STAT 135 Lab 5 Bootstrapping and Hypothesis Testing - b
... We know that if the H0 is true then T (X1 , ..., Xn ) ∼ N(0, 1), so our p-value for the hypothesis test with H1 : µ > 5 is given by P(Z > T (X1 , ..., Xn )) = P(Z > 4.44) = 0.0000045 This tells us that, assuming H0 is true, the probability of seeing a test statistic as extreme or more extreme than w ...
... We know that if the H0 is true then T (X1 , ..., Xn ) ∼ N(0, 1), so our p-value for the hypothesis test with H1 : µ > 5 is given by P(Z > T (X1 , ..., Xn )) = P(Z > 4.44) = 0.0000045 This tells us that, assuming H0 is true, the probability of seeing a test statistic as extreme or more extreme than w ...
FITTING DISTRIBUTIONS WITH R
... distributions. We can estimate frequency density using density()and plot()to plot the graphic ( Fig. 2): plot(density(x.norm),main="Density estimate of data") R allows to compute the empirical cumulative distribution function by ecdf() (Fig. 3): plot(ecdf(x.norm),main=” Empirical cumulative distribu ...
... distributions. We can estimate frequency density using density()and plot()to plot the graphic ( Fig. 2): plot(density(x.norm),main="Density estimate of data") R allows to compute the empirical cumulative distribution function by ecdf() (Fig. 3): plot(ecdf(x.norm),main=” Empirical cumulative distribu ...
Hypothesis Tests about the Mean and Proportion
... Example 9-1 The management of Priority Health Club claims that its members lose an average of 10 pounds or more within the first month after joining the club. A consumer agency that wanted to check this claim took a random sample of 36 members of this health club and found that they lost an average ...
... Example 9-1 The management of Priority Health Club claims that its members lose an average of 10 pounds or more within the first month after joining the club. A consumer agency that wanted to check this claim took a random sample of 36 members of this health club and found that they lost an average ...
Chapter 1: Statistics
... a. Describe the population parameter of concern b. State the null hypothesis (Ho) and the alternative hypothesis (Ha) 2. The Hypothesis Test Criteria a. Check the assumptions b. Identify the probability distribution and the test statistic formula to be used c. Determine the level of significance, ...
... a. Describe the population parameter of concern b. State the null hypothesis (Ho) and the alternative hypothesis (Ha) 2. The Hypothesis Test Criteria a. Check the assumptions b. Identify the probability distribution and the test statistic formula to be used c. Determine the level of significance, ...
An Introduction to MCMC methods and Bayesian
... A powerful feature of MCMC and the Bayesian approach is that all inference is based on the joint posterior distribution. We can therefore address a wide range of substantive questions by appropriate summaries of the posterior. Typically report either the mean or median of the posterior samples fo ...
... A powerful feature of MCMC and the Bayesian approach is that all inference is based on the joint posterior distribution. We can therefore address a wide range of substantive questions by appropriate summaries of the posterior. Typically report either the mean or median of the posterior samples fo ...
One-way ANOVA - Studentportalen
... The first step was to calculate a mean (from the n independent pieces of data collected). The second step is to calculate a variance with reference to that mean. If n − 1 deviations are calculated, it is known what the final deviation must be, for they must all add up to zero by definition. So we ha ...
... The first step was to calculate a mean (from the n independent pieces of data collected). The second step is to calculate a variance with reference to that mean. If n − 1 deviations are calculated, it is known what the final deviation must be, for they must all add up to zero by definition. So we ha ...
MAT 220 Class Notes
... population parameter from information contained in a sample. Elements of a statistical problem: (i) A clear definition of the population and variable of interest. (ii) a design of the experiment or sampling procedure. (iii) Collection and analysis of data (gathering and summarizing data). (iv) Proce ...
... population parameter from information contained in a sample. Elements of a statistical problem: (i) A clear definition of the population and variable of interest. (ii) a design of the experiment or sampling procedure. (iii) Collection and analysis of data (gathering and summarizing data). (iv) Proce ...
The Z-test - UW Courses Web Server
... rejection region, so we fail to reject H0 and conclude that our drug did not have a significant effect on IQ. To calculate the p-value we need to find the area under the standard normal distribution beyond our observed value of z and double it. This is because for a two-tailed test we want the proba ...
... rejection region, so we fail to reject H0 and conclude that our drug did not have a significant effect on IQ. To calculate the p-value we need to find the area under the standard normal distribution beyond our observed value of z and double it. This is because for a two-tailed test we want the proba ...