The sample dataset has placement test scores (out of 100 points) for four subject areas: English, Reading, Math, and Writing. Students in the sample completed all 4 placement tests when they enrolled in the university. Suppose we are particularly interested in the English and Math sections, and want to determine whether students tended to score higher on their English or Math test, on average. We could use a paired t test to test if there was a significant difference in the average of the two tests.

BEFORE THE TEST

Variable English has a high of 101.95 and a low of 59.83, while variable Math has a high of 93.78 and a low of 35.32 (Analyze > Descriptive Statistics > Descriptives). The mean English score is much higher than the mean Math score (82.79 versus 65.47). Additionally, there were 409 cases with non-missing English scores, and 422 cases with non-missing Math scores, but only 398 cases with non-missing observations for both variables. (Recall that the sample dataset has 435 cases in all.)

Run a paired sample t test to examine the english and math scores and answer the following questions

1. what was your paird samples result, write it in this format, t(df) = X.XX, p = .xxx. df = degrees of freedom, t = t value, p = p value
2. Was there a statistical difference between the math and english scores ?
3. What can you say about the difference based on your results.

Question 2

Use Paired Samples dataset 2 to answer the following

1. What was your paird samples result, write it in this format, t(df) = X.XX, p = .xxx. df = degrees of freedom, t = t value, p = p value
2. Is there a significant difference between apercentnegative and bpercent negative?
3. Did illusory correlations happen in this group of people?
4. What can you say about the difference based on your results?