We Now Have Two Ways To Examine Variability Simulation Or The Normal Model If Conditions Are Met We Know That The Am 1 (36.53 KiB) Viewed 41 times
We Now Have Two Ways To Examine Variability Simulation Or The Normal Model If Conditions Are Met We Know That The Am 2 (34.36 KiB) Viewed 41 times
We Now Have Two Ways To Examine Variability Simulation Or The Normal Model If Conditions Are Met We Know That The Am 3 (34.36 KiB) Viewed 41 times
We now have two ways to examine variability: simulation or the normal model (if conditions are met.) We know that the amount of variability in random samples depends on the sample size. Let's examine what happens when we select samples of 40 freshmen (n=40). Then let's see what happens when we collect larger samples of 300(n=300) 2) Sample size of 40: Here are the results from a coinflipping simulation in StatCrunch with probability of a head set to 0.20. Each "run" is 40 coin flips representing a random sample of 40 community college freshmen. a) With a sample of 40 freshmen, is a proportion of 0.25 unusual when the population proportion is 0.20 ? How do you know? b) Based on the simulation, what is the probability that a random sample of 40 has 25% or more with a credit card? How do you know? c) What does this suggest about our claim? Does our sample data provide strong evidence that more than 20% of the entire population own a credit card? Why or why not?
We now have two ways to examine variability: simulation or the nomal model if conditions are met.) We know that the amount of variability in random samples depends on the sample size. Let's examine what happens when we select samples of 40 freshmen (nwi0). Then let's see what happens when we collect larger samples of 300(n=300) 2) Sample size of 40 : Here are the results from a coin-flipping simulation in StatCrunch with probability of a head set to 0.20. Each "run" is 40 coin flips representing a random sample of 40 community college freshmen. a) With a sample of 40 freshmen, is a proportion of 0.25 unusual when the population proportion is 0.20 ? How do you know? b) Bascd on the simalation, what is the probability that a random sample of 40 has 25% or more with a credit card? How do you know? c) What does this suggest about our claim? Does our sample data provide strong, evidence that more than 20 of of the entire poputation own a credit card Why of why not?
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