Analysis of Variance Key Concept
... An Approach to Understanding ANOVA 1. Understand that a small P-value (such as 0.05 or less) leads to rejection of the null hypothesis of equal means. With a large P-value (such as greater than 0.05), fail to reject the null hypothesis of equal means. 2. Develop an understanding of the underlying ra ...
... An Approach to Understanding ANOVA 1. Understand that a small P-value (such as 0.05 or less) leads to rejection of the null hypothesis of equal means. With a large P-value (such as greater than 0.05), fail to reject the null hypothesis of equal means. 2. Develop an understanding of the underlying ra ...
Chapter 9 - Sampling Distributions
... The final sampling distribution introduced is that of the difference between two sample means. This requires: independent random samples be drawn from each of two normal populations If this condition is met, then the sampling distribution of the difference between the two sample means, i.e. will b ...
... The final sampling distribution introduced is that of the difference between two sample means. This requires: independent random samples be drawn from each of two normal populations If this condition is met, then the sampling distribution of the difference between the two sample means, i.e. will b ...
Algebra II Notes Statistical Inference Part I Units 9.1-9.3,9.6
... 1) Population - the entire group of individuals that we want information about. 2) Parameter – a measureable characteristic of the population. 3) Sample – a part of the population that we will actually examine in order to gather information. 4) Statistic – a measureable characteristic of the sample. ...
... 1) Population - the entire group of individuals that we want information about. 2) Parameter – a measureable characteristic of the population. 3) Sample – a part of the population that we will actually examine in order to gather information. 4) Statistic – a measureable characteristic of the sample. ...
PDF
... p-value representing the probability that the data values are consistent with the underlying distribution function. If the optional parameter is passed to the function, then it must be a reference to a variable that, upon return, will be set to the value of the Kolmogorov statistic.. The ...
... p-value representing the probability that the data values are consistent with the underlying distribution function. If the optional parameter is passed to the function, then it must be a reference to a variable that, upon return, will be set to the value of the Kolmogorov statistic.. The ...
mean? proportion? relationship? • Mean: one population? two populations?
... • Proportion: one population? two populations? ∗ One population: z-procedure if we want to estimate p by confidence interval, then how large is our sample? both number of successes and number of failures are at least 15 → large-sample C.I. number of uccesses or number of failures is less than 15 bu ...
... • Proportion: one population? two populations? ∗ One population: z-procedure if we want to estimate p by confidence interval, then how large is our sample? both number of successes and number of failures are at least 15 → large-sample C.I. number of uccesses or number of failures is less than 15 bu ...
