Question 1 - True or False
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