Understanding Political Science Research
(POS 3713‐02, Fall 2017, HCB 113)
Prof. Jens Großer
Unit exam #3
11/09/2017
This is the third out
... [Show More] of four multiple choice tests (unit exams) that count for your final
grade. There are 25 questions with four possible answers each. In all questions, only one of
the four answers is correct. You will receive 1 point for each correct answer, and 0 points
for each incorrect answer. Hence, the maximum possible points in this test are 25 points.
Please read the questions and possible answers carefully before you make your choices!
Also, don’t forget to write down and “bubble” your name on the answer sheet!
On Chapter 6:
1. What is the key insight of the Central Limit Theorem?
(a) Regardless of the shape of a frequency distribution, as the sample size gets larger and
larger, that distribution will more closely resemble a normal distribution, and, when a
sample hypothetically becomes infinitely large, it is guaranteed to be normally distributed.
(b) For variables that are normally distributed, it is possible to use even a small sample to
make inferences about the population.
(c) Regardless of the shape of a frequency distribution of a randomly chosen sample, a
hypothetical distribution of an infinite number of sample means will be normally
distributed, with a knowable variance.
(d) For random samples, but only for random samples, the process of statistical inference
does not depend on sample size.
2. Which of the following is not true about normal distributions?
(a) It is the basis of statistical inference.
(b) Approximately 68% of the area under the curve lies within one standard deviation of its
mean.
(c) It is symmetrical about its mean.
(d) As the name implies, they are quite common in everyday experience.
3. Which of the following is not true about a sampling distribution?
(a) A sampling distribution represents a hypothetical distribution, showing what the true
population distribution would look like if our sample size were infinitely large.
(b) A sampling distribution for a variable is normally distributed even if the underlying
population is not distributed normally for that variable.
(c) Sampling distributions are almost never observed in real life.
(d) The mean of a sampling distribution is equal to the true population mean.
2
4. If a mean age of a sample of 100 randomly chosen individuals is 48 and the
standard deviation of the sample is 16, what is the standard error of the mean?
Recall that ࢅ࣌ഥ ൌ ࢅ࢙
√
.
(a) 3
(b) .16
(c) 4.8
(d) 1.6
The following 2 questions refer to this figure:
5. How large, in %, is the area to the left of െ (standard errors)?
(a) 2.5%
(b) 5%
(c) 16%
(d) 32%
6. How large, in %, is the area to the left of (standard errors)?
(a) 68%
(b) 84%
(c) 95%
(d) 97.5%
7. If, for a sample in which the subjects ar [Show Less]