Module 8 Flashcards
The fundamental condition that permits proper statistical inference is
A) Random sampling
B) Normal distribution of scores
C) Knowledge of the values of the parameters of the population
D) Having a large sample
A) Random sampling
Randomization and random sampling A) Are synonymous B) Often amount to the same thing C) Are different procedures D) Can be substituted for each other
C) Are different procedures
In forming groups of volunteer subjects for a learning experiment, Professor Jones will most likely use A) Randomization B) Random sampling C) Systematic sampling D) Representative sampling
A) Randomization
Randomization is used:
A) To select subjects randomly from a population
B) As a less complex substitute for random sampling
C) To analyze data from random samples
D) None of the above
D) None of the above
Professor Smith uses flips of a coin to form two groups of 4 subjects each out of an original group of 8 subjects. This is an example of A) Randomization B) Random sampling C) Systematic sampling D) Representative sampling
A) Randomization
Which of the following is a parameter? A) r B) S C) x̄ D) σ
D) σ
A population characteristic is known as a A) Element B) Parameter C) Statistic D) Basic value
B) Parameter
“Statistic” is to “parameter” as: A) “Mean” is to “standard deviation” B) “Sample” is to “population” C) “Random sampling” is to “randomization” D) “Calculated” is to “given”
B) “Sample” is to “population”
Whether or not a sample is considered random depends on
A) The method of selection
B) How closely it resembles the population
C) Both of the above
D) None of the above
A) The method of selection
Which is not a characteristic of random sampling?
A) Whether a sample is random or not cannot be told from inspection of the sample
B) Characteristics of a random sample may differ widely from characteristics of its population
C) A sample must be reasonably large to be considered a random sample
D) Every element in the population must be given an equal chance for inclusion in the sample.
C) A sample must be reasonably large to be considered a random sample.
Each score in a random sampling distribution of means represents A) A single individual B) A random data point C) A standard score D) A sample mean
D) A sample mean
The answer to which of the following questions is the “key” to solving a statistical inference problem?
A) Are the sample values close to the population values?
B) What sample values are likely to occur under random sampling?
C) Is the sample sufficiently representative of the population to proceed?
D) Is the sample large enough?
B) What sample values are likely to occur under random sampling?
A particular sampling distribution of means is based on means of
A) All possible samples of the same size
B) n samples of the same size
C) All possible samples of all possible sizes
D) n samples of all possible sizes
A) All possible samples of the same size
The correct formula for the standard error of the mean is A) σ² / n B) σ / n C) √(σ / n) D) σ / √(n)
D) σ / √(n)
From the formula for the standard error of the mean, it is apparent the variation among sample means will be decreased when
A) Variation among scores in the population is less
B) Sample size is larger
C) Either (or both) of the above occurs
D) The population size is larger
C) Either (or both) of the above occurs
The standard error of the mean is: A) Given in terms of standard units B) A standard deviation C) Larger for larger populations D) The average amount by which sample values are in error
C) A standard deviation
The Central Limit Theorem states that
A) The mean of a sample approaches the population mean as sample size increases
B) The standard deviation of a sample approaches the population standard deviation as sample size increases
C) Sampling distributions of means tend toward normality, regardless of the shape of the population distribution
D) The limits of the central 95% of means in a sampling distribution are μ ± 1S
C) Sampling distributions of means tend toward normality, regardless of the shape of the population distribution
The formula for the z ratio is similar to that for the z score. The “score” in the formula for the z ratio is A) x̄ B) σx̄ C) σ D) μ
A) x̄
Which is not a characteristic of the random sampling distribution of means?
A) Its mean is the same as the mean of the population of scores
B) Its standard deviation is greater than that of the population of scores
C) It tends to resemble the normal curve irrespective of the shape of the population of scores
D) Its standard deviation changes with changes in sample size
B) Its standard deviation is greater than that of the population of scores
For a normal population of scores, μ = 50 and σ = 10. If a sample of size 100 is to be randomly selected, what is the probability of its mean falling below 51? A) 0.9332 B) 0.6826 C) 0.9772 D) 0.8413
D) 0.8413
For a normal population of scores, μ = 50 and σ = 10. For samples of size 25, the highest 5% of sample means fall above what value? A) 51.96 B) 51.64 C) 53.28 D) 54.31
C) 53.28
A sample of size 16 is to be randomly selected from a normal population with μ = 130 and σ = 12. What is the probability of obtaining a sample mean above 136? A) 0.0228 B) 0.0505 C) 0.1587 D) 0.2120
C) 0.1587
For a normal population of scores, μ = 130 and σ = 12. What proportion of all possible samples of size 16 will have means between 118 and 142?
A) Almost all of them
B) About two thirds of them
C) About 5% of them
D) There is insufficient information to answer
A) Almost all of them
For a normal population of scores, μ = 50 and σ = 10. For samples of size 25, the central 95% of sample means will fall between what values (approximately)? A) 45 and 55 B) 46 and 54 C) 40 and 50 D) 49 and 51
B)46 and 54
For a normal population of scores, μ = 130 and σ = 12. For samples of size 36, the probability of obtaining a sample mean more than 2 points away from the population mean is about: A) 0.64 B) 0.32 C) 0.16 D) 0.10
B) 0.32
The mean of the sampling distribution of means:
A) Changes as sample size is increased
B) Changes as the standard deviation of the population of scores is increased
C) Changes from μ if the population is not normally distributed
D) Is unaffected by any of the above
D) Is unaffected by any of the above
A sampling distribution is a distribution of
A) Scores obtained from samples
B) Values of a statistic obtained from samples
C) Values of a parameter obtained from samples
D) Any of the above
B) Values of a statistic obtained from samples
A sampling distribution is A) A relative frequency distribution B) A probability distribution C) Both (A) and (B) D) Neither (A) nor (B)
C) Both (A) and (B)
The concept of random sampling distribution applies to A) Means B) Any measure of central tendency C) Standard deviations D) Any statistic
D) Any statistic
The standard deviation of the sampling distribution of means:
A) Increases as sample size increases
B) Increases as the mean of the population increases
C) Increases as the standard deviation of the population decreases
D) None of the above
D) None of the above.
