Interpreting confidence interval for the p-value

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Reference no: EM1316762

Interpreting the confidence interval for the given P-value.

Provide an appropriated response.

A weight loss center provided a loss for 72% of its participants. The center's leader decides to test a new weight loss strategy on a random sample size of 140 and found 109 participants lost weight. Should the center continue its new strategy? Test an appropriate hypothesis using = 0.02 and state your conclusion. Be sure the appropriate assumptions and conditions are satisfied before you proceed.

• Z = 1.54; P-value = 0.2136. The change is statistically significant. A 95% confidence interval is (70.4%, 85.3%). This is clearly lower than 72%. The chance of observing 109 or more participants of 140 is only 11.42% if the weight loss is really 72%.

• Z = 1.54; P-value = 0.0618. The change is statistically significant. A 90% confidence interval is (71.6%, 84.1%). This is clearly higher than 72%. The chance of observing 109 or more participants of 140 is only 5.71% if the weight loss is really 72%.

• Z = 1.54; P-value = 0.0618. The center should not continue with the new strategy. There is a 6.18% chance of having 109 or more of 140 participants in a random sample weigh less if in fact 72% do. The P-value of 0.0618 is greater than the alpha level of 0.02.

• Z = 1.54; P-value = 0.9382. The change is statistically significant. A 98% confidence interval is (69.0%, 86.7%). This is clearly higher than 72%. The chance of observing 109 or more participants of 140 is only 94.29% if the weight loss is really 72%.

Reference no: EM1316762

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