Question

A cognitive psychologist is interested in whether taking a speed-reading course increases reading speed. She has students complete a reading speed test before and after a six-week speed-reading course. In the beginning of the study, a randomly selected group of 121 students scored an average of 252 words per minute on the reading speed test. Since the sample size is larger than 30, the cognitive psychologist can assume that the sampling distribution of md d is normal. She plans to use a repeated-measures t test. The cognitive psychologist identifies the null and alternative hypotheses as: h₀ : μd d 0 h₁ : μd d 0

Answer 1

The question involves hypothesis testing using a repeated-measures t-test in cognitive psychology to assess the effectiveness of a speed-reading course. The null hypothesis indicates no change in reading speed, while the alternative suggests a difference. Assumptions of a t-test include a random sample and a normally distributed population or large sample size.

Step-by-step explanation:

The question relates to the application of hypothesis testing in cognitive psychology, specifically examining the impact of a speed-reading course on the reading speed of students. The cognitive psychologist employs a repeated-measures t-test to determine if there is a statistically significant difference in reading speeds before and after the course. The null hypothesis states that there is no difference in mean reading speeds (μd = 0), while the alternative hypothesis suggests that there is a difference (μd ≠ 0). A key consideration for the t-test is that it assumes a normal distribution of differences, which is met here due to the sample size being larger than 30.

Hypothesis testing is a method used in statistics to determine whether there is enough evidence in a sample of data to infer that a certain condition holds for the entire population. To perform a t-test, certain assumptions must be satisfied, such as the data being a simple random sample and the population being normally distributed or the sample size being large enough to justify a normal approximation.