Answer:
The decision rule is
Fail to reject the null hypothesis
The conclusion is
The is no sufficient evidence to support the claim that the less than 1% of the cards are defective
Step-by-step explanation:
From the question we are told that
The sample size is [tex]n = 600[/tex]
The population proportion of defective samples is p = 0.01
The sample proportion of defective samples is [tex]\^ p = 0.03[/tex]
The level of significance is [tex]\alpha = 0.01[/tex]
The null hypothesis is [tex]H_o : p = 0.01[/tex]
The alternative hypothesis is [tex]H_a: p < 0.01[/tex]
Generally the test statistics is mathematically represented as
[tex]t = \frac{\^ p - p }{ \sqrt{ \frac{p( 1 - p )}{n} } }[/tex]
=> [tex]t = \frac{0.03 - 0.01 }{ \sqrt{ \frac{0.01( 1 - 0.01 )}{600} } }[/tex]
=> [tex]t = 0.00406[/tex]
From the z table the area under the normal curve to the left corresponding to 0.00406 is
[tex]p-value = P(Z < 0.00406 ) = 0.50162[/tex]
comparing the p-valve and the level of significance we see that the
[tex]p-value > \alpha[/tex] hence
The decision rule is
Fail to reject the null hypothesis
The conclusion is
The is no sufficient evidence to support the claim that the less than 1% of the cards are defective
