What do students need to do with the data in Table 1 to answer their teacher's question?

When trying to draw meaningful conclusions from research data, it's not enough to simply observe the results. Students need to employ statistical analysis to determine if any observed differences are statistically significant or simply due to chance. This is where inferential statistical tests, such as the Chi-squared test, come in.

In this scenario, the students would need to perform a Chi-squared test on the data presented in Table 1. This is because:

* The data is categorical/nominal. The variables being measured (e.g., "Type of Film" and "Emotional Response") are divided into distinct categories. * The study uses an independent design. Different groups of participants are being compared (those watching horror films vs. those watching comedies).

Here's how the students would proceed:

1. Calculate the Chi-squared statistic (observed value). This involves comparing the observed frequencies in each cell of the table to the expected frequencies (what would be expected if there was no relationship between the variables). 2. Determine the degrees of freedom. This is calculated based on the number of rows and columns in the table. 3. Choose a significance level (alpha). This is typically set at 0.05, meaning there's a 5% acceptable risk of incorrectly rejecting the null hypothesis. 4. Compare the calculated Chi-squared value to the critical table value. Students would find this critical value in a Chi-squared distribution table, using the degrees of freedom and chosen significance level. * If the calculated value is GREATER than the critical table value: The results are statistically significant. This means there's less than a 5% probability that the observed difference in emotional responses between the two film groups is due to chance. The students would then reject the null hypothesis and accept their research hypothesis. * If the calculated value is LESS than the critical table value: The results are not statistically significant. The observed difference could easily be due to random variation. The students would fail to reject the null hypothesis.

In essence, the Chi-squared test helps determine if the observed relationship between watching a certain type of film and experiencing a particular emotional response is strong enough to be considered statistically significant and not just a random occurrence.