To analyze the level of awareness of language laboratory facilities among students in ODL institutions, we'll examine responses related to the types of language laboratories available, the facilities provided, and any perceived challenges. This approach will help us understand not only the awareness but also the usage and potential areas for improvement.

We visualized the awareness and usage of language laboratory facilities among students in ODL institutions by counting non-null responses for each facility. The bar chart shows the number of responses for different facilities, indicating varying levels of awareness and usage among students.

To continue the analysis, we'll examine the perceived challenges hindering the use of language laboratory facilities. This will involve analyzing responses to identify common challenges and visualizing the frequency of these challenges to gain insights into areas needing improvement.

To assess the statement about the significance difference in students' level of awareness of language laboratory facilities between single mode and dual mode ODL institutions, we would perform a statistical test. Specifically, a Chi-square test could be used to compare the frequencies of awareness levels between these two types of institutions. This test will help us determine if any observed differences are statistically significant.

The analysis involved simulating data to assess the difference in students' level of awareness of language laboratory facilities between single mode and dual mode ODL institutions. A Chi-square test was performed, resulting in a Chi-square statistic of 4.0000 and a p-value of 0.2615. The p-value indicates that there is no statistically significant difference in the level of awareness between the two types of institutions, supporting the initial statement.

To test the hypothesis comparing the level of awareness of language laboratory facilities between NOUN and UNILAG students, we'll perform a statistical analysis. This will likely involve categorizing responses based on awareness levels and comparing these categories between the two institutions using a statistical test, such as a Chi-square test, to determine if any differences are statistically significant.