Step 1 :Identify the null hypothesis (H0) as \(\mu = 1000\) hic and the alternative hypothesis (H1) as \(\mu < 1000\) hic.
Step 2 :Calculate the sample mean (\(\bar{x}\)) as \(\frac{738 + 644 + 1260 + 642 + 555 + 505 + 0}{7} = 620.571\).
Step 3 :Calculate the sample standard deviation (s) as \(\sqrt{\frac{(738-620.571)^2 + (644-620.571)^2 + (1260-620.571)^2 + (642-620.571)^2 + (555-620.571)^2 + (505-620.571)^2 + (0-620.571)^2}{6}} = 394.261\).
Step 4 :Calculate the test statistic (t) as \(\frac{620.571 - 1000}{394.261 / \sqrt{7}} = -2.428\).
Step 5 :Find the P-value as 0.0254.
Step 6 :Since the P-value (0.0254) is less than the significance level (0.05), reject the null hypothesis.
Step 7 :\(\boxed{\text{There is evidence to support the claim that the sample is from a population with a mean less than 1000 hic.}}\)
Step 8 :\(\boxed{\text{The results suggest that not all child booster seats meet the safety requirement of less than 1000 hic.}}\)