Calculating Confidence Interval
Confidence interval can be easily calculated by following the steps added below:
Step 1: Collect Data: Collect the sample data.
Step 2: Calculate Sample Mean and Standard Deviation: Calculate the average and standard deviation of the sample.
Step 3: Choose Confidence Level: Choose a confidence level, such as 90%, 95%, or 99%.
Step 4: Find Critical Value: Refer to a table of z-scores or t-scores to find the corresponding value based on your chosen confidence level and sample size.
Step 5: Calculate Margin of Error: Use Formula: Margin of Error = Critical Value × (Sample Standard Deviation / √Sample Size).
Step 6: Compute Confidence Interval: Add and subtract the margin of error from the sample mean to get the interval.
Step 7: Interpret Results: Formulate the confidence interval, for example: “We are 95% confident that the true population mean falls within this interval.”
This is explained by the example added below:
Confidence Intervals for Population Mean and Proportion
Confidence intervals for population mean estimate the range within which the true mean lies, based on sample data. For proportions, they estimate the range within which the true population proportion lies. Both intervals reflect statistical certainty about the estimates.
This article explains confidence intervals, their calculation, interpretation, and applications for population means and proportions in statistics.
Table of Content
- Defining Confidence Interval
- Formula for Confidence Interval
- Confidence Interval Table
- Calculating Confidence Interval
- Example of Confidence Interval Calculation