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... decision making, x, is determined by the requirement to control the Type I error. For n = 60 and a 90sik criteria, the benefit-of-doubt decision rule is: "e > 10 =breachw. With this compliance there is a 95% chance that a marginal breach would not be detected. Remember, that the chance of a Type I1 ...
Notes on basic statistics
Notes on basic statistics

Population Mean
Population Mean

... lower segment contains at least p%, and the upper segment contains at least (100 – p)%, of the data. The 50th percentile is the median. ...
Hypothesis Testing Methods to test
Hypothesis Testing Methods to test

how to introduce standard deviation
how to introduce standard deviation

summary statistics - NYU Stern School of Business
summary statistics - NYU Stern School of Business

Chapter 1: Descriptive Statistics – Part I
Chapter 1: Descriptive Statistics – Part I

Question 1
Question 1

... Part B: 20 Multiple Choice Questions Part A is to be answered in the examination answer booklets provided. Number each question clearly. Write your name and student number on the front cover of the answer booklets used. Part B is to be answered on the General Purpose Answer Sheet, using a 2B pencil ...
19: Sample Size, Precision, and Power
19: Sample Size, Precision, and Power

... EpiCalc 2000 uses a slightly different formula than those above, its sample size calculation will be slightly smaller. This should not concern you because the problem with sample size calculations come not from small differences in formulas but from differences in values entered into the formula. S ...
Data analysis reflection
Data analysis reflection

6. Introduction to Regression and Correlation
6. Introduction to Regression and Correlation

... The input to the regression process is a sample of pairs of values of x and y. Outline of regression /straight line ‘fitting’ It is always a good idea to create a Scatter Plot of the data beforehand as a visual check that the assumption of a straight relationship is plausible. Be clear on which vari ...
Estimating_Population
Estimating_Population

View/Open - Pan Africa Christian University
View/Open - Pan Africa Christian University

σ < = 2.355 = 4.492 - Emily Miller`s ePortfolio
σ < = 2.355 = 4.492 - Emily Miller`s ePortfolio

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Document

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No Slide Title

ID_994_MI-1-4- Medical knowledge and _English_sem_4
ID_994_MI-1-4- Medical knowledge and _English_sem_4

... Calculated values of one- and two-tailed t-tests and degrees of freedom. Calculated values of means, variances for the both input datasets, degrees of freedom, t-statistic and both the one-tailed and two-tailed probabilities and critical values Calculated values of means, variances for the both inpu ...
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DA_Lecture10

PDF
PDF

... A statistical sample is a fraction or a portion of the whole (population) that is studied. This is a concept that may be confusing to many and is best illustrated with examples. Consider that a chemical engineer is interested in understanding the relationship between the rate of a reaction and tempe ...
Statistics - Ipemgzb.ac.in
Statistics - Ipemgzb.ac.in

Activity 2: To choose the statistical technique for given problems
Activity 2: To choose the statistical technique for given problems

... 11. When new paperback novels are promoted at bookstores, a display is often arranged with copies of the same book with differently colored covers. A publishing house wanted to find out whether there is a dependence between the place where the book is sold and the color of its cover. For one of its ...
PPT presentation
PPT presentation

DOC
DOC

... A statistical sample is a fraction or a portion of the whole (population) that is studied. This is a concept that may be confusing to many and is best illustrated with examples. Consider that a chemical engineer is interested in understanding the relationship between the rate of a reaction and tempe ...
Stat 281 Chapter 9
Stat 281 Chapter 9

DOC - math for college
DOC - math for college

... A statistical sample is a fraction or a portion of the whole (population) that is studied. This is a concept that may be confusing to many and is best illustrated with examples. Consider that a chemical engineer is interested in understanding the relationship between the rate of a reaction and tempe ...
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Misuse of statistics

Statistics are supposed to make something easier to understand but when used in a misleading fashion can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy.The false statistics trap can be quite damaging to the quest for knowledge. For example, in medical science, correcting a falsehood may take decades and cost lives.Misuses can be easy to fall into. Professional scientists, even mathematicians and professional statisticians, can be fooled by even some simple methods, even if they are careful to check everything. Scientists have been known to fool themselves with statistics due to lack of knowledge of probability theory and lack of standardization of their tests.
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