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BESC 3010 POSTTEST 3 QUESTIONS AND ANSWERS | LATEST UPDATE | 2024/2025 | GRADED A+
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BESC 3010 POSTTEST 3 QUESTIONS AND ANSWERS | LATEST UPDATE | 2024/2025 | GRADED A+ What is the definition of a statistic? A statistic is a numerical characteristic or measure obtained by using the data values from a sample. What is the difference between a parameter and a statistic? ...

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  • November 4, 2024
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  • 2024/2025
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BESC 3010 POSTTEST 3 QUESTIONS
AND ANSWERS | LATEST UPDATE |
2024/2025 | GRADED A+
What is the definition of a statistic?


✔✔A statistic is a numerical characteristic or measure obtained by using the data values from a

sample.




What is the difference between a parameter and a statistic?


✔✔A parameter is a numerical characteristic of a population, while a statistic is a numerical

characteristic of a sample drawn from that population.




How do you calculate the mean of a data set?


✔✔The mean is calculated by summing all the data points and dividing by the number of points

in the dataset.




What does the standard deviation measure?


✔✔The standard deviation measures the amount of variability or dispersion in a set of data

values, indicating how much the values deviate from the mean.




1

, What is a skewed distribution, and how can you identify it?


✔✔A skewed distribution is one where the data points are not symmetrically distributed around

the mean. It can be identified by comparing the mean and median; in a right-skewed distribution,

the mean is greater than the median.




What is the purpose of a hypothesis test?


✔✔The purpose of a hypothesis test is to determine whether there is enough statistical evidence

in a sample of data to support a specific claim about the population.




How do you interpret a confidence interval?


✔✔A confidence interval provides a range of values that is believed to contain the true

population parameter with a certain level of confidence, usually expressed as a percentage.




What is the significance of the p-value in hypothesis testing?


✔✔The p-value indicates the probability of observing the test results under the null hypothesis.

A low p-value suggests that the null hypothesis may be rejected.




What is the difference between Type I and Type II errors?




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