A fandom sampie of 1020 adults in a certain large country was asked "Do you pretty much think televisions are a necessity or a luxury you could do without?" Of the 1026 adults surveyed, 526 indicated that televisions are a luxury they could do without. Com parts (a) through (e) below Click here to view the standard normal distribution table (page1). Click here to view the standard normal distribution table (page 2). (a) Obtain a point estimate for the population proportion of adults in the country who believe that televisions are a luxury they could without (Round to three decimal places as needed) (b) Verity that the requirements for constructing a confidence interval about p are satisfied The sample (Round to three decimal places as needed) Va simple random sample, the value of vis which is v 10, and the V less than or equal to 5% of the (c) Construct and interpret a 95% confidence interval for the population proportion (Type integers or decimals rounded to three decimal places as needed. Use ascending order) adults in the country who believe that televisions are a luxury they could do without. Select the correct choice below and fill in any answer boxes within your choice O A. There is a % probability the proportion of adults in the country who believe that televisions are a luxury they could do without is between and O B. We are % confident the proportion of adults in the country who believe that televisions are a luxury they could do without is between and (d) is it possible that a supermajority (more than 60%) of adults in the country believe that television is a luxury they could do without? Is it likely? v that a supermajority It is (Type an integer or a decimal. Do not round) adults in the country believe that television is a luxury they could do without because the 95% confidence interval
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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