PPT-Sampling and Confidence Interval

How can it be that mathematics being after all a product of human thought independent of experience is so admirably adapted to the objects of reality Albert Einstein Some parts of these slides were prepared based on . Confidence Intervals. Lecture Summary. Last lecture, we talked about summary . statistics. and how “good” they were in estimating the . parameters. Risk, bias, and variance. Sampling distribution. Reports.  . How are we doing?. Sort the types of error into sampling and non-sampling errors, then match the situations to the types of error.. Some concepts which teachers and students find difficult. Excel. GrowingKnowing.com © 2011. 1. GrowingKnowing.com © 2011. Estimates. We are often asked to predict the future!. When will you complete your team project?. When will you make your first million dollars?. Lecture #. 16. . Thursday. , October . 13, . 2016. Textbook: Sections . 9.3, 9.4. , 10.1, 10.2. • Define standard error, relate it to both standard deviation and sampling distribution ideas.. • . . Interval. You. . sample. 36 . apples. . from. . your. . farm’s. . harvest. of . over. 200,000 . apples. . . The. . mean. . weight. of . the. . sample. is 112 . grams. (. with. 40 gram . Intervals for Proportions. Ch. 19 . Notes. AP Statistics. Chapter 19 Textbook HW. p.455. #2,4,6,13 (Goal for Tonight). #7,8,14,18,22,26,30,32,35,36. P. 443 Graphs. Inference. To infer means to draw a conclusion.. How . can it be that mathematics, being after all a product of human thought independent of experience, is so admirably adapted to the objects . of reality. Albert Einstein. Some parts of these slides were prepared based on . 16. . Thursday. , October . 13, . 2016. Textbook: Sections . 9.3, 9.4. , 10.1, 10.2. • Define standard error, relate it to both standard deviation and sampling distribution ideas.. • . Describe the sampling distribution of a sample proportion. GrowingKnowing.com © 2011. 1. GrowingKnowing.com © 2011. Estimates. We are often asked to predict the future!. When will you complete your team project?. When will you make your first million dollars?. Section 8.1. Confidence Intervals: The Basics. After this section, you should be able to…. INTERPRET a confidence level. INTERPRET a confidence interval in context. DESCRIBE how a confidence interval gives a range of plausible values for the parameter. Confidence Intervals on . and. An interval estimator is a formula that tells us how to use sample data to calculate an interval that estimates a population parameter.. The confidence coefficient is the probability that an interval estimator encloses the population parameter.. (b) . The 95% confidence interval is 0.56 to 0.62. We are 95% confident that the interval from 0.52 to 0.62 captures the true proportion of those who would like to lose weight. . (c) . If we were to repeat the sampling procedure many times, about 95% of the confidence intervals computed would contain the true proportion of those who would like to lose weight.. Chapter 6 Confidence Intervals Sections 6-1 and 6-2 Confidence Intervals for Large and Small Samples   VOCABULARY: Point Estimate – A single value estimate for a population parameter. sources for data . for game analytics?. What are two main . sources for data . for game analytics?. Quantitative. – instrumented game. Qualitative. – subjective evaluation. What steps are in the .