Stats: Test 1 Review
... 18) A random sample of 30 high school students is selected. Each student is asked how many hours he or she spent on the Internet during the previous week. The results are shown in the histogram. Estimate the sample mean. ...
... 18) A random sample of 30 high school students is selected. Each student is asked how many hours he or she spent on the Internet during the previous week. The results are shown in the histogram. Estimate the sample mean. ...
Discrete Probability Distributions
... p(x=0|µ)=1-µ Probability distribution has the form Bern(x|µ)=µ x (1-µ) 1-x Mean is shown to be E[x]=µ Variance is Var[x]=µ (1-µ) Likelihood of n observations independently drawn from p(x|µ) is N ...
... p(x=0|µ)=1-µ Probability distribution has the form Bern(x|µ)=µ x (1-µ) 1-x Mean is shown to be E[x]=µ Variance is Var[x]=µ (1-µ) Likelihood of n observations independently drawn from p(x|µ) is N ...
Lecture 3
... Ei expected cases in ith category when the null is true. k the number of categories. The null hypothesis is rejected at an significance level if v 2 ( k 1). ...
... Ei expected cases in ith category when the null is true. k the number of categories. The null hypothesis is rejected at an significance level if v 2 ( k 1). ...
experimental - accepted
... S states that 68.26% of all data lies between ±1s of the mean, 95.44% of all data lies The empirical rule between ±2s, and 99.74% lies between ±3s. If the data is very precise, then the standard deviation will be small, meaning that the “spread” of the data is narrow and our values are very close to ...
... S states that 68.26% of all data lies between ±1s of the mean, 95.44% of all data lies The empirical rule between ±2s, and 99.74% lies between ±3s. If the data is very precise, then the standard deviation will be small, meaning that the “spread” of the data is narrow and our values are very close to ...
3.1 Events, Sample Spaces, and Probability
... Let pi represent the probability of sample point i. Then 1. All sample point probabilities must lie between 0 and 1 (i.e. 0 ≤ pi ≤ 1). 2. P The probabilities of all the sample points within a sample space must sum to 1 (i.e., pi = 1) Example 4 In example 1, we have only two sample points and thus, w ...
... Let pi represent the probability of sample point i. Then 1. All sample point probabilities must lie between 0 and 1 (i.e. 0 ≤ pi ≤ 1). 2. P The probabilities of all the sample points within a sample space must sum to 1 (i.e., pi = 1) Example 4 In example 1, we have only two sample points and thus, w ...
FORMULA SHEET NUMBER ONE (consists of 2 pages)
... This is the smaller of the two standard deviations provided by the TI 83/84. ...
... This is the smaller of the two standard deviations provided by the TI 83/84. ...
Power - faculty.arts.ubc.ca
... This will be demonstrated for tests of the mean of a normal population when the population variance is known. With this set‐up, the Appendix Table for the standard normal distribution can be used to look‐up required probabilities. The ideas can be applied to any other hypothesis testing appl ...
... This will be demonstrated for tests of the mean of a normal population when the population variance is known. With this set‐up, the Appendix Table for the standard normal distribution can be used to look‐up required probabilities. The ideas can be applied to any other hypothesis testing appl ...
Action Level
... If you repeatedly calculate sample means for many independent random sampling events from a population, in the long run, you would be correct 95% of the time in claiming that the true mean is less than or equal to the 95% UCL of all those sampling events. ...
... If you repeatedly calculate sample means for many independent random sampling events from a population, in the long run, you would be correct 95% of the time in claiming that the true mean is less than or equal to the 95% UCL of all those sampling events. ...
