1. Psychology 302, Quantitative Methods Francis Marion University Quiz, Sampling Distributions

2. 1. According to ______ the larger the sample, the closer the sample mean is to the population mean. (p. 251)
Murphy’s law
the law of large numbers
the Hildreth Principle
Simpson’s Paradox
null hypothesis

3. 1. According to ______ the larger the sample, the closer the sample mean is to the population mean. (p. 251)
Murphy’s law
the law of large numbers
the Hildreth Principle
Simpson’s Paradox
null hypothesis

4. 2. A property of the population is called a: (p. 250)
parameter
polarity
pooled estimator
Probability distribution
Correlation

5. 2. A property of the population is called a: (p. 250)
parameter
polarity
pooled estimator
Probability distribution
Correlation

6. 3. We do inferential statistics because the ____ is unknown. (p. 250)
parameter
polarity
pooled estimator
Probability distribution
skewness

7. 3. We do inferential statistics because the ____ is unknown. (p. 250)
parameter
polarity
pooled estimator
Probability distribution
skewness

8. 4. The population mean is represented as:σ M PM μ Σ

9. 4. The population mean is represented as:σ M PM μ Σ

10. 5. A sampling distribution is like a frequency distribution except that it consists of: (p. 255)
statistics
parameters
means
slopes
ANOVA’s

11. 5. A sampling distribution is like a frequency distribution except that it consists of: (p. 255)
statistics
parameters
means
slopes
ANOVA’s

12. 6. Probability is a matter of:
the standard deviation of the sample
the square root of the sample
Relative frequency
the harmonic mean
all of the above

13. 6. Probability is a matter of:
the standard deviation of the sample
the square root of the sample
Relative frequency
the harmonic mean
all of the above

14. 6. Probability is a matter of:
the standard deviation of the sample
the square root of the sample
the standard deviation of the sample divided by the square root of n
the harmonic mean
all of the above

15. 7. According to the Central Limit Theorem: (p. 259)
the mean of the sample equals the standard deviation
the standard deviation cannot be calculated
when n is large the sampling distribution is normal
when n is small the sampling distribution is normal
the standard deviation is used to measure the center

16. 7. According to the Central Limit Theorem: (p. 259)
the mean of the sample equals the standard deviation
the standard deviation cannot be calculated
when n is large the sampling distribution is normal
when n is small the sampling distribution is normal
the standard deviation is used to measure the center

17. 8. According to the Central Limit Theorem: (p. 259)
the sampling distribution is normal even if the population is not
the sampling distribution can be normal only if the population is normal
the population mean measures the population variance
the mean always equals the standard deviation

18. 8. According to the Central Limit Theorem: (p. 259)
the sampling distribution is normal even if the population is not
the sampling distribution can be normal only if the population is normal
the population mean measures the population variance
the mean always equals the standard deviation

19. 9. For the sample means, the distribution is ______ the raw score means. (p. 257)
less spread out than
more spread out than
the same as
all of the above
exam 2 question 34

20. 9. For the sample means, the distribution is ______ the raw score means. (p. 257)
less spread out than
more spread out than
the same as
all of the above
exam 2 question 34

21. 10. Averages are ____ than individual differences.
more variable than
the same as
less variable than
all of the above
none of the above
exam 2 question 36

22. 10. Averages are ____ than individual differences.
more variable than
the same as
less variable than
all of the above
none of the above
exam 2 question 36

23. Bonus question: The standard deviation of the sampling distribution is called:
The hypotenuse
The level of significance
The Range
The standard error
The correlation coefficient

24. Bonus question: The standard deviation of the sampling distribution is called:
The hypotenuse
The level of significance
The Range
The standard error
The correlation coefficient

25. The End