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Questions and Answers

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?

  • 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?

  • 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?

    <p>Measuring IQ before and after a specific intervention in the same group.</p> Signup and view all the answers

    How are the correlation coefficients interpreted regarding their values?

    <p>Values close to -1 or +1 indicate a stronger association.</p> Signup and view all the answers

    What is the null hypothesis in an independent sample t-test?

    <p>There will be no significant difference between the population means.</p> Signup and view all the answers

    In an independent groups research design, what characterizes the participants?

    <p>They are from different groups or conditions.</p> Signup and view all the answers

    What does a t-score indicate in the context of an independent sample t-test?

    <p>The difference between two means is significant.</p> Signup and view all the answers

    What is the effect size in the context of an independent samples t-test?

    <p>It measures the strength of the relationship between the two groups.</p> Signup and view all the answers

    What characterizes a repeated measures t-test?

    <p>Participants' scores are compared across multiple occasions.</p> Signup and view all the answers

    In correlation research design, what is being assessed?

    <p>The relationship between two variables.</p> Signup and view all the answers

    When should the null hypothesis be rejected in the context of a t-test?

    <p>When the t-score is extreme for the degrees of freedom.</p> Signup and view all the answers

    What does a significant p-value indicate in hypothesis testing?

    <p>The groups are statistically different from each other.</p> Signup and view all the answers

    What type of test should be used when the population standard deviation is unknown?

    <p>Single sample t-test</p> Signup and view all the answers

    What does the t-test use as an estimate of the population standard deviation?

    <p>Sample standard deviation</p> Signup and view all the answers

    How do you calculate degrees of freedom for a single sample t-test?

    <p>One less than the sample size</p> Signup and view all the answers

    What is the significance level typically applied in null hypothesis significance testing?

    <p>5%</p> Signup and view all the answers

    In the t-test, what must we consider along with the sample mean to determine its probability?

    <p>Sample size and degrees of freedom</p> Signup and view all the answers

    Which of the following statements regarding the critical limits in t-tests is true?

    <p>Critical limits vary based on sample size and degrees of freedom.</p> Signup and view all the answers

    What would the probability need to be for the null hypothesis to be accepted in the head injury IQ example?

    <p>Greater than 5%</p> Signup and view all the answers

    Which of the following is a primary difference between the z-test and the t-test?

    <p>Z-tests require the population standard deviation to be known.</p> Signup and view all the answers

    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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