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Correlation coefficient: r = SSxy/√SSxSSy = 94.20466667/√56.72933*5318.417 = 0.1715

0.1715 is closer to 0, therefore there is a weak correlation

Coefficient of determination: r^2 = (r)^2 = (0.1715)^2 = 0.0294

Thus, 2.94% of the variation in prenatal care is explained to the weak linear relationship between house value versus rental. The other 97.06% of the variation is due to other factors.

10.3.2

Table #10.1.6 contains the value of the house and the amount of rental income in a year that the house brings in ("Capital and rental," 2013).

Test at the 5% level for a positive correlation between house value and rental amount.

Table #10.1.6: Data of House Value versus Rental

Ho:ρ=0(There is no correlation)

HA:ρ≠0(There is a correlation)

or HA:ρ<0(There is a negative correlation)

or HA:ρ>0(There is a positive correlation)

α level = 0.05

10.3.4

The World Bank collected data on the percentage of GDP that a country spends on health expenditures ("Health expenditure," 2013) and also the percentage of women receiving prenatal care ("Pregnant woman receiving," 2013). The data for the countries where this information is available for the year 2011 are in table #10.1.8.

Test at the 5% level for a correlation between percentage spent on health expenditure and the percentage of women receiving prenatal care.

Table #10.1.8: Data of Health Expenditure versus Prenatal Care

11.1.2

Researchers watched groups of dolphins off the coast of Ireland in 1998 to determine what activities the dolphins partake in at certain times of the day ("Activities of dolphin," 2013). The numbers in table #11.1.6 represent the number of groups of dolphins that were partaking in an activity at certain times of days. Is there enough evidence to show that the activity and the time period are independent for dolphins? Test at the 1% level.

Table #11.1.6: Dolphin Activity

11.1.4

A person’s educational attainment and age group was collected by the U.S. Census Bureau in 1984 to see if age group and educational attainment are related. The counts in thousands are in table #11.1.8 ("Education by age," 2013). Do the data show that educational attainment and age are independent? Test at the 5% level.

Table #11.1.8: Educational Attainment and Age Group

11.2.4

In Africa in 2011, the number of deaths of a female from cardiovascular disease for different age groups are in table #11.2.6 ("Global health observatory," 2013). In addition, the proportion of deaths of females from all causes for the same age groups are also in table #11.2.6. Do the data show that the death from cardiovascular disease are in the same proportion as all deaths for the different age groups? Test at the 5% level.

Table #11.2.6: Deaths of Females for Different Age Groups

11.2.6

A project conducted by the Australian Federal Office of Road Safety asked people many questions about their cars. One question was the reason that a person chooses a given car, and that data is in table #11.2.8 ("Car preferences," 2013).

Table #11.2.8: Reason for Choosing a Car

Do the data show that the frequencies observed substantiate the claim that the reasons for choosing a car are equally likely? Test at the 5% level.

Ho: the reason for choosing a car is equally likely

Ha: the reason for choosing a car is not equally likely

Observed frequency = 84+62+46+34+47+27 = 300

Expected value = sum of all frequency/#rows = 300/6 = 50

Percentage of GDP a country spends

9.6 3.7 5.2 5.2 10 4.7 4.8 6 5.4 4.8 4.0999999999999996 6 9.5 6.8 6.1 47.9 54.6 93.7 84.7 100 42.5 96.4 77.099999999999994 58.3 95.4 78 93.3 93.3 93.7 89.8

Health Expenditure %

Pre-natal Care %