Uploaded April 2013 | Updated September 2026, 1 hour ago
An introduction to confidence intervals for the population mean mu. These methods are appropriate when we are sampling from a normally distributed population, where the population standard deviation sigma is known. When the population standard deviation is not known, as is usually the case, we need to use a slightly different method (a method based on the t distribution).
The 2D:4D ratio data (from the right hand) is simulated data with the same summary statistics as found in:
Stevenson et al. (2007). Attention Deficit/Hyperactivity Disorder (ADHD) Symptoms and Digit Ratios in a College Sample. American Journal of Human Biology. 19:41-50.
For those that use R, here is the R code to find the values given in the video:
To find the value of a standard normal random variable that has an area of 0.025 to the left,
qnorm(.025)
[1] -1.959964
To find the value of a standard normal random variable that has an area of 0.025 to the right,
qnorm(.975)
[1] 1.959964
To find the value of a standard normal random variable that has an area of 0.05 to the left,
qnorm(.05)
[1] -1.644854
To find the value of a standard normal random variable that has an area of 0.05 to the right,
qnorm(.95)
[1] 1.644854
An introduction to confidence intervals for the population mean mu. These methods are appropriate when we are sampling from a normally distributed population, where the population standard deviation sigma is known. When the population standard deviation is not known, as is usually the case, we need to use a slightly different method (a method based on the t distribution).
The 2D:4D ratio data (from the right hand) is simulated data with the same summary statistics as found in:
Stevenson et al. (2007). Attention Deficit/Hyperactivity Disorder (ADHD) Symptoms and Digit Ratios in a College Sample. American Journal of Human Biology. 19:41-50.
For those that use R, here is the R code to find the values given in the video:
To find the value of a standard normal random variable that has an area of 0.025 to the left,
qnorm(.025)
[1] -1.959964
To find the value of a standard normal random variable that has an area of 0.025 to the right,
qnorm(.975)
[1] 1.959964
To find the value of a standard normal random variable that has an area of 0.05 to the left,
qnorm(.05)
[1] -1.644854
To find the value of a standard normal random variable that has an area of 0.05 to the right,
qnorm(.95)
[1] 1.644854
