If we take samples from the population that has an unknown probability distribution, the sampling distribution will still be approximatelynormal if the sample size is large because of the Central Limit TheoremO TrueO False

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Answered: If we take samples from the population…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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The inferential statistics is used to compare the sample sets and estimate the probability that they belong to truly different populations as opposed to be different just due to a random chance. P-value is the outcome of a statistical calculation. P stands for probability. The 'p-value' always between 0 and 1. The p-value of 0 means that an event never occurs, and p-value of 1 means that an event occurs always. In biomedical scinces, a p-value of 0.05 or less is usually considered significant (meaning the differences in the data are likely not due to chance, the sample(s) are not from the same population, and the observed differences are likely real). Value: 1 The p value of 0.03 indicates significant difference in biomedical sciences. True False Check Answer Tails is a statistical parameter that used in statistical significance testing. There are one-tailed and two-tailed options for statistical test. The one-tailed option is used when the hypothesis predicts not only difference…
When using the central limit theorem for means with n = 98, it is not necessary to assume the distribution of the population data is normally distributed. True False
What does the central limit theorem say about the shape of the distribution of the sample means? O The distribution will be approximately normal when the sample size is large. The distribution will be approximately normal when the standard deviation of the sample means is the same as the population standard deviation. O The distribution will be approximately normal when the sample size is small. The distribution will be normal when all sample means within 2 standard deviations of the actual mean are considered. O The distribution will be approximately normal regardless of sample size.
You want to find the probability that people will return a shopping cart to the corral after loading the groceries in their vehicle. For a 4 hours period, you observe the number of people who returned their cart and the number who did not. A success in this case would be that the person returned their cart. Choose the best statistical tool to calculate this probability A. Use the Central Limit Theorem to find the probability that the sample mean exceeds a certain value B. Use the empirical rule to find the number of cars that bracket 68% of the data C. Calculate a confidence interval for the population mean D. Calculate the total number of successes divided by the total number of observations to find the observed probability
A sign on the pumps at a gas station encourages customers to have their oil checked, and claims that one out of 3 cars needs to have oil added. If this is true, what is the probability of each of the following: (a) What is the probability that at least two of the next 5 cars need oil? Probability = (b) What is the approximate probability that between 181 and 216 of the next 600 cars need oil (Use the Normal approximation technique)? Probability =
What is the difference between discrete and continuous probability distributions? What are six situations in which a variable of interest may be considered either continuous or discrete?
When using the central limit theorem for means with n = 60, it is not necessary to assume the distribution of the population data is normally distributed. True False
When using the central limit theorem for means with n = 69, it is not necessary to assume the distribution of the population data is normally distributed. True False
if we take samples from the population that has an unknown probability distribution, the sampling distribution will still be approximately normal even if the sample size is small because of the central limit theorem True or False
Suppose that you take a sample of size 40 from a population that is normally distributed. Can the sampling distribution of x̄ be approximated by a normal probability distribution? What if the population was not normally distributed, can the sampling distribution of x̄ be approximated by a normal probability distribution?
Suppose that the amount of time it takes a clerk to process an employment application is uniformly distributed between 5 and 12 minutes. What is the probability that the clerk will take exactly 7 minutes to process a randomly selected application?
Obtain the maximum likelihood estimate 0 of for the probability distribution.

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If we take samples from the population that has an unknown probability distribution, the sampling distribution will still be approximately normal if the sample size is large because of the Central Limit Theorem O True O False