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UCF FINAL QMB 3200 - Only Ch 17-10 &14 Exam Questions And Correct Answers.

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Sampling from a finite population: - Answer choosing a simple random sample of size n from a finite population of size N where each possible sample of size n has the same probability of being selected. 1. Assign a random number to each element of the population. 2. Select the n elements corresponding to the n smallest random numbers. Sampling from an infinite population: - Answer A random sample of size n form an infinite population is a sample selected meeting the following: 1. Each element comes from the same population; 2. Each element is selected independently. How would we take a finite random sample in excel? - Answer Use the formula =rand() which will assign a random number between 0 and 1 for each data point, then copy and paste the random number column (this is to ensure that the random numbers don't change when you move it around- paste as values, not a formula) then sort the data by smallest to largest of the random number values then select the smallest numbers- for example, if the sample is 30- from the top down select thirty data points. When you sort the data make sure if your data has headers to check the box indicating this before you sort. Point Estimation - Answer calculate the mean, standard deviation and proportion. The resulting values are point estimators for each. So if we had a mean of 6- the point estimate would be 6 and the estimator would be the mean. Same if we were to use standard deviation or proportion- (which is how many out of a certain number of data do a certain act.)- for example 6/100 people drink tea so 6% is our proportion.

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Publié le
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Écrit en
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UCF FINAL QMB 3200 - Only Ch 17-10
&14 Exam Questions And Correct
Answers.
Sampling from a finite population: - Answer choosing a simple

random sample of size n from a finite population of

size N where each possible sample of size n has the

same probability of being selected.



1. Assign a random number to each element of the

population.

2. Select the n elements corresponding to the n

smallest random numbers.



Sampling from an infinite population: - Answer A random sample of size n form an infinite

population is a sample selected meeting the

following:

1. Each element comes from the same population;

2. Each element is selected independently.



How would we take a finite random sample in excel? - Answer Use the formula =rand() which
will assign a random number between 0 and 1 for each data point, then copy and paste the
random number column (this is to ensure that the random numbers don't change when you
move it around- paste as values, not a formula) then sort the data by smallest to largest of the
random number values then select the smallest numbers- for example, if the sample is 30- from
the top down select thirty data points.



When you sort the data make sure if your data has headers to check the box indicating this
before you sort.



Point Estimation - Answer calculate the mean, standard deviation and

proportion. The resulting values are point estimators

for each.

, Variable used to describe proportion - Answer P for population proportion

p(bar)- for sample proportion



Sampling distribution - Answer a distribution of statistics obtained by selecting all the possible
samples of a specific size from a population



The Sampling Distribution of ̅ 𝑥 is the probability

distribution of all possible values of the sample mean

( ̅ 𝑥).



Standard Deviation of ̅ 𝑥 is denoted as 𝜎 ̅𝑥; and its

value depends on whether the population is finite or

infinite.



What is the standard error of the

mean - Answer the standard deviation of xbar- or the mean



Form/Shape of the Sampling Distribution of xbar - Answer The form/shape of the sampling
distribution of ̅ 𝑥 has

two possibilities:

1. The population has a normal distribution;

2. The population does not have a normal

distribution.



When the population has a normal distribution, the

sampling distribution of ̅ 𝑥 is normally distributed for

any sample size.



When the population does not have a normal

distribution the central limit theorem helps identify


the shape of the sampling distribution of ̅ 𝑥.
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