Πο Π1 Πε = = = 0.511 51.1 % Brand A = 0.289 = 28.9% Brand B = 0.2 = 20 % Brand C Calcular la P elevada - Data are taken monthly, and the analyst has constructed the following (one-step) transition -matrix from past data.
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- Why would the male lifespan not be the dependent variable?a.State the predictors available in this model.The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. In a particular region, 28.3 percent of adults 25 years and older have at least a bachelor's degree. The median income in this region is $37,389. Is this income higher than what you would expect? Why?
- The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Predict the median income of a region in which 30% of adults 25 years and older have at least a bachelor's degree.Consider a model with an interaction term between being female and being married. The dependent variable is the log of the hourly wage: log(wage) = 0.151 - 0.038 female + 0.1 married - 0.301 female* married + 0.079 educ + 0.027 exper+0.029 tenure (0.072) (0.056) (0.055) (0.007) (0.005) (0.007) n = 536, R2 = 0.461 Numbers in parantheses are standard errors of coefficients. Given the estimation result and the observation number fill in the blanks below which aim at discussing the statistical significance of variables. The test statistic of the interaction term is The critical value at 1% significance level is Then the interaction term statistically significant at 1% significance level. (Hint: to fill the blank make a choice between "is" and "is not".)The least-squares regression equation is y = 689.9x + 14,803 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7256. Complete parts (a) through (d). (a) Predict the median income of a region in which 20% of adults 25 years and older have at least a bachelor's degree. (Round to the nearest dollar as needed.) . TOLED dian Income Media 55000- 20000- 15 20 25 30 35 40 45 50 55 60 Bachelor's 96 Q
- An experiment is conducted to see the effect of light intensity on plant growth, what is the dependent variable in this scenario?Are any of the variables significantly correlated? If so, which ones and in which direction (positive or negative)? Correlation matrix: Health Score Anxiety Score Anxiety 0.13994335 Score (0.5047) Stress Score 0.38584335 0.010340294 (0.0568) (0.9609)The least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962. In a particular region, 26.5 percent of adults 25 years and older have at least a bachelor's degree. The median income in this region is $29,889. Is this income higher or lower than what you would expect? Why?
- In the simple linear regression model, if there is a very strong correlation between the independent and dependent variables, then the correlation coefficient should be a) close to either -1 or +1 b) close to zero c) close to -1 d) close to +1 ( don't hand writing solution)State University has increased its tuition for in-state and out-of-state students in each of the past 5 years to offset cuts in its budget allocation from the state legislature. The university administration always thought that the number of applications received was independent of tuition; however, drops in applications and enrollments the past 2 years have proved this theory to be wrong. University admissions officials have developed the following relationships between the number of applicants who accept admission and enter State and the cost of tuition per semester (in-state) (out-of-state) The university would like to develop a planning model that will indicate the in-state and out-of-state tuitions, as well as the number of students that could be expected to enroll in the freshman class. The university doesn’t have enough classroom space for more than 1,400 freshmen, and it needs at least 700 freshmen to meet all its class-size x2 = 35,000 - 6t2 x1 = 21,000 - 12t1 (xi) (ti):…The least-squares regression equation is y = 758.4x + 12.9 12,935 where y is the median income and is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7500. (a) Predict the median income of a region in which 30% of adults 25 years and older have at least a bachelor's degree.