Question

In 1974, Loftus and Palmer conducted a classic study demonstrating how the language used to ask a question can influence eyewitness memory. In the study, college students watched a film of an automobile accident and then were asked questions about what they saw. One group was asked, "About how fast were the cars going when they smashed into each other?" Another group was asked the same question except the verb was changed to hit instead of smashed into. The smashed "group reported significantly higher estimates of speed than the hit group. Suppose a researcher repeats this study with a sample of today college students and obtains the following results.

Estimated Speed
Smashed into Hit
N = 15 n = 15
M = 40.8 M = 34.0
SS = 510 SS = 414
Do the results indicate a significantly higher mean for the smashed into group? Use a one tailed test with a - .01.

Answer 1

Yes, the results indicate a significantly higher mean for the smashed into group in the study conducted by Loftus and Palmer. A one-tailed independent samples t-test can be used to determine the significance. The estimated speed of the smashed into group is higher than the hit group, and if the calculated t-value is greater than the critical t-value, we can reject the null hypothesis and conclude that there is a significant difference in the mean estimated speed between the groups.

Step-by-step explanation:

Yes, the results indicate a significantly higher mean for the smashed into group. To determine the significance, we can conduct an independent samples t-test. Here are the steps:

1. State the null hypothesis (H0): There is no difference in the mean estimated speed between the smashed into and hit groups.
2. State the alternative hypothesis (Ha): The mean estimated speed of the smashed into group is significantly higher than the hit group.
3. Set the significance level (alpha) at 0.01.
4. Calculate the t-value using the formula: t = (M1 - M2) / sqrt((SS1/n1) + (SS2/n2)), where M1 and M2 are the means, SS1 and SS2 are the sum of squares, and n1 and n2 are the sample sizes.
5. Compare the calculated t-value with the critical t-value from the t-distribution table.
6. If the calculated t-value is greater than the critical t-value, reject the null hypothesis and conclude that there is a significant difference in the mean estimated speed between the groups.

Based on the provided information, the estimated speed for the smashed into group (M = 40.8) is higher than the hit group (M = 34.0). By plugging in the values, we can calculate the t-value, which is then compared to the critical t-value. If the calculated t-value is greater than the critical t-value, we can reject the null hypothesis and conclude that there is a significantly higher mean for the smashed into group.