When testing gas pumps for accuracy, fuel-quality enforcement specialists tested pumps and found that 1334 of them were not pumping accurately (within 3.3 oz when 5 gal is pumped), and 5663 pumps were accurate. Use a 0.01 significance level to test the claim of an industry representative that less than 20% of the pumps are inaccurate. Use the P-value method and use the normal distribution as an approximation to the binomial distribution.

We accept H0, Therefore we conclude that there is no evidence to support the claim that less than 20% of the pumps are inaccurate.

Step-by-step explanation:

We have,

x = 1334

n = 1334 + 5663 = 6997

we have to:

p = x / n = 1334/6997 = 0.1907

The hypothesis is:

H0: P = 0.20

H1: P <0.20

P = 0.2 and Q = 1 - P = 0.8

the test statistic is:

Z = (p - P) / [(P * Q / n) ^ (1/2)]

replacing:

Z = (0.1907 - 0.20) / [(0.2 * 0.8 / 6997) ^ (1/2)]

Z = -1.96

now, the p-value is

P = 0.0250, from normal table, attached

Here p-value> 0.01, so we accept H0, Therefore we conclude that there is no evidence to support the claim that less than 20% of the pumps are inaccurate.

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step-by-step explanation:

smple

50- 250 is correct i did that one too

step-by-step explanation: