370_Exam_1_Review - Qualitative Data data that come in terms of categories like ethnicity and sex and brand name Quantitative Data data that

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Qualitative Data: data that come in terms of categories like ethnicity and sex and brand name. Quantitative Data: data that consists of numbers. o Nominal: this type of data is just like qualitative data; the only difference is that the categories are numbers. o Ordinal: the ordering of the numbers makes sense, but other uses of the numbers like adding or subtracting them doesn't. Interval and Ratio Data: data that operations can be done on. (add, subtract, multiply, divide) o for regression analysis we need interval or ratio variables. Discrete Data: data for which there are a finite or countably finite number of possible values. Continuous Data: data that can take all possible values in an interval. Data Set: refers to a collection of data. Observational Study: observes individuals and measures variables of interest but doesn't attempt to control the changes of responses. Experiment: deliberately imposes some treatment on individuals in order to observe their responses. o Experimental Unit: the object that the experiment is being performed on, if it is a person it is called a “subject”. o Treatment: A specific experimental condition applied to the experimental units (number of possible combinations of factors). o Factor: a variable that relates to different levels like temperature or capacitance. o Response: the variable measured to judge the reaction. o Experimental Design: manner in which levels of all the factors are changed from one run to the next. o Balanced: if every level of every factor appears an equal number of times, the design is said to be balanced Lurking Variables: variables that have an important effect on the response in an experiment but are not included among the variables studied. Confounding: when effects of different variables on the response cannot be distinguished from each other. Completely Randomized Design: can only be done when you have identical experimental units. Randomly assign a number to each block in the table. Randomized Complete Block Design: Randomly assign a number to each block of a row so that each different unit receives all treatments. Blocking:

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## This note was uploaded on 04/28/2009 for the course ST 370 taught by Professor Nail during the Spring '08 term at N.C. State.

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ST_370_Exam_1_Review - Qualitative Data data that come in terms of categories like ethnicity and sex and brand name Quantitative Data data that

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