Lower Tail Test of Population Mean with Unknown Variance
The null hypothesis of the lower tail test of the population mean can be expressed as follows:
where μ0 is a hypothesized lower bound of the true population mean μ.
Suppose the manufacturer claims that the mean lifetime of a light bulb is more than 10,000 hours. In a sample of 30 light bulbs, it was found that they only last 9,900 hours on average. Assume the sample standard deviation is 125 hours. At .05 significance level, can we reject the claim by the manufacturer?
The null hypothesis is that μ ≥ 10000. We begin with computing the test statistic.
> mu0 = 10000 # hypothesized value
> s = 125 # sample standard deviation
> n = 30 # sample size
> t = (xbar−mu0)/(s/sqrt(n))
> t # test statistic
We then compute the critical value at .05 significance level.
The test statistic -4.3818 is less than the critical value of -1.6991. Hence, at .05 significance level, we can reject the claim that mean lifetime of a light bulb is above 10,000 hours.
Instead of using the critical value, we apply the pt function to compute the lower tail p-value of the test statistic. As it turns out to be less than the .05 significance level, we reject the null hypothesis that μ ≥ 10000.