Quiz Over Chapter 6 of the 6th Edition


Estimation

Introduction
  1. The two main types of estimation are called _______ estimation and _______ estimation.
  2. high-confidence; low-confidence
    precise; approximate
    interval; point
    scientific; non-scientific
    probability; nonprobability
  3. When a researcher uses the techniques of estimation, he/she is making a guess as to unknown characteristics of the sample based upon the known characteristics of the population.
  4. True
    False
Sampling Error
  1. What is a "sampling error"?
  2. A failure to give everyone in the population a chance to be in the sample.
    The inclusion of the same member of the population multiple times in the sample.
    A discepancy between the population parameter and the sample statistic.
  3. If a population is made up of 600 males and 400 females, should you expect that a simple random sample  of 100 people will end up containing 60 males and 40 females?
  4. Yes
    No
  5. Can researchers prevent sampling errors by extracting stratified random samples from populations?
  6. Yes
    No
  7. Under what unrealistic condition would a researcher be justified in anticipating no sampling error?
  8. s2 = 0.
    m = 0.
    s2 = m
Sampling Distributions and Standard Errors
  1. If 100 samples are taken from a population, with each sample having n = 25, there would be __ entries in the sampling distribution of means if the sample means are plotted.
  2. 4
    25
    100
    It depends on the size of the population
  3. Which of the following terms is closest in meaning to the term "standard error?"
  4. computational error
    sampling error
    standard score
    standard deviation
  5. Suppose 10,000 random samples of the same size are drawn from a population having M=50 & SD=4.  Each sample's mean is computed and then displayed in a sampling distribution.  About ___% of the sample means would lie within one standard error of 50?
  6. one-fourth
    one-third
    one-half
    two-thirds
    three-fourths
  7. In the expression SEM, the E stands for "error."  What do the S and the M stand for?
  8. Statistical; Method
    Standardized; Mesokurtic
    Stipulated; Mechanical
    Standard; Mean
  9. Only 1 word can legitimately be put in the blank in the phrase: "standard error of the ____"
  10. True
    False
  11. In Excerpt 6.1, what abbreviation was used for the phrase, "estimated standard error of the mean"?
  12. ESEM
    ESE
    SEM
    SE
  13. In Excerpt 6.3, thow many standard error bars are displayed in the figure?
  14. 1
    2
    4
    8
Confidence Intervals: What They Look Like
  1. What does the number 10 signify in this statement: "95% CI: 10, 15"?
  2. The sample size
    The mean
    The CI's width
    The lower end of the CI
  3. If a researcher computes a sample mean and says "95% CI = (80-90)," could the sample mean be 95?
  4. Yes
    No
  5. Confidence intervals can be built for means and correlation coefficients but not for percentages..
  6. True
    False
  7. If the CIs presented in Excerpts 6.4-6.5 are typical, what is the most popular level of confidence used?
  8. 68%
    90%
    95%
    99%
The Construction of Confidence Intervals
  1. In building a confidence interval, what does a researcher specify first?
  2. The two numerical values (i.e., end points) that define the interval.
    The level of confidence desired for the CI to be constructed.
  3. Using the same data, a confidence interval will get wider if the confidence level is increased.
  4. True
    False
  5. A __________ relationship exists between the size of the sample & the distance between the end points  of the confidence interval.
  6. positive
    negative
    near zero
    absolutely zero
  7. If based on the same 25 scores, will a 95% CI for the mean turn out the same as a 95% CI for the median?
  8. Yes
    No
The Proper Interpretation of Confidence Intervals
  1. A confidence interval indicates the probability that the population parameter lies somewhere between the numerical end points of the CI.
  2. True
    False
  3. To interpret a CI correctly, you must imagine that lots of samples are drawn from the population, not just one sample.
  4. True
    False
The Advantage of Confidence Intervals Over Estimate Standard Errors
  1. Confidence intervals are more easily interpreted than "standard error intervals" because CIs take into consideration __ whereas "standard error intervals" do not.
  2. sampling error
    N
    n
  3. The advantage of confidence intervals over "standard error intervals" become trivial when ____ is very large.
  4. the sample mean
    the size of the sample
    the size of the population
Point Estimation
  1. When a researcher engages in point estimation, does he/she stipulate a confidence level?
  2. Yes
    No
  3. What statistical concept can be used to explain why point estimation is unlikely to "hit the bullseye?"
  4. Outliers
    Poor response rates
    Skewed distributions
    Sampling error
  5. Should reliability and validity coefficients be considered to be point estimates?
  6. Yes
    No
  7. Point estimation should be respected because it is used twice whenever CIs are built.
  8. True
    False
Warnings Concerning Interval and Point Estimation
  1. If someone says "52 ± 3," the 3 might be referring to the SD or it might be referring to the SEM.
  2. True
    False
  3. If a researcher carefully puts his/her sample data into the proper formula, he/she will still be unable to determine the precise value of the standard error of the statistic being focused on.
  4. True
    False
  5. If a confidence interval is built around a correlation coefficient, it may be the case that the CI's end points are not the same distance from the numerical value of r computed from the sample data.
  6. True
    False
  7. The 2nd sentence in the final paragraph of Chapter 6 says that "the entire process of estimation requires that the data used to form the inference come from _____ ."
  8. a reliable measuring instrument
    a normally distributed population
    a random sample

 

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