Statistics Final Exam
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Mathematics
•
9th Grade - University
•
Hard
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15 questions
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1.
FLASHCARD QUESTION
Front
What is a point estimate in statistics?
Back
A point estimate is a single value given as an estimate of a population parameter. For example, the proportion of 'yes' voters in a sample can be used as a point estimate for the proportion in the entire population.
2.
FLASHCARD QUESTION
Front
How do you calculate the proportion of 'yes' voters?
Back
The proportion of 'yes' voters is calculated by dividing the number of 'yes' votes by the total number of votes. For example, if there are 1757 'yes' votes out of 2584 total votes, the proportion is 1757/2584 = 0.6799535604.
3.
FLASHCARD QUESTION
Front
What is the significance of the mean in a normal distribution?
Back
The mean is the average value of a dataset and serves as the center of the normal distribution. In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean.
4.
FLASHCARD QUESTION
Front
What does a standard deviation indicate in statistics?
Back
Standard deviation measures the amount of variation or dispersion in a set of values. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation indicates that the values are spread out over a wider range.
5.
FLASHCARD QUESTION
Front
What is the z-score in statistics?
Back
A z-score indicates how many standard deviations an element is from the mean. It is calculated as (X - μ) / σ, where X is the value, μ is the mean, and σ is the standard deviation.
6.
FLASHCARD QUESTION
Front
What is the probability of selecting a value greater than a certain z-score in a normal distribution?
Back
The probability can be found using z-tables or normal distribution calculators, which provide the area under the curve to the left of the z-score. The area to the right gives the probability of selecting a value greater than that z-score.
7.
FLASHCARD QUESTION
Front
What is the Central Limit Theorem?
Back
The Central Limit Theorem states that the sampling distribution of the sample mean will be normally distributed, regardless of the shape of the population distribution, provided the sample size is sufficiently large (usually n > 30).
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