Given the following hypotheses: H 0 : μ = 100 H 1 : μ ≠ 100 A random sample of six resulted in the following values: 118, 105, 112, 119, 105, and 1 1 1. Assume a normal population. Using the .05 significance level, can we conclude the mean is different from 100? a. State the decision rule. b. Compute the value of the test statistic. c. What is your decision regarding the null hypothesis? d. Estimate the p -value.
Given the following hypotheses: H 0 : μ = 100 H 1 : μ ≠ 100 A random sample of six resulted in the following values: 118, 105, 112, 119, 105, and 1 1 1. Assume a normal population. Using the .05 significance level, can we conclude the mean is different from 100? a. State the decision rule. b. Compute the value of the test statistic. c. What is your decision regarding the null hypothesis? d. Estimate the p -value.
Solution Summary: The author explains how to obtain the critical value of test statistic using MINITAB software.
A random sample of six resulted in the following values: 118, 105, 112, 119, 105, and 1 1 1. Assume a normal population. Using the .05 significance level, can we conclude the mean is different from 100?
a. State the decision rule.
b. Compute the value of the test statistic.
c. What is your decision regarding the null hypothesis?
(a+b)
R2L
2+2*0=?
Ma
state without proof the uniqueness theorm
of probability function suppose thatPandQ
are probability measures defined on the
same probability space (Q, F)and that
Fis generated by a π-system if P(A)=Q(A)
tax for all A EthenP=Q i. e. P(A)=Q(A) for alla g
// معدلة 2:23 ص
6. Show that
1{AU B} = max{1{A}, I{B}} = I{A} + I{B} - I{A} I{B};
I{AB} = min{I{A}, I{B}} = I{A} I{B};
I{A A B} = I{A} + I{B}-21{A} I {B} = (I{A} - I{B})².
Theorem 3.5 Suppose that P and Q are probability measures defined on the same
probability space (2, F), and that F is generated by a л-system A. If P(A) = Q(A)
for all A = A, then P = Q, i.e., P(A) = Q(A) for all A = F.
Chapter 10 Solutions
Loose Leaf for Statistical Techniques in Business and Economics (Mcgraw-hill/Irwin Series in Operations and Decision Sciences)
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