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1. A in a density histogram the area of a region is equivalent tothe density of that region_________.
2. Extreme values or “outlier” have a great effect on theInterquartile range than on the standard deviation as the standarddeviation is a resistant measure of spread_______.
3. In the events A and B are disjoint they must also beindependent_______.
4. For any two events A and B, P (A or B)= P(B)+ P(A and B).________.
5. If the events A and B are independent, the P (A and B) =P(A)P(B)_________.
6. If the events A and B are disjoint then conditionalprobabilities P(AB) and P(BA) are both equal to 0______.
7. A random variable that assumes only negative values will have anegative mean ______.
8. A random variable that assumes only negative values will have anegative standard deviation______.
9. A binomial random variable counts the number of “successes” ina fixed number of independent trials where the probability of“success” varies from trial to trial_____.
10. A statistic is a random quantity: different random samples willyield different statistic values______.
11. The mean of sampling distribution of the sample mean is equalto the population mean_____.
12. The standard deviation of the sampling distribution of the thesample mean is generally smaller than the standard deviation of thepopulation_____.
13. If the population is (exactly) normally distributed, thesampling distribution of the sample mean will be (exactly) normalalso______.
14. Even if the population distribution is not normal, as long asthe sample size is sufficiently large, the sampling distribution ofthe sample mean will be approximately normal, by central limittheorem______.
15. A 95% Confidence Interval will generally be wider than a 90%Confidence Interval for the same parameter, based on the same data______.  
16. A 95% Confidence Interval for a population mean will contain atleast 95% of the values in the underlying population_______.
17. If we were to take a large number of independent random samplesand calculate a A 95% Confidence Interval from about 95% of theresulting intervals would cover the true parametervalue______.
18. In hypothesis testing, H₀is a statement about thepopulation that we initially assume to be true________.
19. A P-value close to zero indicated that the observed data areinconsistent with the null hypothesis______.
20. If we reject H₀at the a=0.05 level of significanceclearly we would reject a=0.01 as well_______.
21. A P-value less than 0.01 indicates that if H₀ weretrue, the chance of observing data as extreme as those observedwould be less than one out of 100______.
22. In a two-way contingency table, the marginal (row and column)sums of the “expected cell counts” will be equivalent marginal sumsof the observed cell counts_______.
23. Evidence against the null hypothesis of independent between rowand column variables in a contingency table is provided by a verysmall value of the chi-square statistic_____.
24. In an r x c contingency table the P-value for a test ofrow-column is found by comparing the test statistic x^2 to thechi-square distribution with (r-1)(c-1) degrees offreedom______.
25. If two quantitative variable x and y are negatively associatedabove average values of x will tend to occur with below averagevalues of y and vice versa_______.
26. If a set of data (x₁, y₁) …….(x_n,y_n) satisfy y_i=4x for eachi=1…n then the correlation between the x’s and the y’s is1______.
27. Correlation is a resistant measure in that it is not sensitiveto extreme values or outliers______.
28. Correlation makes a distinction between response variable andexplanatory variable______.
29. Least-square regression makes a distinction between responsevariable and explanatory variable______.
30. The least square regression line always passes through thepoint(xbar, ybar) ______.