Question

Networking - A 2016 study conducted by LinkedIn found that 85% of all jobs are filled via networking - the process of interacting with others to develop professional contacts. Marie is skeptical of this study, and believes that the actual percentage of jobs filled by networking is actually less than 85%. Marie randomly samples recently filled jobs and finds that 80% of them were filled by networking. She conducts a hypothesis test. The p-value for the test is calculated to be 0.143. Which of the statements below are correct interpretations of the p-value? You should choose all that are correct interpretations. The p-value is the probability of obtaining a sample result at least as or more in favor of the alternative hypothesis if the null hypothesis is true. This p-value suggests that based on this sample there is little evidence that the null model is not compatible with the data. If we repeat the hypothesis test many times, the p-value is the proportion of times our test statistic will be close to the expected value of the null distribution. The p-value is the proportion of times in repeated sampling that the alternative hypothesis is true.

Answer 1

• A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you reject the null hypothesis.

• A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis.

• p-values very close to the cutoff (0.05) are considered to be marginal (could go either way). Always report the p-value so your readers can draw their own conclusions.

Simply the P Value is the one which is support the Null Hypothesis.

In the above problem, The phone value suggest that the there is little evidence that the null model is not compatible with the Data.

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