Question

Please explain how you got your answer.

1. The standard error of x-bar1 - x-bar2 is the measure of ____ for the sampling distribution of x-bar1 -- x-bar2.

a) point estimator b) interval estimate c) standard deviation

2. The point estimator for the difference between two population means, u1 - u2, is___

a) o1 - o2 b) s1 - s2 c) there is no point estimator for the difference between two population means

3. Suppose students with an ACT Math score below 27 (population 1) historically score at least 5 percentage points lower on exams in stats sources than students with higher ACT scores (population 2). The appropriate null hypothesis for the test to see if students who have ACT Math scores below 27 score at least 5% points lower on statistics exams would be...

a) Ho: u1 -u2 = -.5 b) Ho: u1 - u2 less than or equal to -.5 c) Ho: u1 - u2 less than -.5 d) Ho: u1 -u2 greater than or equal to -.5

4. When making inferences about the difference between two population means where o is not known for either population, we use...

a) the sample standard deviation and the standard normal distribution b) the sample standard deviation and the t-distribution

5. Tests for independence use which of the following tools to summarize the data for two variables simultaneously?

a) covariance matrices b) cross tabulation c) histograms

6. the sample statistics for the population parameters Bo and B1 are...

a) estimated by bo and b1 b)estimated by x and y c) none of the above are correct

7. if we were using mileage on a sample of 2009 Toyota Prius cars to predict the price of these vehicles, what is the independent variable?

a) the year of the cars b) the mileage on the cars c)the price of the cars

Answer 1

1)

standard error is measure of variation

c) standard deviation

2)

difference of sample mean is point estimator of point estimator

x-bar1 -- x-bar2

3)

there is always equality in null hypothesis

option A) is correct

4)

when we don't know population standard deviation, we use t-distribution

b) the sample standard deviation and the t-distribution