Question:

An original factor that has created the need for reform is the individual mandate which requires Americans to purchase health insurance or face government penalty. Another factor that has created a need for reform is the Medicaid expansion which required states to expand their Medicaid programs to cover adults with incomes up to 33 percent above the poverty level. Millions of Americans have benefitted from the ACA by receiving health insurance coverage, many of them which were unemployed or had low-paying jobs. Despite these positive outcomes, there are some cons to the ACA such as increase in taxes and many people are now paying higher premiums as a result of funding the ACA. The ACA hasn't admirably functioned for the working class who get considerably less help, especially individuals who earn income just over the federal poverty level. Without the ACA nearly 20 million Americans would lose health care coverage and 135 million Americans with pre-existing conditions could face discrimination if they needed to purchase health coverage from the individual market.

Response Posts:

In your response to at least two peers, discuss what additional difficulties you see in with implementing the revised ACA components addressed in their post. Respectfully agree or disagree with the consequences identified for patients.

Consider the following conditional density function extracted from a joint bivariate normal density function. A student thinks that there is a mistake, that the two variables were uncorrelated. It the student is correct, and everything else is correct, what are the correct Hyla-3.5 and f(y | x) ~ NUbe an = 25+0.42 TE (3.5 - 3) = 2.60, Jax an = (1 -0.4')0.4" = 0.36660) Select one: A bivariate normal density with variance 0.4 and mean Q b. A univariate normal density with mean 2.5 and standard deviation 0.4 " A bivariate normal density with mean of X equal 3.5 and mean of Y equal 0.4 d. A univariate normal density with mean 0 and standard deviation 1Match the letter with its meaning. average of a value In a bivariate data set actual value in a bivariate data set p-hat population proportion Intercept of an LSRL P slope of an LSLR Y bar often used to represent a random variable y-hat sample proportion predicted value iria bivariate data setriate Normal Distribution: Properties Marginal Distributions of Bivariate Normal Random Variables If X and Y have a bivariate normal distribution with joint probability density fxy(x, y, ox. Oy, Hy, Hy, p), the marginal probability distributions of X and Y are normal with means Hy and py and standard deviations ox and oy, respectively. (5.22) Conditional Distribution of Bivariate Normal Random Variables If X and Y have a bivariate normal distribution with joint probability density fxy(x, y, ox. Or, Hx, Hy, p), the conditional probability distribution of Y given X = x is normal with mean Hylx = Hy + P- (x- Hx) and variance ONLY = o? (1 - p? )