Statistical Definitions and Statement: X, S^2, μ, σ^2, True or False

In summary, the random sample X1,...,Xn from a population with mean μ and variance σ^2 have different notations as the sample mean X and the sample variance S^2. X is an unbiased estimator for μ and the standard error of X is σ/(sqrt n) which can be estimated as S/sqrt(n).
  • #1
lina29
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Homework Statement


Let X1,…,Xn denote a random sample from a population with mean μ and variance σ^2. Assume that both μ and σ^2 are finite but unknown. Let X denote the sample mean and S^2 denote the sample variance. Are the following statements true or false?
A-There is no difference between X and μ - the two are different notations for the same quantity.
B- There is no difference between S^2 and σ^2 - the two are different notations for the same quantity.
C- X is an unbiased estimator for μ.
D- The standard error of X is σ/(sqrt n) which can be estimated as S/sqrt(n).


Homework Equations





The Attempt at a Solution


I believe I have the right answers I just want to double check
A- yes
B- yes
C- yes
D- no
 
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  • #2
Actually, as I understood, a),b) are false. If they were equal, confidence intervals would not be necessary. For c),d) , there are actual formulas, so that you can verify.
 
  • #3
Thank you!
 

Related to Statistical Definitions and Statement: X, S^2, μ, σ^2, True or False

1. What is the definition of mean in statistics?

The mean in statistics is the measure of central tendency that represents the average value of a dataset. It is calculated by adding all the values in the dataset and dividing by the number of values.

2. What does standard deviation mean in statistics?

Standard deviation in statistics is a measure of how spread out the data points are from the mean. It indicates the variability or dispersion of the data from the average.

3. What is the difference between correlation and causation?

Correlation is a statistical measure that indicates the strength and direction of the relationship between two variables. Causation, on the other hand, refers to a cause-and-effect relationship where one variable directly influences the other.

4. What is the definition of probability in statistics?

Probability in statistics is the likelihood of an event occurring. It is calculated by dividing the number of favorable outcomes by the total number of possible outcomes.

5. What is the difference between descriptive and inferential statistics?

Descriptive statistics involves summarizing and describing a dataset, while inferential statistics involves making inferences or predictions about a larger population based on a sample of the data.

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