D using the random babies applet approximate the

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(d) Using the Random Babies applet, approximate the expected value for how many of the eight mothers will receive the correct baby. How does your approximation compare to the situation with 4 mothers?
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¤ Chance/Rossman, 2015 ISCAM III Chapter 1 19 CHAPTER 1: ANALYZING ONE CATEGORICAL VARIABLE In this chapter, you will begin to analyze results from statistical studies and focus on the process of statistical inference. In particular, you will learn how to assess evidence against a particular claim about a random process. Section 1: Analyzing a process probability Investigation 1.1: Friend or foe ± Inference for a proportion Probability Exploration: Mathematical Model Probability Detour: Binomial Random Variables Investigation 1.2: Do names match faces ± Bar graph, hypotheses, binomial test (technology) Investigation 1.3: Heart transplant mortality ± Factors affecting p-value Investigation 1.4: Kissing the right way ± Two-sided p-values Investigation 1.5: Kissing the right way (cont.) ± Interval of plausible values Investigation 1.6: Improved baseball player ± Types of error and power Probability Exploration: Exact Binomial Power Calculations Section 2: Normal approximations for sample proportions In vestigation 1.7: Reese’s pieces ± Normal model, Central Limit Theorem Probability Detour: Normal Random Variables Investigation 1.8: Is ESP real? ± Normal probabilities, z -score Investigation 1.9: Halloween treat choices ± Test statistic, continuity correction Investigation 1.10: Kissing the right way (cont.) ± z -interval, confidence level Investigation 1.11: Heart transplant mortality (cont.) ± Plus Four/Adjusted Wald Section 3: Sampling from a finite population Investigation 1.12: Sampling words ± Biased and random sampling Investigation 1.13: Literary Digest ± Issues in sampling Investigation 1.14: Sampling words (cont.) ± Central Limit Theorem for p ˆ Investigation 1.15: Freshmen Voting Patterns Nonsampling errors, hypergeometric distribution Probability Detour: Hypergeometric Random Variables Investigation 1.16: Teen hearing loss ± One sample z -procedures Investigation 1.17: Cat households ± Practical significance Investigation 1.18: Female senators ± Cautions in inference Example 1.1: Predicting Elections from Faces Example 1.2: Cola Discrimination Example 1.3: Seat Belt Usage Appendix: Stratified random sampling Investigating Statistical Concepts, Applications, and Methods
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Chance/Rossman, 2015 ISCAM III Investigation 1.1 20 SECTION 1: ANALYZING A PROCESS PROBABILITY In this investigation you will be introduced to a basic statistical investigation as well as some ideas and terminology that you will utilize throughout the course. You will combine ideas from the preliminary investigations: examining distributions of data and simulating models of random processes to help judge how unusual an observation would be for a particular probability model.
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