MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear re…
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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7,8,9
True/False portion: 1) The sample mean x is a point estimate for the population mean µ. 2) In tests of significance, it is possible to reject the null hypothesis and yet still have a significant result. 3) that you made the wrong decision. If one rejects the null hypothesis at the 5% level, then there is a 5% chance 4) In the p-value approach, if p-value>a (the level of significance) we reject the null hypothesis. If you fail to reject the null hypothesis at the 5% level, then the probability 5) that you are wrong is always 5%. A wider confidence interval gives a greater level of confidence than a 6) narrower one (when working with the same data). If the sample mean of a data set is 3.2 then the population mean must also 7) be 3.2 8) As the sample size (n) increases, the standard deviation of x from that sample decreases, this assumes the standard deviation is positive.. The level of significance is the probability of rejecting the null hypothesis 9) when the null hypothesis is true. 10) even with the same level of significance, hypotheses and data? Classical hypothesis testing can give different decisions than the P-value approach
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Transcribed Image Text:True/False portion: 1) The sample mean x is a point estimate for the population mean µ. 2) In tests of significance, it is possible to reject the null hypothesis and yet still have a significant result. 3) that you made the wrong decision. If one rejects the null hypothesis at the 5% level, then there is a 5% chance 4) In the p-value approach, if p-value>a (the level of significance) we reject the null hypothesis. If you fail to reject the null hypothesis at the 5% level, then the probability 5) that you are wrong is always 5%. A wider confidence interval gives a greater level of confidence than a 6) narrower one (when working with the same data). If the sample mean of a data set is 3.2 then the population mean must also 7) be 3.2 8) As the sample size (n) increases, the standard deviation of x from that sample decreases, this assumes the standard deviation is positive.. The level of significance is the probability of rejecting the null hypothesis 9) when the null hypothesis is true. 10) even with the same level of significance, hypotheses and data? Classical hypothesis testing can give different decisions than the P-value approach
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