A) The standard deviation is calculated only from sample attributes.
B) The standard error is a measure of central tendency.
C) All of the above.
D) The standard error is calculated solely from sample attributes.
F) C) and D)
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D
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A) We can be 95% confident that the true difference between the population means falls between −0.08 and 0.15.
B) The probability is 0.95 that a significant difference between the population means lies between −0.08 and 0.15.
C) The probability is 0.05 that the true difference between the population means is between −0.08 and 0.15
D) The two populations cannot have the same means.
F) B) and D)
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A) Yes you can,because the correlation coefficient is .5 (which is above .30) and falls within the boundaries of the confidence interval.
B) No you cannot,because the lower boundary of the confidence interval is .131,which is less than .30,and so the true correlation could be less than .30.
C) Yes you can,because the upper boundary of the confidence interval is above .30 we can be 95% confident that the true correlation will be above .30
D) No you cannot,because the sample size was too small.
F) None of the above
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A) The standard error is the standard deviation of sample means.
B) The standard error is a measure of how representative a sample parameter is likely to be of the population parameter.
C) The standard error is computed from known sample statistics,and it provides an unbiased estimate of the standard deviation of the statistic.
D) All of the options describe the standard error.
F) A) and D)
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A) Can be used instead of conventional statistics based on point estimates.
B) Are not frequently used in research articles because they can mislead the reader.
C) Are constructed using subjective evaluations of confidence.
D) None of these options are correct.
F) A) and C)
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A) We conclude that there is not an effect in the population when in fact there is.
B) We conclude that there is an effect in the population when in fact there is not.
C) We conclude that the test statistic is significant when in fact it is not.
D) The data we have typed into SPSS is different from the data collected.
F) None of the above
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A) large
B) small
C) small to medium
D) medium to large
F) B) and C)
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C
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A) p is the probability of observing a test statistic at least as big as the one we have if there were no effect in the population (i.e.,the null hypothesis were true) .
B) p is the probability that the results are due to chance,the probability that the null hypothesis (H0) is true.
C) p is the probability that the results are not due to chance,the probability that the null hypothesis (H0) is false.
D) p is the probability that the results would be replicated if the experiment was conducted a second time.
F) A) and D)
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A) There will be no relationship between heart rate and the number of cups of coffee drunk within the last 4 hours.
B) People who drink more coffee will have significantly higher heart rates.
C) People who drink more cups of coffee will have significantly lower heart rates.
D) There will be a significant relationship between the number of cups of coffee drunk within the last 4 hours and heart rate.
F) All of the above
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A) Dutch people differ in height from English people.
B) English people are taller than Dutch people.
C) Dutch people are taller than English people
D) All of the statements are plausible alternative hypotheses.
F) All of the above
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A) Parameters are estimated from the data and are (usually) constructs believed to represent some fundamental truth about the relations between variables in the model.
B) Parameters are measured constructs that vary across entities in the sample.
C) A parameter tells us about how well the mean represents the sample data.
D) All of the options describe parameters.
F) A) and B)
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A) Eating cheese is linearly related to the number of nightmares you have.
B) Eating cheese before bed gives you more nightmares.
C) The number of nightmares you have is not affected by eating cheese before bed.
D) Eating cheese before bed gives you fewer nightmares.
F) None of the above
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A) Eating salmon does not predict the glow of skin.
B) People who eat salmon will have a similar complexion to those who do not.
C) People who eat salmon will have a more glowing complexion compared to those who don't.
D) There will be no difference in the appearance of the skin of people who eat salmon compared to those who don't.
F) A) and D)
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A) Variables estimate the centre of the distribution.
B) Variables estimate the relationship between two parameters.
C) Variables are measured constructs that vary across entities in the sample.
D) Variables are estimated from the data and are (usually) constants believed to represent some fundamental truth about the relations in the model.
F) C) and D)
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A) In small samples only small effects will be deemed 'significant'.
B) Large effects tend to be significant only in small samples.
C) Large effects tend to be significant only in large samples.
D) In large samples even small effects can be deemed 'significant'.
F) B) and D)
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A) The standard error decreases as the sample size increases.
B) The standard error decreases as the sample size decreases.
C) The standard error is unaffected by the sample size.
D) The standard error increases as the sample size increases.
F) A) and C)
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A
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A) Confidence intervals are known as point estimates.
B) Confidence intervals tell us about the range of possible values of a statistic within the sample.
C) If the confidence interval for the difference between two means does include zero then the difference between the means is statistically significant.
D) Confidence intervals are not biased by non-normally distributed data.
F) None of the above
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A) 95 out of 100 confidence intervals will contain the population mean.
B) 95 out of 100 sample means will fall within the limits of the confidence interval.
C) 95% of population means will fall within the limits of the confidence interval.
D) There is a 0.05 probability that the population mean falls within the limits of the confidence interval.
F) C) and D)
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A) A one-tailed hypothesis
B) A non-scientific statement
C) A two-tailed hypothesis
D) A null hypothesis
F) C) and D)
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A) The variability of scores in the population.
B) The 'flatness' of the distribution of sample scores.
C) The variability of sample estimates of a parameter.
D) The variability in scores in the sample.
F) A) and B)
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