Review Chapter 5 and 6
... researcher suspects that the mean monthly cell phone bill is different today. (a) State the null and alternative hypotheses. (b) Explain what it would mean to make a Type I error. Choose the correct answer below. a. The sample evidence led the researcher to believe the mean monthly cell phone bill i ...
... researcher suspects that the mean monthly cell phone bill is different today. (a) State the null and alternative hypotheses. (b) Explain what it would mean to make a Type I error. Choose the correct answer below. a. The sample evidence led the researcher to believe the mean monthly cell phone bill i ...
1_ClassNotes
... The mean (μ), or expected value, is π and the variance can be calculated as π (π-1), which in this case, will be 0.3(0.7) or 0.21. You can see that in this type of distribution the variance and the mean cannot be independent—that is, the variance is tied to the mean. This is one key difference betwe ...
... The mean (μ), or expected value, is π and the variance can be calculated as π (π-1), which in this case, will be 0.3(0.7) or 0.21. You can see that in this type of distribution the variance and the mean cannot be independent—that is, the variance is tied to the mean. This is one key difference betwe ...
ehw8
... 3. Refer to question 2. Could the results of these interviews be used to infer responses of the population of high school principals in New England? a. Yes b. No Use this information for questions 4 and 5: In order to assess the membership’s attitudes about a new Supreme Court decision, a local bar ...
... 3. Refer to question 2. Could the results of these interviews be used to infer responses of the population of high school principals in New England? a. Yes b. No Use this information for questions 4 and 5: In order to assess the membership’s attitudes about a new Supreme Court decision, a local bar ...
Significance, Importance, and Undetected Differences
... Rates of heart attack: 9.4 per 1000 for aspirin group and 17.1 per 1000 for placebo group, difference < 8 people per 1000, about 1 less heart attack for every 125 who took aspirin. Relative risk: Aspirin group had half as many heart attacks; so could cut risk almost in half. Estimated relative risk ...
... Rates of heart attack: 9.4 per 1000 for aspirin group and 17.1 per 1000 for placebo group, difference < 8 people per 1000, about 1 less heart attack for every 125 who took aspirin. Relative risk: Aspirin group had half as many heart attacks; so could cut risk almost in half. Estimated relative risk ...
Carrie`s Section Slides (10/5)
... • LRL: lower real limit of the interval in which the score falls (half-way between the lowest number in that interval and the highest number in the next lowest interval) • h: interval size ...
... • LRL: lower real limit of the interval in which the score falls (half-way between the lowest number in that interval and the highest number in the next lowest interval) • h: interval size ...
Exam 3A Fall 2002
... b) (8 pts) the sample size n that was used in the study. c) (8 pts) Determine the sample size to be 99% confident that the error of estimation is within .05 if the company has no idea about the true population proportion. 3. (15 pts) Weights from a sample of 11 female wolves are recorded and the mea ...
... b) (8 pts) the sample size n that was used in the study. c) (8 pts) Determine the sample size to be 99% confident that the error of estimation is within .05 if the company has no idea about the true population proportion. 3. (15 pts) Weights from a sample of 11 female wolves are recorded and the mea ...
Chapter 4 Statistical inferences
... the population parameter is likely to occur within that range at a specified probability. • Specified probability is called the level of confidence. • States how much confidence we have that this interval contains the true population parameter. The confidence level is denoted by (1-α)×100% • Example ...
... the population parameter is likely to occur within that range at a specified probability. • Specified probability is called the level of confidence. • States how much confidence we have that this interval contains the true population parameter. The confidence level is denoted by (1-α)×100% • Example ...
Lab 9: z-tests and t-tests
... mu.hat<-mean(leadIQ$IQ) s<-sd(leadIQ$IQ) n<-length(leadIQ$IQ) t<-(mu.hat-100)/(s/sqrt(n)) 2*pt(t,n-1) mu.hat+qt(c(.025,.975),n-1)*s/sqrt(n) # Using t-test function (good for when given data) t.test(leadIQ$IQ,mu=100,alternative="two.sided") ...
... mu.hat<-mean(leadIQ$IQ) s<-sd(leadIQ$IQ) n<-length(leadIQ$IQ) t<-(mu.hat-100)/(s/sqrt(n)) 2*pt(t,n-1) mu.hat+qt(c(.025,.975),n-1)*s/sqrt(n) # Using t-test function (good for when given data) t.test(leadIQ$IQ,mu=100,alternative="two.sided") ...
