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Questions and Answers
What does a Pearson's r value of -0.9 indicate about the relationship between two variables?
What does a Pearson's r value of -0.9 indicate about the relationship between two variables?
- There is a strong negative association. (correct)
- There is a weak negative association.
- There is no significant association.
- There is a strong positive association.
Which statement accurately describes a null hypothesis significance test in correlation analysis?
Which statement accurately describes a null hypothesis significance test in correlation analysis?
- It proves that correlation implies causation.
- It supports the existence of an association if the p-value is greater than 0.05.
- It rejects the null hypothesis if the p-value is less than 0.05. (correct)
- It determines the exact strength of the correlation.
What is the main purpose of correlation analysis?
What is the main purpose of correlation analysis?
- To analyze the variance within a single population.
- To determine the cause-and-effect relationship between two variables.
- To predict the outcome of one variable based on another.
- To examine associations between two variables. (correct)
In which scenario would a repeated measures t-test be appropriate?
In which scenario would a repeated measures t-test be appropriate?
How are the correlation coefficients interpreted regarding their values?
How are the correlation coefficients interpreted regarding their values?
What is the null hypothesis in an independent sample t-test?
What is the null hypothesis in an independent sample t-test?
In an independent groups research design, what characterizes the participants?
In an independent groups research design, what characterizes the participants?
What does a t-score indicate in the context of an independent sample t-test?
What does a t-score indicate in the context of an independent sample t-test?
What is the effect size in the context of an independent samples t-test?
What is the effect size in the context of an independent samples t-test?
What characterizes a repeated measures t-test?
What characterizes a repeated measures t-test?
In correlation research design, what is being assessed?
In correlation research design, what is being assessed?
When should the null hypothesis be rejected in the context of a t-test?
When should the null hypothesis be rejected in the context of a t-test?
What does a significant p-value indicate in hypothesis testing?
What does a significant p-value indicate in hypothesis testing?
What type of test should be used when the population standard deviation is unknown?
What type of test should be used when the population standard deviation is unknown?
What does the t-test use as an estimate of the population standard deviation?
What does the t-test use as an estimate of the population standard deviation?
How do you calculate degrees of freedom for a single sample t-test?
How do you calculate degrees of freedom for a single sample t-test?
What is the significance level typically applied in null hypothesis significance testing?
What is the significance level typically applied in null hypothesis significance testing?
In the t-test, what must we consider along with the sample mean to determine its probability?
In the t-test, what must we consider along with the sample mean to determine its probability?
Which of the following statements regarding the critical limits in t-tests is true?
Which of the following statements regarding the critical limits in t-tests is true?
What would the probability need to be for the null hypothesis to be accepted in the head injury IQ example?
What would the probability need to be for the null hypothesis to be accepted in the head injury IQ example?
Which of the following is a primary difference between the z-test and the t-test?
Which of the following is a primary difference between the z-test and the t-test?
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Study Notes
Single Sample t-test (Module 6)
- Used when population standard deviation is unknown; estimates it using sample standard deviation.
- Similar to z-test in process, using null hypothesis significance testing.
- Uses t-distribution, requiring degrees of freedom (df = n-1) to determine probability of sample mean. Critical limits vary based on sample size and df.
- Example: Assessing if head injury affects IQ. Null hypothesis: head injury has no effect.
Independent Samples t-test (Module 7)
- Uses independent groups research design: participants assigned to different groups/conditions.
- Assesses if the difference between two sample means is significantly different from zero.
- JASP output provides descriptives, t-score, p-value, effect size.
- Tests if samples originate from the same population.
- Null hypothesis: There is no significant difference between population means.
- A p-value less than 0.05 indicates statistical significance, rejecting the null hypothesis.
Repeated Measures t-test (Module 8)
- Uses repeated measures research design: each participant measured multiple times (e.g., pre- and post-treatment).
- Assesses significant difference in participant scores before and after an event or intervention.
- Samples come from different populations (before and after).
- Also known as paired samples or related samples t-test.
- Example research question: Is there a change over time?
Correlation (Module 9)
- Uses correlational research design exploring the relationship between two variables.
- Examines linear and symmetrical associations.
- Pearson's r measures correlation in a sample; ranges from -1 to +1.
- Values near -1 or +1 indicate strong associations; 0 indicates no association.
- Positive correlation: as one variable increases, the other increases. Negative correlation: as one increases, the other decreases.
- Can infer from sample to population correlations using null hypothesis significance testing. Significant correlations suggest an association in the population.
- Example: Association between age and IQ; testing if there is a positive correlation (smarter with age).
- Scatterplots visually represents the correlations.
Choosing the Right t-test
- Single Sample: Comparing a sample mean to a known population mean (population standard deviation unknown).
- Independent Samples: Comparing means of two independent groups.
- Repeated Measures: Comparing means of the same group at different times or under different conditions.
- Correlational: Exploring the relationship between two continuous variables.
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