Research by Oishi & Scimmack (2010) suggests that people who move from home to home when they are children are more likely to have lower than average levels of well-being as adults. Imagine that a researcher obtains a sample of 1000 young adults who have moved to 5 or more different houses before age 16. You give them a standardized well-being questionnaire, that ranges from 10 to 50, for which the general population has an average score of 40, with unknown standard deviation.

The researchers report a two-tailed test finding their sample had lower average well-being than the population, t(999) = 2.44, p < .05, d = .001.

*This is based on an independent sample t test!*

Please answer the following questions using symbolic notation and appropriate formulas and explanation for thumbs up!

1. What type of analysis would be needed to examine this question? Explain your answer
2. What scale of measurement is the independent variable? Explain.
3. Consider the dependent variable. If you were to draw a distribution of scores for this variable, would you expect it to be normal, positively skewed, or negatively skewed? Explain your answer
4. What does t(999) = 2.44, p < .05 indicate?
5. Imagine the researchers were to include the 95% confidence interval in their report. Would they confidence interval include the population mean? Explain your answer
6. Consider the effect size. What is the role of significance and sample size when interpreting this result?Explain

Thanks