AC

Arun Chatterjee

8 months ago

Quantitative Techniques Statistics Standard Error

How can the standard error be used to calculate confidence intervals for a dataset?

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6 Comments

Discussion

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Chidinma
8 months ago

The standard error (SE) of a statistic (most often the mean) is a measure of the amount that a sample statistic would vary if different samples were taken from the same population. Confidence intervals can be calculated using the standard error by constructing a range around the sample mean that gives the probability that the true population mean lies within that range.

To calculate a confidence interval around a sample mean, you would typically use the following formula:

Confidence Interval = Sample Mean ± (Critical Value * Standard Error)

where the critical value corresponds to the desired level of confidence (e.g., 1.96 for a 95% confidence interval in a normal distribution).

Examples and further explanations can be found at:

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KM

Kalyani Mehra
8 months ago

Interesting! I never understood how CI calculations were related to the SE. Makes sense now.
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Sneha Malpani
8 months ago

Could someone elaborate on choosing the right critical value for different confidence levels?
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Narmada Sharaf
7 months ago

How does sample size affect the standard error and subsequently the confidence intervals?
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DBS

Daanish Bhai Sethi
7 months ago

Thank you for the examples, they made the concept much clearer for a visual learner like me.
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BRM

Balaji Ram Mahajan
7 months ago

This is really helpful, thanks for the formula!
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