Statistics: Understanding Confidence Intervals and One-Sample t Tests, Exams of Psychology

Download Statistics: Understanding Confidence Intervals and One-Sample t Tests and more Exams Psychology in PDF only on Docsity! PSYCH STATS QUALIFYING EXAM A confidence interval computed for the mean of a single sample - is associated with a probability about the location of a population mean. If the population from which we sample is normal: the sampling distribution of the mean - will be normal For a t test with one sample we - lose one degree of freedom because we estimate the mean. The t distribution - approaches the normal distribution as its degrees of freedom increase. When we are using a two-tailed hypothesis test: the null hypothesis is of the form - H0 : μ = 50. If the population from which we draw very large samples is "rectangular": then the sampling distribution of the mean will be roughly - normal When you have a single sample and want to compute an effect size measure: the most appropriate denominator is - the standard deviation of the sample. If we compute 95% confidence limits on the mean as [112.5, 118.4]: we can conclude that - an interval computed in this way has a probability of .95 of bracketing the population mean. The term "effect size" refers to - the actual magnitude of the mean or difference between means. When you are using a one-sample t test: the degrees of freedom are - N - 1 All of the following increase the magnitude of the t statistic and/or the likelihood of rejecting H0 EXCEPT - a smaller significance level (alpha). If we have run a t test with 35 observations and have found a t of 3.60 which is significant at the .05 level: we would write - t(34) = 3.60, p <.05. A one-sample t test was used to see if a college ski team skied faster than the population of skiers at a popular ski resort. The resulting statistic was t(23) = -7.13, p < .05. What should we conclude? - The sample mean of the college skiers was significantly different from the population mean. If the population from which we sample is positively skewed: the sampling distribution of the mean - will approach normal for large sample sizes A one-sample t test was used to see if a college ski team skied faster than the population of skiers at a popular ski resort. The resulting statistic was t(23) = -1.13, p < .28. What should we conclude? - The sample mean of the college skiers was not significantly different from the population mean. When we are using a two-tailed hypothesis test: the alternative hypothesis is of the form - H1 : μ ≠ 50. A 95% confidence interval is going to be _______ a 99% confidence interval. - narrower than