Question

QUESTION 3)What is the critical value of the test statistic to test the mean child mortality rate for countries in Africa is more than the mean child mortality rate for countries in South Asia?

0.59

0.299

0.126

2.015

2.35

Case Description

Corporations with international operations need to assess the risks associated with setting up and maintaining operations in different regions of the world. Consideration of the risks include considering such issues as political and economic stability. One indicator of the healthcare and quality of life in a country or region that is considered correlated with the risk and stability in the region is the child mortality rate. As a result, the healthcare and quality of care as measured by the child mortality rate in a region can impact the type and amount of investment in a region and countries within a region. The child mortality rate is the number of children 5 and under that die per thousand people in the population. The Inter-agency Group for Child Mortality Estimation (IGME) was obtained from www.childmortality.org. In 2008 the US rate was 7.6 deaths per thousand and in North America (US and Canada) the rate was 6.65 with a standard deviation of 0.68. The Excel file for this assignment has labels for the year, country name, and continent group.

Answer 1

Solution:-

3) t = 0.59

State the hypotheses. The first step is to state the null hypothesis and an alternative hypothesis.

Null hypothesis: u_Africa< u_{South Asia}
Alternative hypothesis: u_Africa > u_{South Asia}

Note that these hypotheses constitute a one-tailed test.

Formulate an analysis plan. For this analysis, the significance level is 0.05. Using sample data, we will conduct a two-sample t-test of the null hypothesis.

Analyze sample data. Using sample data, we compute the standard error (SE), degrees of freedom (DF), and the t statistic test statistic (t).

SE = sqrt[(s₁²/n₁) + (s₂²/n₂)]
SE = 54.6828
DF = 22

t = [ (x₁ - x₂) - d ] / SE

t = 0.59

where s₁ is the standard deviation of sample 1, s₂ is the standard deviation of sample 2, n₁ is thesize of sample 1, n₂ is the size of sample 2, x₁ is the mean of sample 1, x₂ is the mean of sample 2, d is the hypothesized difference between population means, and SE is the standard error.

The observed difference in sample means produced a t statistic of 0.59.

Therefore, the P-value in this analysis is 0.281.

Interpret results. Since the P-value (0.281) is greater than the significance level (0.05), we cannot reject the null hypothesis.

From the above test we do not have sufficient evidence in the favor of the claim that the mean child mortality rate for countries in Africa is more than the mean child mortality rate for countries in South Asia.