The linear probability model‚ ctd. When Y is binary‚ the linear regression model Yi = β0 + β1Xi + ui is called the linear probability model. • The predicted value is a probability: • E(Y|X=x) = Pr(Y=1|X=x) = prob. that Y = 1 given x • Yˆ = the predicted probability that Yi = 1‚ given X • β1 = change in probability that Y = 1 for a given ∆x: Pr(Y = 1 | X = x + ∆x ) − Pr(Y = 1 | X = x ) β1 = ∆x 5 Example: linear probability model‚ HMDA data Mortgage denial v. ratio of debt payments to income (P/I
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Chapter 1 The Problem and Its Background Introduction Changes are permanent thing on earth. Are the people is ready enough to accept the changes on the educational system? The current opening of classes here in the Philippines usually starts from June to March but our lawmakers want to amend the opening of classes. The existing school calendar which spans from June to March is often disrupted as destructive typhoons plague the region during the rainy season that’s why our lawmakers decided to
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Week Four Discussion 2 1. In your own words‚ describe two main differences between classical and empirical probabilities. The differences between classical and empirical probabilities are that classical assumes that all outcomes are likely to occur‚ while empirical involves actually physically observing and collecting the information. 2. Gather coins you find around your home or in your pocket or purse. You will need an even number of coins (any denomination) between 16 and 30. You do not
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Probability Games Walter J Mahoney MTH 157 1/20/2013 Andrea Hayes Probability is a fascinating math concept. It can be applied in many aspects of our students’ daily lives. As the world of technology continues to grow‚ teaching of many math
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Chapter 6 Continuous Probability Distributions Case Problem: Specialty Toys 1. Information provided by the forecaster At x = 30‚000‚ [pic] [pic] Normal distribution [pic] [pic] 2. @ 15‚000 [pic] P(stockout) = 1 - .1635 = .8365 @ 18‚000 [pic] P(stockout) = 1 - .3483 = .6517 @ 24‚000 [pic] P(stockout) = 1 - .7823 = .2177 @ 28‚000 [pic]
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Chapter 3 Probability True/False 1. A contingency table is a tabular summary of probabilities concerning two sets of complementary events. Answer: True Difficulty: Medium 2. An event is a collection of sample space outcomes. Answer: True Difficulty: Easy 3. Two events are independent if the probability of one event is influenced by whether or not the other event occurs. Answer: False Difficulty: Medium 4. Mutually exclusive events have a nonempty
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respondent is selected at random‚ what is the probability that he or she a. prefers to order at the drive-through? b. is a male and prefers to order at the drive-through? c. is a male or prefers to order at the drive-through? d. Explain the difference in the results in (b) and (c). e. Given that a respondent is a male‚ what is the probability that he prefers to order at the drive-through? f. Given that a respondent is a female‚ what is the probability that she prefers to order at the drive-through
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Probability Concepts 1. Fundamental Concepts of Probability 2. Mutually Exclusive and Collectively Exhaustive 3. Statistically Independent and Dependent Events 4. Bayes’Theorem Learning Objectives • Understand the basic foundations of probability analysis • Learn the probability rules for conditional probability and joint probability • Use Bayes’ theorem to establish posterior probabilities Reference: Text Chapter 2 Introduction • Life is uncertain; we are note sure what the
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Chapter 1 The Probability in Everyday Life In This Chapter Recognizing the prevalence and impact of probability in your everyday life Taking different approaches to finding probabilities Steering clear of common probability misconceptions You’ve heard it‚ thought it‚ and said it before: “What are the odds of that happening?” Someone wins the lottery not once‚ but twice. You accidentally run into a friend you haven’t seen since high school during a vacation in Florida. A cop pulls you over the
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A group of investors wants to develop a chain of fast-food restaurants. In determining potential costs for each facility‚ they must consider‚ among other expenses‚ the average monthly electric bill. They decide to sample some fast-food restaurants currently operating to estimate the monthly cost of electricity. They want to be 90% confident of their results and want the error of the interval estimate to be no more than $100. They estimate that such bills range from $600 to $2‚500. How large a sample
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