Please help me with the following questions:

In Simple linear regression, the coefficient of correlation r and the slope 0 must be equal. 0 must have the same Sign. 0 must have the opposite Sign. 0 must not be equal. The regression equation is \\7' = 23.57 - 0.45x The independent variable is the employee age. The dependent variable is the number workdays absent. From the regression equation we determine: 0 for each additional year of age, we can expect the number of days of absence to increase by 0.45 days. 0 for each additional 23.5? years of age, we can expect the number of days of absence to increase 0.45 days. 0 for each additional 23.5? years of age, we can expect the number of days of absence to decrease by 0.45 days. 0 for each additional year of age, we can expect the number of days of absence to decrease by 0.45 days. The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean 0 is approximately normal if n 30. The coefficient of correlation r equals one when there is no: 0 explained variation. 0 y-intercept in the model. 0 unexplained variation. 0 linear relationship between x and y. The regression equation is '1" = 23.57 - 0.45): The independent variable is the employee age. The dependent variable is the number workdays absent. From the regression equation we determine: 0 An average employee will have 0.45 days of absence. 0 The y-intercept has no meaning in the context of this example. 0 An average employee will have 23.5? days of absence. 0 An employee who is 23.5? years of age will average 0.45 days of absence. Question 3 (1 point] If a random sample of size n is drawn from a normal population, then the sampling distribution of the sample mean will be: 0 normal only for n > 30. 0 approximately normal only for n > 30. 0 approximately normal for all values of n. 0 normal for all values of n. Question 28 {1 point) In a regression problem, if the coefficient of determination is 0.80, this means that: O 80% of the 3/ values are positive. 0 80% of the y values are predicted correctly by the model. 0 64% of the variation in y can be explained by the variation in x. O 80% of the variation in y can be explained by the variation in x. Question 9 (1 point) The standard error of the estimate is a measure of the: 0 percentage of variation in x explained by the variation in y. 0 the variation in the y-intercept. O the variation of the slope. O variation around the regression line