Question 1

Which of the following best describes the relationship between sample size and significance testing?

Accepted Answer

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'. 
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'. D

Question 2

What is the relationship between sample size and the standard error of the mean?

Accepted Answer

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. 
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. A

Question 3

Which of the following is true about a 95% confidence interval of the mean:

Accepted Answer

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. 
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. A

Question 4

Confidence intervals:

Accepted Answer

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. 
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.

Question 5

'Children can learn a second language differently before the age of 7 than after.' Is this statement:

Accepted Answer

A) A non-scientific statement 
B) A two-tailed hypothesis 
C) A one-tailed hypothesis 
D) A null hypothesis 
A) A non-scientific statement 
B) A two-tailed hypothesis 
C) A one-tailed hypothesis 
D) A null hypothesis

Question 6

What is the alternative hypothesis for the following question: Does eating salmon make your skin glow?

Accepted Answer

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. 
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.

Question 7

Which of the following statements is true?

Accepted Answer

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. 
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.

Question 8

The 99% confidence interval usually is:

Accepted Answer

A) Narrower than the 95% confidence interval. 
B) Wider than the 95% confidence interval. 
C) The same as the 95% confidence interval. 
D) A less precise estimate of the effect in the population than the 95% confidence interval. 
A) Narrower than the 95% confidence interval. 
B) Wider than the 95% confidence interval. 
C) The same as the 95% confidence interval. 
D) A less precise estimate of the effect in the population than the 95% confidence interval.

Question 9

In general, as the sample size (N) increases:

Accepted Answer

A) The confidence interval is unaffected. 
B) The confidence interval becomes less accurate. 
C) The confidence interval gets narrower. 
D) The confidence interval gets wider. 
A) The confidence interval is unaffected. 
B) The confidence interval becomes less accurate. 
C) The confidence interval gets narrower. 
D) The confidence interval gets wider.

Question 10

What is the null hypothesis for the following question: Is there a relationship between heart rate and the number of cups of coffee drunk within the last 4 hours?

Accepted Answer

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. 
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.

Question 11

What is the standard error?

Accepted Answer

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. 
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.

Question 12

If my experimental hypothesis were 'Eating cheese before bed affects the number of nightmares you have', what would the null hypothesis be?

Accepted Answer

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. 
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.

Question 13

What does a significant test statistic tell us?

Accepted Answer

A) There is an important effect. 
B) That the test statistic is larger than we would expect if there were no effect in the population. 
C) The hull hypothesis is false. 
D) All of the above. 
A) There is an important effect. 
B) That the test statistic is larger than we would expect if there were no effect in the population. 
C) The hull hypothesis is false. 
D) All of the above.

Question 14

A Type II error occurs when :

Accepted Answer

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. 
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.

Question 15

Why is the standard error important?

Accepted Answer

A) It gives you a measure of how well your sample parameter represents the population value. 
B) It is unaffected by outliers. 
C) It is unaffected by the distribution of scores. 
D) It tells us the precise value of the variance within the population. 
A) It gives you a measure of how well your sample parameter represents the population value. 
B) It is unaffected by outliers. 
C) It is unaffected by the distribution of scores. 
D) It tells us the precise value of the variance within the population.

Question 16

Under a null hypothesis, a sample value yields a p-value of .015. Which of the following statements is true?

Accepted Answer

A) This finding is statistically significant at the .01 level of significance. 
B) This finding is not statistically significant. 
C) This finding is statistically significant at the .001 level of significance. 
D) This finding is statistically significant at the .05 level of significance. 
A) This finding is statistically significant at the .01 level of significance. 
B) This finding is not statistically significant. 
C) This finding is statistically significant at the .001 level of significance. 
D) This finding is statistically significant at the .05 level of significance.

Question 17

A 95% confidence interval is:

Accepted Answer

A) The range of values of the statistic which we can be 5% confident contains a significant effect in the population. 
B) The range of values of the statistic which probably contains the true value of the statistic in the population. 
C) The range of values of the statistic that we can be 95% confident contains a significant effect in the population. 
D) The range of values of the statistic which we can by 95% certain does not contain the true population effect. 
A) The range of values of the statistic which we can be 5% confident contains a significant effect in the population. 
B) The range of values of the statistic which probably contains the true value of the statistic in the population. 
C) The range of values of the statistic that we can be 95% confident contains a significant effect in the population. 
D) The range of values of the statistic which we can by 95% certain does not contain the true population effect.

Question 18

What are variables?

Accepted Answer

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. 
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.

Question 19

If my null hypothesis is 'Dutch people do not differ from English people in height', what is my alternative hypothesis?

Accepted Answer

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. 
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.

Question 20

What are parameters?

Accepted Answer

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. 
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.

Exam 2: The Spine of Statistics

Which of the following best describes the relationship between sample size and significance testing?

What is the relationship between sample size and the standard error of the mean?

Which of the following is true about a 95% confidence interval of the mean:

Confidence intervals:

'Children can learn a second language differently before the age of 7 than after.' Is this statement:

What is the alternative hypothesis for the following question: Does eating salmon make your skin glow?

Which of the following statements is true?

The 99% confidence interval usually is:

In general, as the sample size (N) increases:

What is the null hypothesis for the following question: Is there a relationship between heart rate and the number of cups of coffee drunk within the last 4 hours?

What is the standard error?

If my experimental hypothesis were 'Eating cheese before bed affects the number of nightmares you have', what would the null hypothesis be?

What does a significant test statistic tell us?

A Type II error occurs when :

Why is the standard error important?

Under a null hypothesis, a sample value yields a p-value of .015. Which of the following statements is true?

A 95% confidence interval is:

What are variables?

If my null hypothesis is 'Dutch people do not differ from English people in height', what is my alternative hypothesis?

What are parameters?

Why Is My Evil Lecturer Forcing Me to Learn Statistics

The Phoenix of Statistics

The IBM Spss Statistics Environment

Exploring Data With Graphs

The Beast of Bias

Non-Parametric Models

Correlation

Regression

Comparing Two Means

Moderation, Mediation and More Regression

GlM 1: Comparing Several Independent Means

GlM 2: Comparing Means Adjusted for Other Predictors Analysis of Covariance

GlM 3: Factorial Designs

GlM 4: Repeated-Measures Designs

GlM 5: Mixed Designs

Multivariate Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Outcomes: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

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