PSYCHSTATS - SAMPLE TEST

The null hypothesis is rejected, but the result may lack practical significance.

A psychologist tested whether mindfulness practices improve working memory and obtained a p-value of 0.045. The significance level was set at 0.05. How should the psychologist interpret this result?

One-tailed t-test; alternative hypothesis that stress is lower in nature.

Imagine you are designing an experiment to test whether exposure to nature reduces stress levels compared to urban settings. Which statistical test and hypothesis direction would you choose if your prediction is that nature will decrease stress more than urban environments?

The result is statistically significant, but the effect size suggests limited practical significance.

A researcher reports a statistically significant result with a p-value of 0.04 but an effect size of 0.1 (Cohen’s d). What conclusion can be drawn about the practical significance of the study?

Statistical significance does not imply practical significance.

In a one-sample t-test, the sample mean is close to the population mean, but the test is significant due to a large sample size. What does this imply about the results?

The small sample size increases the likelihood of Type I errors.

A one-sample t-test reveals that participants’ average scores on a psychological measure differ significantly from the population mean. However, the sample size is very small. What should the researcher consider when interpreting these results?

Highlight the practical significance of a 0.5-hour reduction in sleep.

A psychologist uses a one-sample t-test to determine if the average sleep duration of patients is different from the recommended 8 hours. The study finds a mean of 7.5 hours, with a significant p-value. How should the psychologist communicate the implications of this finding?

There is greater variability in that group’s data.

What does a large standard deviation in one group indicate when interpreting the results of an independent t-test?

The null hypothesis is not rejected.

When interpreting the results of an independent t-test, a researcher observes that the confidence interval for the mean difference includes zero. What does this imply?

Analyze the effect size to assess practical significance.

A significant independent t-test result shows a small mean difference. What additional analysis can strengthen the interpretation?

Calculate the mean of the differences.

 In a paired t-test, the difference between paired observations is calculated for each participant. What is the next step in the analysis process?

The result is statistically significant but may have limited practical significance.

A study finds a significant result in a paired t-test, but the effect size is very small. What should the researcher consider?

Report the large effect size, emphasizing its practical significance despite the non-significant p-value.

A researcher tests the effectiveness of a training program by measuring participants’ performance before and after the program. The paired t-test shows no significant difference, but the effect size is large. What should the researcher focus on?

The psychologist should reject the null hypothesis because the p-value is below 0.05, but they should acknowledge the small effect size and consider increasing the sample size in future studies to enhance power and generalizability.

A psychologist is studying the effect of a mindfulness training program on participants’ stress levels. The null hypothesis states that the training program does not reduce stress levels, while the alternative hypothesis suggests that it does. The researcher conducts a paired t-test on pre-training and post-training stress scores and obtains a p-value of 0.04, which is below the chosen significance level of 0.05. Additionally, a small effect size (Cohen’s d = 0.3) is calculated. While the test results suggest a statistically significant difference, the psychologist notices that the sample size is relatively small ( n = 15 ) and is concerned about the generalizability of the findings. The psychologist also wants to ensure that the likelihood of a Type II error is minimized in future studies.

What should the psychologist conclude about the findings, and what steps can be taken to strengthen future research?

The likelihood of Type II error increases.

If a researcher decides to conduct a two-tailed test instead of a one-tailed test, what is the primary implication?

To measure the magnitude of the relationship or difference.

What is the primary purpose of reporting the effect size in hypothesis testing?

Because small effect sizes can still be statistically significant with large sample sizes.

Why is it important to consider effect size alongside p-values in hypothesis testing?

Question the practical significance of the findings despite statistical significance.

A team of psychologists conducts a study with a large sample size and achieves p < 0.001 but reports that the effect size is 0.05. As a reviewer, how would you evaluate their findings?

Increase the sample size to improve the power of the test.

 Imagine you are testing whether a group of students performs better on a standardized test than the national mean of 100. If the test power is 0.80 and the null hypothesis is not rejected, what might you do differently in the future?

Examine the effect size and confidence intervals for clinical relevance.

A researcher is testing if their new therapy program improves depression scores compared to a baseline of 20. The one-sample t-test shows significant results. What step should the researcher take next?

The small sample size increases the likelihood of Type II errors.

A one-sample t-test reveals that participants’ average scores on a psychological measure differ significantly from the population mean. However, the sample size is very small. What should the researcher consider when interpreting these results?

Increase the sample size to improve the power.

Imagine you find no significant difference between two groups in an independent t-test, but the power of the test is only 0.50. What would you recommend?

A small sample size reduced the test’s power.

 An independent t-test compares stress scores for two job types. The results are non-significant, but the means differ substantially. What might explain this?

Consider the possibility of other factors influencing the outcome and revisit the study design

A clinical psychologist uses a paired t-test to compare the symptoms of depression before and after therapy. The t-test shows no significant difference. What should the psychologist consider next?