The document outlines the procedure for hypothesis testing which includes setting up the null and alternative hypotheses, determining the test statistic, critical region, and making a decision. It then provides an example of testing whether the mean longevity of lightbulbs from a sample of 90 bulbs is equal to the manufacturer's claim of 4 years using a 5% significance level. Finally, it presents a problem about testing if a sample of 60 MBA students with a mean score of 2.8 came from a population with a mean of 2.4 and constructing a 99% confidence interval.

1. Procedure of Hypothesis testing
• 1. Set up a null and alternative hypothesis
• 2. set up a suitable significance level
• 3. Determine a suitable test statistics
• 4. Determine the critical region.
• 5. Do the calculation of test statistics using
sample information
• 6. Make a decision based on the whole
procedure

2. Test of Hypothesis: Mean(μ)
• 1. A bulb manufacturing company claims that
the average longevity of their bulbs is 4 years
with standard deviation of 0.16 years.
• A random sample of 90 bulbs gave a mean
longevity of 3.45 years.
• Does the sample mean justify the claim of the
manufacturer? Use 5% level of significance.

3. Tabulated Value
Critical value
of Z
Level of
significance
1%
Level of
significance
5%
Level of
significance
10%
One tail test -2.33 or 2.33 -1.64 or 1.64 -1.28 or 1.28
Two tail test -2.58 and 2.58 -1.96 and 1.96 -1.64 and 1.64

4. Problem
• 2. The mean and standard deviation of scores
obtained from a random sample of 60 students of
MBA were 2.8 and 0.35 respectively.
• Can we conclude that the sample has come from
the entire group of students which has a mean
score of 2.4?
• Use 1% level of significance and compute 99%
confidence interval for the mean.