(a) Because the sample size is smal, the manager must verify that the wait time is normally distributed and the sample does not contain any outliers. The normal probability plot is shown below and the sample correlation coefficient is known to ber=0.989. Are the conditions for testing the hypothesis satisfied? the conditions V satisfied. The normal probability plot V linear enough, since the correlation coefficient is V than the critical value. In addition, a boxplot does not show any outliers. AExpected soore 1- 0- 60 90 105 Critical values Time (sec) (b) is the new system effective? Conduct a hypothesis test using the P-value approach and a level of significance of a = 0.1. Sample Size, n Critical Value 0.941 0.944 0.946 First determine the appropriate hypotheses. Sample Size, n Critical Value 0.880 16 Hạ: 85 4 H, 854 0 888 0.898 0.906 0.912 17 18 19 Họ: 8 0.949 20 0.951 0.952 0.954 0.956 0.957 0.959 0.960 10 11 0.918 21 22 Find the test statistic. 12 13 14 0.923 0.928 0.932 23 (Round to two decimal places as needed.) 24 25 0.935 0.939 Find the P-value. 15 30 The P-value is (Round to three decimal places as needed.) Print Done Use the a=0.1 level of significance. What can be concluded from the hypothesis test? O A. The P-value is greater than the level of significance so there is not sufficient evidence to conclude the new system is effective. O B. The Pvalue is less than the level of significance so there is not sufficient evidence to conclude the new system is effective. OC. The P-value is greater than the level of significance so there is sufficient evidence to conclude the new system is effective. O D. The P-value is less than the level of significance so there is sufficient evidence to conclude the new system is effective.
Compound Probability
Compound probability can be defined as the probability of the two events which are independent. It can be defined as the multiplication of the probability of two events that are not dependent.
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Probability theory is a branch of mathematics that deals with the subject of probability. Although there are many different concepts of probability, probability theory expresses the definition mathematically through a series of axioms. Usually, these axioms express probability in terms of a probability space, which assigns a measure with values ranging from 0 to 1 to a set of outcomes known as the sample space. An event is a subset of these outcomes that is described.
Conditional Probability
By definition, the term probability is expressed as a part of mathematics where the chance of an event that may either occur or not is evaluated and expressed in numerical terms. The range of the value within which probability can be expressed is between 0 and 1. The higher the chance of an event occurring, the closer is its value to be 1. If the probability of an event is 1, it means that the event will happen under all considered circumstances. Similarly, if the probability is exactly 0, then no matter the situation, the event will never occur.
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