The phrase "linear regression" pertains to regression

The phrase "linear regression" pertains to regression models with normal equations that can be expressed in matrix form using linear algebra to determine coefficient estimates.

Question 2 - Use the given data to find the equation of the regression line. Round the final values to three significant digits, if necessary. Let x be the independent variable and y the dependent variable. (Note that if x = 2, then y = 7 and so forth. yhat is the predicted value of the fitted equation.)

x 2 4 5 6 8

y 7 11 13 20 24

a. yhat = 0.15 + 2.8x

b. yhat = 0.15x + 3.0

c. yhat = 0.15 + 3.0x

d. yhat = 2.8x

Question 3 - Choose the one alternative that best completes the statement or answers the question.

Assume two independent random samples are available which provide sample proportions. For the first sample assume n1= 100 and x1= 39. For the second sample, assume n2= 100 and x2= 49. Test the null hypothesis that the population proportions are equal versus the alternative hypothesis that the proportions are not equal at the 90% confidence level. Frame the test statistic by subtracting the proportion for population 1 from that for population 2. Pick an appropriate z value, p-value and conclusion. Round your answer to the nearest thousandth.

a. z-value = -1.425 p-value= 0.077 statistically significant

b. z-value = 1.425 p-value= 0.077 not statistically significant

c. z-value = 1.425 p-value= 0.077 statistically significant

d. z-value = -1.425 p-value= 0.1543 not statistically significant