Ch 2 Solutions to Slr

6. How have educational and vocational programs for Indian women influenced birth rate and infant mortality? How have India’s population growth trends influenced access water and food production?

First we find E by doing Zc(standard deviation/square root of number of trials.) Now we add and subtract that number from the mean income to find both endpoints. The Zc of 95% is 1.96 so we would do

The method used to study the hypothesis was by having 328 women completed five surveys up to 72 hours postpartum. They were between the ages of 18-42. Out of the group 68.6% were married or living with a partner and 43.3% had a job. The average number of years the women spent in school was 8.8yrs. More than half (59.2%), did not complete high school and only 2% (6) completed higher education. From the group, 19.2% of them had a miscarriage before. More than half (51.5%) had already

Three quarters of the U.S. population would spend essentially all of their yearly incomes to purchase consumer goods such as food, clothes, radios, and cars. These were the poor and middle class: families with incomes around, or usually less than, $2,500 a year. The bottom three quarters of the population had a total income of less than 45% of the combined national income; the top 25% of the population took in more than 55% of the national income. While the wealthy too purchased consumer goods, a family earning $100,000 could not be expected to eat 40 times more than a family that only earned $2,500 a year, or buy 40 cars, 40 radios, or 40 houses.

Table 6.1.1 displays the matlab output of beta, standard error, t-statistic and p-value for the two independent variables during 10-year period. It is found that beta of X1 is 0.2750 which indicates there is a positive relationship between the utilities excess return and the healthcare excess return. This positive relationship is statistically significant as the p-value is close to 0 which is much less than the significance level of 5%. In addition, the standard error of X1 is 0.0300 which represents the average distance that the observed values fall from the regression line. This indicates that the model fits the data. In contrast, it is found that the material excess return is negatively

While evaluating and analyzing the issue of smoking, various models and systems could be used. Healthy People 2020 use information analyzed from national census data of events such as the National Vital Statistics System. It also uses data from nationally representative sample surveys for example the National Health Interview survey. Data on the relationship between maternal behavior and birth weight, maternal and child health and vital statistics derived from The Pregnancy Risk Assessment Monitoring System (PRAM) can also be

The figure below shows a portion of a consumer’s indifference map, and a budget line. The consumer’s income is $1,200 and the price of Y is

7. Describe the difference between public and private IP addresses. If a network is using

Therefore the demand for the low-calorie microwavable food is inelastic. An increase in the price of the food will cause a decrease in quantity demanded. Income elasticity of the goods calculated is 1.08, which means that the good selected is a luxury good. Changes in income could also affect the demand of this product. The cross price elasticity is 0.005. Therefore the two goods can be considered as neutral goods. The advertisement elasticity is 0.08. This indicates that advertisement has an important impact on the sales of the product. Lastly, the microwave ovens elasticity is 0.05. This is a direct correlation as sales of microwave ovens increase; demand for of low-calorie microwavable food also increases.

Scientists and economists equally agree that the answer to our population problem is education; specifically the education and empowerment in women. “The relationship between population and development with education is undeniable.” Education among women affects fertility rates in many ways, it

4. Is there a difference in the mean amount spent in restaurants each month across people with different marital status? If the groups are different, which category (or categories) of material status spend the most?

Where Age is the age of the mother, birthweight is the weight of the baby and History of Hypertension = 1 or 0 if the woman had a history of hypertension/doesn’t have a history of hypertension. So, for a woman that is 21 years old, had a baby with a birthweight of 6 pounds, and has a history of hypertension the predicted weight of the mom at her last menstrual period= 157.32. The R-squared of .1326 tell us that 13% of the variability in the weight of the mom at her last menstrual period can be explained by the regression model with a 21 year old woman, has a 6 pound baby, and has a history of hypertension. Furthermore, since we wish to know the predicted weight of the mom at the last menstrual period we can further assess how much weight is needed in the beginning for the woman to gain throughout the pregnancy. This predicted weight will help to determine how much in addition to your pre-pregnancy weight you should gain while pregnant to help sustain your baby’s growth and development. Even more importantly, the mother’s pre-pregnancy weight helps to determine if the mother is considered underweight, normal weight, or overweight. Moreover, when predicting the pre-pregnancy weight it is essential to know that many factors are associated that determine if the mother is likely to have a baby weighing

Income compared to the years at the current location had in inverse correlation of -0.2. In other words, those with higher

Estimate the effect on income each of the options Rowe has suggested if Bradley estimates as follows :

It is also important to note that what we are measuring here is the long-run If the $200 household were to double its income overnight, its relationship. consumption behaviour might well be completely different from the household which has been receiving $400 income for a long period of time. Our estimates, therefore, concern the long-run adjustment of consumption behaviour to income change. For these reasons, the consumption-income relationship based on cross sectional data may well be very different from the relationship based on time-series data, which probably include a relatively larger element short-run adjustment.