The time required to start a​ business, defined as the number of days needed to complete the procedures to legally operate a​ business, in 20 developed countries and 20 emerging countries is included in the accompanying table. Assuming that the population variances for developed countries and emerging countries are​ equal, is there evidence of a difference in the mean time required to start a business between developed countries and emerging​ countries? (Use α=0.05​.) Let μ1 be the mean time required to start a business in developed countries and let μ2 be the mean time required to start a business in emerging countries. What are the null and alternative​ hypotheses?   A. H0​: μ1=μ2      H1​: μ1≠μ2   B. H0​: μ1≠μ2      H1​: μ1=μ2   C. H0​: μ1≥μ2      H1​: μ1<μ2   D. H0​: μ1≤μ2      H1​: μ1>μ2   t-stat=___ p-value=___   What is the correct​ conclusion?   A. Reject H0. There is insufficient evidence of a difference in mean time required to start a business.   B. Do not reject H0. There is insufficient evidence of a difference in mean time required to start a business.   C. Do not reject H0. There is sufficient evidence of a difference in mean time required to start a business.   D. Reject H0. There is sufficient evidence of a difference in mean time required to start a business.   Choose the correct answer below.   A. The two sample sizes are equal.   B. The two populations have equal standard deviations.   C. The hypothesis test must be a​ two-tail test so the results can be validly compared to a 95​% confidence interval.   D. The two populations are normally distributed.   Construct a 95​%confidence interval estimate of the difference between the population means of developed countries and emerging countries.   ≤μ1−μ2≤ ​(Type integers or decimals rounded to two decimal places as​ needed.)

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...