Course Content
Learning Statistics with Python
Learning Statistics with Python
Confidence Interval
What is a Confidence Interval?
A confidence interval is a range of estimated values for an unknown parameter. To calculate it, a confidence level must be specified. The most common confidence level is 95%, although 90% and 99% confidence levels are also frequently used.
What Does a 95% Confidence Level Mean?
A 95% confidence level means that in 95% of cases, the estimate will fall within the lower and upper bounds of the interval.
Alpha Value
The confidence interval is typically equal to 1 minus alpha (1-a), where alpha represents the probability of a Type I error. Type I errors occur when we incorrectly reject a true null hypothesis.
Null and Alternative Hypotheses
The null and alternative hypotheses are assumptions used in statistical tests to make judgments based on data. In hypothesis testing, these hypotheses are mutually exclusive statements. Typically, we either attempt to reject or fail to reject the null hypothesis.
In this section, we will work with penguin data. By the end of this section, we will be able to confidently state that, with a "95% level of confidence, the mean penguin mass is...".
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