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## StatisticswithApplications

by: Chyna Hettinger

36

0

2

# StatisticswithApplications STA120

Chyna Hettinger
CSU Pomona
GPA 3.83

JefferyGarland

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COURSE
PROF.
JefferyGarland
TYPE
Class Notes
PAGES
2
WORDS
KARMA
25 ?

## Popular in Statistics

This 2 page Class Notes was uploaded by Chyna Hettinger on Saturday October 3, 2015. The Class Notes belongs to STA120 at California State Polytechnic University taught by JefferyGarland in Fall. Since its upload, it has received 36 views. For similar materials see /class/218375/sta120-california-state-polytechnic-university in Statistics at California State Polytechnic University.

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Date Created: 10/03/15
Statistics Definitions Bivariate Data data that involves two variables the quantities from these two variables are often represented using a scatter plot This is done so that the relationship if any between the variables is easily seen Response variable The outcome ofa study a variable you would be interested in predicting or forecasting Often called a dependent variable or predicted variable Explanatory variable Any variable that explains the response variable Often called an independent variable or predictor variable Confounding is an extraneous variable in a statistical model that correlates positively or negatively with both the dependent variable and the independent variable Lurking variable an extraneous variable in a statistical model that correlates positively or negatively with both the dependent variable and the independent variable Bias A statistic is biased if it is calculated in such a way that it is systematically different from the population parameter of interest Sampling Bias when a sample is collected in such a way that some members of the intended population are less likely to be included than others It results in a biased sample a non random samplem ofa population or non human factors in which all individuals or instances were not equally likely to have been selectedlzl If this is not accounted for results can be erroneously attributed to the phenomenon under study rather than to the method of sampling Nonresponse Bias Non response bias occurs in statistical surveys if the answers of respondents differ from the potential answers of those who did not answer Response Bias Response bias is a type of cognitive bias which can affect the results of a statistical survey if respondents answer questions in the way they think the questioner wants them to answer rather than according to their true beliefs Sampling Error sampling error or estimation error is the error caused by observing a sample instead ofthe whole population Nonsampling error A statistical error caused by human error to which a specific statistical analysis is exposed These errors can include but are not limited to data entry errors biased questions in a questionnaire biased processingdecision making inappropriate analysis conclusions and false information provided by respondents Control Group a group of subjects closely resembling the treatment group in many demographic variables but not receiving the active medication or factor under study and thereby serving as a comparison group when treatment results are evaluated Treatment Group When analyzing data the treatments are specified either as numerical values or as levels of a factor When several different treatments are being studied at the same time a given subject or item in the experiment would be described by values or factors associated with each ofthe different treatments as well as by any observed outcomes from the experiment Experimental Design We are concerned with the analysis of data generated from an experiment It is wise to take time and effort to organize the experiment properly to ensure that the right type of data and enough of it is available to answer the questions of interest as clearly and efficiently as possible This process is called experimental design

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