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STA 282- 1/13/2016

by: Erica Bass

STA 282- 1/13/2016 STA 282QR

Erica Bass
GPA 3.54
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About this Document

Notes from Lecture 1/13/2016
Intro to Statistics
Fu Chijung
Class Notes




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This 2 page Class Notes was uploaded by Erica Bass on Thursday January 14, 2016. The Class Notes belongs to STA 282QR at Central Michigan University taught by Fu Chijung in Summer 2015. Since its upload, it has received 57 views. For similar materials see Intro to Statistics in Statistics at Central Michigan University.


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Date Created: 01/14/16
Introduction: Conducting a Research Observational study: without attempting to influence the value of response or explanatory variables. Observes behavior. Designed Experiment Study: assigns to a certain group of individuals intentionally changes value of explanatory variable and records the value of the response variable of each group. Population: entire group of individuals to be studies Sample: a subset of the population that is being studied (cost, time, and accuracy are factors to consider) Parameter: numerical summary of a population Statistic: numerical summary of a sample Simple Random Sampling: using chance to select individuals from a population; everyone has equal chance of getting sampled Systematic Sampling: selecting every kth individual from a population. First individual selected is a random number between 1 and k. Stratified Sampling: obtained by separating the population into homogenous, non over lapping groups called strata. (Example: male versus female) Cluster Sampling: can not find a difference between groups. Qualitative Variables: allow for classification of individuals based on characteristics (gender, blood type) Quantitative: numerical measures of individuals (height, gpa) Continuing Variables: infinite number of possible values Discrete Variables: (Example – you can have 0, 1, 2 siblings; not 1.5 siblings) Nominal Variables: naming, labeling, categorizing (nationality, hair color) Ordinal Variables: allows to be arranged in a ranked, specific order Interval Variables: able to measure, arithmetic can be performed (Example – 0 degrees does no mean there is no temperature, temperature can be negative) Ratio Variables: (Example – Height; 0 inches means no length, can not be negative) Sampling Bias: bad samples; not all individuals in population included Non-Response Bias: not interested; doesn’t want to participate Response Bias: no ability to answer; misunderstood question, biased questionnaire Variable: characteristics that changes or varies over time and/or different individuals (hair color, white blood cell count) Experimental Unit: individual or object on which a variable is measured (person, car, class) Measurement: results when a variable is actually measured on an experimental unit


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